2012
Annual Report
of the
U. S. Hospital
IT Market
An industry report provided by
and
This historical report
of the U.S. Hospital
IT Market is brought
to you as an online
resource from the
Dorenfest Institute.
▶▶ Table of Contents
2011 Hospital Industry Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2011 Hospital IT Budget and Expenses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Financial Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Financial Decision Support Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Human Resource Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Revenue Cycle Management Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Next Generation Revenue Cycle Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Health Information Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Document Management/Electronic Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
Nursing Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Ancillary Department Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Laboratory Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Operating Room (Surgery) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Ambulatory (Hospital Owned/Managed) IT Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Radiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Cardiology PACS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Bar Code Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Electronic Medical Record Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
The EMR Adoption ModelSM: Measuring Clinical IT Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
HIMSS Mission
To lead healthcare transformation through the effective use of health information technology.
© 2012 by the Healthcare Information and Management Systems Society and HIMSS Analytics.
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For more information about HIMSS Analytics, please visit www.himssanalytics.org.
▶▶ A Letter from the EVP and CEO of HIMSS Analytics and HIMSS
Dear Healthcare Executive:
Welcome to the 2012 Annual Report of the U.S. Hospital IT Market, produced jointly by the Healthcare Information and Management
Systems Society (HIMSS) and HIMSS Analytics LLC, the wholly-owned, not for profit market research arm of HIMSS. We are very
pleased to present this comprehensive view of the current state of IT adoption in U.S. hospitals in 2012.
In 2011, the Department of Health & Human Services (HHS) made incentive payments of well over $2 billion to American hospitals and eligible
providers authorized under the HITECH provisions of the 2009 American Recovery and Reinvestment Act (ARRA). We at HIMSS Analytics
believe the incentive program is beginning to have some beneficial effect in healthcare IT adoption in U.S. hospitals. In 2011, we saw 102 hospitals
achieve Stage 6 on the EMRAM model, up from 80 in 2010. In addition, we saw a 90 percent growth in hospitals achieving Stage 5, which
requires closed loop medication administration, a difficult achievement requiring process changes affecting pharmacy, nursing and medical staff.
In February 2011, HIMSS Analytics released research that indicated that 25 percent of surveyed hospitals have the capability to meet
10 or more of the process core measures and at least five of the menu items required by the ARRA Meaningful Use program.1 Hospitals
in the industry have made some progress since that time as the December 2011 report2 indicates that 27 percent of hospitals are at this
level. Additionally, nine percent of hospitals have the capability to meet all 14 core metrics and at least five menu items.
HHS has commented that there is a “perfect storm” of impending deadlines facing healthcare CIOs. In autumn, Secretary of HHS,
the Honorable Kathleen Sebelius agreed with the recommendation of the new National Coordinator for Health Information Technology,
Dr. Farzad Mostashari, that the Meaningful Use Stage 2 requirements deadline should be postponed by one year to 2014. The final
regulations for MU Stage 2 are due out in early 2012.
Another area that has picked up quite a bit of momentum in 2012 is mobile health. In order to help grow the productive use of mobile
health and to identify key barriers to success, HHS formed the Text4Health Task Force. In 2011, HIMSS created an mHealth community
and has produced an initial series of surveys and white papers on mobile health.3
In November, the Institute of Medicine (IOM) released its report on Health IT and Patient Safety, Building Safer Systems for Better Care.
The report identified recommendations designed to bring about rapid detection and correction of patient safety problems which could have
been brought about by the use of IT. Without proper training, support and usability design, healthcare IT can add burden to the healthcare
delivery process.
Conversely, there are terrific examples of appropriately applied healthcare IT investments which have generated quality and efficiency
improvements. In 2011, HIMSS Analytics produced its first in a series of reports on Return on Investment in healthcare IT.4 Future reports
will identify additional quality and efficiency improvements identified by healthcare organizations.
We believe that 2011 will be seen as the first of several years in which the stimulus provided by ARRA began to make an effect on helping
U.S. hospitals reach a “tipping point” in IT investments. You can count on HIMSS Analytics and HIMSS to equip you to stay on top of
these changes, and to be your most trusted and comprehensive source of information on the adoption of IT applications and the progress
toward implementing those applications in today’s U.S. healthcare provider environment.
We hope you find this eighth edition of the Annual Report of the U.S. Hospital IT Market informative, compelling, and stimulating.
Best regards,
John P. Hoyt
Executive Vice President
HIMSS Analytics
1
2
3
4
http://www.himssanalytics.org/general/pr_20110222.asp
http://www.himssanalytics.org/general/mkt.asp
http://www.mhimss.org/
http://www.himss.org/innovators/research.asp
H. Stephen Lieber
President and CEO
HIMSS
▶▶ 2011 Hospital Industry Overview
Looking Back; Looking Ahead: The Year in Review
At the start of 2012, we sit at a precipice where we could be within
a year of significant change due to the 2012 Presidential election
this autumn. The economic recovery from the meltdown of 2008
has been unsteady and slow, but not unlike other recoveries since
the early 1990s. Unemployment seemed stuck at approximately
9 percent, but showed some downward movement in November,
2011. Because hospitals are typically a “lag indicator,” the effect
of the recession with concomitant loss of health insurance hit
the hospitals in 2009 and 2010. HIMSS Analytics® data show that
the number of hospitals and integrated delivery networks (IDNs)
that reported an increase in their IT budgets actually saw
a notable decrease in 2009–2010, but had a recovery to previous
levels in 2011.
Slow economic growth has led to greater than expected deficits
through continued transfer payments and less than projected tax
revenues at both the federal and state levels. This has added
significant pressure to state Medicaid programs and numerous
federal programs are being scrutinized for effectiveness.
The American Recovery and Reinvestment Act of 2009 (ARRA)
funding has been effective in stimulating the industry for further
adoption of healthcare IT. The HIMSS Analytics Meaningful Use
report of September, 2011 showed that 41 percent of hospitals are
ready or most likely to achieve MU Stage 1. ARRA funding has
clearly stimulated the acute care IT industry and one sign is the
increase rate of progression up the HIMSS Analytics EMR
Adoption Model scale. In 2011, we saw 102 hospitals achieve
Stage 6, up from 80 in 2010. In addition, we saw a 90 percent
growth in hospitals achieving Stage 5, which requires closed loop
medication administration, a difficult achievement requiring process
changes affecting pharmacy, nursing and attending medical staff.
Another sign of certain stimulus of the acute care IT industry is
the continued struggle that hospitals have in recruiting and retaining
clinical system skills for implementation and support of IT systems.
Our Senior IT Executives tell us that consulting firms are offering
significant sign-on bonuses to experienced hospital-based
implementers and that retaining trained resources at hospital
salaries is becoming extremely difficult.
The election of 2012 may become pivotal to the ARRA Health
Information Technology for Economic and Clinical Health Act
(HITECH) program. How the program will be affected is anyone’s
guess, but it is clear that it will be scrutinized and proof of
successful progress will be sought from every corner.
In December, HHS announced that it had awarded $1.38 billion
in EHR incentive payments through Medicare and $1.5 billion in
EHR incentive payments through Medicaid. Medicare has given
payments to 15,255 eligible healthcare providers, 566 hospitals
participating in both the Medicare and Medicaid EHR incentive
programs, and 38 hospitals participating only in the Medicare
EHR incentive program. Medicaid had given payments to 14,089
eligible healthcare providers, and 1,043 hospitals participating either
in both EHR incentive programs or only in the Medicaid incentive
2 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
program. Clearly this program has made an impact, but still there
are significant issues with this “perfect storm” of burdening
requirements on health system chief information officers (CIOs).
The Meaningful Use Stage 2 requirements will be delayed one
year due to the “perfect storm” facing healthcare IT executives.
The unfunded mandate for the new electronic data interchange
format 5010 due for implementation on January 1, 2012, plus the
massive switch to ICD-10 Procedure Coding System (PCS) along
with the drive to achieve Meaningful Use Stage 1 has caused a
logjam in the capacity to take on any more change at most hospitals
and IDNs. The Healthcare Information Technology (HIT) Policy
Committee recommended a one-year delay for the MU Stage 2
requirements. Farzad Mostashari, MD, the new National Coordinator
for Health Information Technology, said that he agreed with the
recommendation by the HIT Policy Committee to delay Stage 2
to 2014. In the first week of December, 2011, Kathleen Sebelius,
U.S. Department of Health and Human Services (HHS) Secretary,
stated that HHS also agreed as well and will delay Stage 2, allowing
providers more time to adopt health IT in 2011 without meeting
the new requirements until 2014.
The final rules for the Accountable Care Organizations (ACOs)
under the Medicare Shared Savings Program were released in
October, 2011. Many provisions in the final rule were more relaxed
than first proposed, such as 33 quality measures instead of 65. The
final rule specified that ACOs must still meet a minimum threshold
of savings, but they can earn back more of the savings they generate
from what was originally proposed. With this final rule, the race has
begun to succeed as an ACO. We believe this may be the beginning
of a new wave of healthcare IT investment for many organizations
evolving into an ACO. Following the investments in an EHR,
investments in clinical and business intelligence, data warehousing,
cost finding and new revenue cycle systems will be needed for many
organizations. Additionally, we believe this will stimulate a new
wave of mergers and acquisitions which itself will generate a minigrowth of IT investments to standardize on major software suites in
clinical, patient financial and back office applications. The effect of
this on the vendor side will be continued consolidation.
In November, the Institute of Medicine (IOM) released its report
on Health IT and Patient Safety, Building Safer Systems for Better
Care. The report, commissioned by the Office of the National
Coordinator for Health IT, produced a series of recommendations
designed to identify the best approaches for surveillance and
reporting activities to bring about rapid detection and correction
of patient safety problems which could have been brought about by
the use of information technology in the directing or documenting
of patient care. The IOM also stated that “Continuing to use paper
records can place patients at unnecessary risk for harm and
substantially constrains the country’s ability to reform health care.”
This is not a call to halt or slow down health IT deployment, but a
call to initiate the creation of an EHR safety action and surveillance
plan while we continue to move ahead with the nations’ goals of
making interoperable EHRs pervasive.
▶▶ 2011 Hospital Industry Overview con tinued
Last year saw the notable entry into the healthcare delivery and
the healthcare IT market by large payers. Aetna purchased
Medicity, which has a strong foothold in the Healthcare Information
Exchange (HIE) market. Additionally, United Health purchased
the 2,300 physician group practice, Monarch Health Care in
California. Highmark, another major payer, made a significant
investment in West Penn Allegheny Health System. Clearly these
types of investments by payers indicate a trend toward payers
acquiring source data to drive clinical and business intelligence
knowledge for effective quality improvement drivers and to help
better position payers to successfully negotiate new levels of
bundled payment programs.
While federal funding of HIEs continued in 2011, serious questions
remain on whether federally funded HIEs will exist in the long run
without federal funding; the business case has not become obvious.
In early 2012, a new level of standards is to be finalized under the
rubric of Nationwide Health Information Network (NwHIN). The
NwHIN is a set of standards and policies that enable secure health
information exchange over the Internet.
It seems clear that a major uptick in activity in the market at
this point is the development of private HIEs to serve the
increasing number of multi-provider integrated delivery systems
and cooperative private exchanges in local and regional markets.
We expect to see more payers enter this space as these exchanges
are a major source of clinical consumption data that will help
develop the next wave of efficacy research and resultant best
practices and protocols.
The ARRA act also provisioned the Federal Coordinating
Council for Comparative Effectiveness Research. Clearly as
hospitals implement EHRs, a wealth of data is being collected in
a way that we have never had before. The goal of the Comparative
Effectiveness Research program is to build the tools and
methodologies to utilize this data to support clinical research and
develop optimized care protocols which can be incorporated into
the clinical decision support capabilities of EMRs and also
eventually drive pay for performance. Hospitals and IDNs that
invest in clinical and business intelligence tools and resources
will be in a better position to succeed in positioning themselves to
meet the new quality and efficiency requirements. Included in this
research will be pharmaceutical efficacy data that goes beyond
Food and Drug Administration (FDA) trials.
Acquisition and mergers of acute care providers increased in
2011 to a new level. As IDNs position themselves to succeed
as an ACO and gain a stronger market presence, the number of
mergers and acquisitions in 2011 outpaced the record 2010.
HIMSS Analytics data shows that the number of hospitals per
IDN continued to grow by 4.5 percent in 2011. We see no force
to prevent this trend from continuing. The desire of the Federal
Government, notably the White House and HHS to have the ACO
program succeed, may result in a confrontation with the anti-trust
watch dogs in the Justice Department. No doubt, more clarity
here is needed in the market.
Long-time HIS vendor, McKesson Provider Technologies,
announced in mid-December that it is going to focus their continued
development on the Paragon platform because it is an integrated
platform not composed of numerous subsystems that were acquired
through acquisitions. This major announcement in the health IT
market will take several years to have an effect. Clearly the market
has spoken that the preferred solution is for integrated clinical suites
and that the best of breed environment glued together by difficultto-support interfaces may clearly become a thing of the past.
So, looking ahead, where are we going in 2012 and beyond? It is
clear that federal policy has stimulated the adoption of healthcare
IT and that the drive to develop a successful ACO, patient-centered
medical home and bundled payment reform has picked up steam.
Will this be derailed or significantly curtailed after the 2012
election? At this point, many political analysts are predicting
that the Senate will stay with a conservative majority and that
the House may switch from a liberal majority or that the existing
liberal majority may be significantly reduced. Clearly such an
outcome will have some affect on these programs. One fact is
clear—healthcare providers will none the less be expected to
improve quality care coordination across care settings, while
simultaneously reducing costs and improving efficiency.
Once healthcare providers demonstrate compliance with Stage 1
meaningful use, they will have little time to rest on their laurels.
Instead, they will be faced in rapid succession with several other
major IT challenges:
• Complying with unfunded government mandates for the new
version 5010 electronic data interchange (EDI) transactions
by January 1, 2012.
• Complying with unfunded government mandates to convert
to ICD-10 diagnosis coding by October 1, 2013.
• Meeting the EHR-related Stage 2 meaningful use requirements
by 2014
• Meeting, by 2014, the anticipated external connectivity
requirements of Stage 2 meaningful use related to the electronic
exchange of patient information with other providers, local,
statewide and national HIEs, public health agencies and other
entities, including patients.
• Addressing the organizational and process changes required
to meet the higher mandated levels of compliance with
computerized practitioner order entry (CPOE) and clinical
decision support (CDS) usage in order to secure continued
meaningful use payments.
At the same time another healthcare IT wave has emerged as almost
unaffected by the “perfect storm” of federal mandates. The growth
of mobile health both for providers and consumers is gaining
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
3
▶▶ 2011 Hospital Industry Overview con tinued
unforeseen momentum. According to a recent study by the World
Health Organization, the use of mobile and wireless technologies to
support healthcare has the potential to transform the face of health
service delivery, driven by rapid advances in the development of
mobile technologies and applications, growth in cellular networks
and new opportunities to integrate mobile health into currently
delivered services.1 In order to identify ongoing mHealth initiatives
and future projects that would promote mhealth, HHS has formed
the Text4Health Task Force.2
“Basic research is what I’m doing when I don’t
know what I’m doing.” –Werhner von Braun
The challenges associated with a multi-year EMR implementation
process can often cause organizations to lose sight of a critical
guiding IT principle: technology is simply a means to the end, not
an end unto itself. As we enter 2012, we see much of the industry’s
attention focused on implementing EMRs, yet the experience of
early adopters has clearly and repeatedly demonstrated that
implementing an EMR alone will not achieve cost savings, quality
improvements or revenue enhancements unless it is a component of
a broader plan with clearly defined organizational and operational
improvement objectives. The most successful organizations are
those that have used their EMR as a foundation for implementing
process change and complementary technologies, such as business
analytics and clinical decision support, to achieve improved
outcomes and reduced costs. A growing body of literature in
respected journals and conference proceedings supports the idea
that quality improvements truly can be derived from appropriately
adopted healthcare IT concomitant with process redesign. HIMSS
Analytics published the first in a series of reports this year on the
return on investment (ROI) of clinical IT investments. There are
clear examples of medication safety improvements, cost savings
when CPOE is supported by evidence-based best practice alerts,
and savings to health plans through reduced healthcare consumption,
just to name a few. Naysayers who say that healthcare IT investments
do not drive quality and efficiency benefits are clearly wrong.
However, can healthcare IT be inappropriately applied? Certainly,
inadequate training and poor usability design can feed an error-prone
environment. Providers and software developers alike must be on
guard to optimize the tremendous power of healthcare it appropriately.
Does healthcare IT reduce costs immediately? Certainly not.
HIMSS Analytics data suggests that the percent of total operating
expenses spent on IT increases as hospitals move up the HIMSS
Analytics Electronic Medical Record Adoption Model (EMRAM)
scale. But a more detailed look indicated that the most “expensive
stages,” where the percent of total expenses spent on IT are the
highest, are Stages 4 and 6. Stage 4 is where CPOE is deployed,
and Stage 6 is where physician documentation is deployed. Both of
these stages are intense in medical staff education which requires
significant skilled resources. HIMSS Analytics data shows that
Stage 7 hospitals actually spend a slightly smaller percent of total
expenses on IT than Stage 6 hospitals. Also, HIMSS Analytics
data shows that the operating margins of Stage 7 hospitals are
significantly higher than any other Stage. The payoff has begun.
Let us continue this progression.
“I was brought up to believe that the only
thing worth doing was to add to the sum of accurate
information in the world.” –Margaret Mead
As the pace of change quickens, even legacy applications can
be expected to enjoy a renaissance. We believe that as the ACO
program and payment reform gain momentum, there will be
significant provider mergers and acquisitions. This will stimulate
three major activities: First, a consolidation on clinical, revenue
cycle and enterprise resource planning (ERP) platforms, thus
decommissioning of systems in the acquired entities which will
require a new wave of consultants to help data conversion and
implementations of some legacy systems. Second, the legacy
revenue cycle systems will need significant enhancements to meet
the needs of a bundled payment environment. Closely adjacent to
this, cost accounting will take on a new key role. Third, to drive
down costs, we see a consolidation of patient accounting and supply
chain operations, again requiring a new wave of revenue cycle
management (RCM) and ERP solutions.
Finally, as hospitals accumulate unprecedented levels of digital
data, we see two major derivatives. First, clinical and business
intelligence will take on a central role to help direct the hospital to
the most effective care protocols and efficiency. Second, hospital
data centers themselves will become increasingly taxed to support
and hold all this data. Manageability and physical space become
key issues for providers. Outsourced data centers or entire hosting
of systems in an application service provider (ASP) model will
clearly grow, harking back to the beginning of our industry when
shared models were the norm. It is a delight to see that HIMSS
Analytics has identified eight critical access hospitals as Stage 6,
and five of those eight utilize an ASP model.
“The way of progress is neither swift nor easy.”
–Marie Curie
Years from now, health IT history buffs will likely look back on
2011 as a year when acute care IT adoption gained momentum,
spurred on by federal stimulus dollars. But the past is merely a
prologue, as we expect the pace of change that characterized 2011
to accelerate in 2012 and beyond unless the stimulus funds are
stopped entirely, which is unlikely. Should the ARRA incentive
program continue, we expect a number of significant provider
mergers and a new wave of investment in financial systems to
support payment reform to commence by the middle of this decade?
As Confucius once said, “May we live in interesting times.”
1
Mhealth: New Horizons for Health Through Mobile Technologies. World Health Organization. 2011
http://www.himss.org/content/files/Code%20491%20-%20mHealth-New%20horizons%20for%20health%20through%20mobile%20technologies_WHO_2011.pdf
Accessed November 22, 2011
2
HHS.gov website on mhealth. http://www.hhs.gov/open/initiatives/mhealth/
Accessed November 22, 2011
4 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
▶▶ 2011 Hospital Industry Overview con tinued
HIMSS Analytics Stage 7 Awards
HIMSS Analytics launched the EMR Adoption ModelSM
(EMRAM) in 2005 to track adoption of EMR applications
within hospitals and health systems. The EMRAM scores
hospitals in the HIMSS Analytics® Database on their progress in
completing 8 Stages (0–7), with the goal of reaching Stage 7, an
environment in which paper charts are no longer used to document
the delivery of patient care. In 2009, HIMSS Analytics honored
38 Stage 7 hospitals, the first hospitals to reach Stage 7. By 2011,
the number of hospitals swelled to 66, including the two
international Stage 7 hospitals.
Stage 7 hospitals are positioned to share clinical information
via standard electronic transactions with all entities within health
information exchange networks (i.e., other hospitals, ambulatory
clinics, sub-acute environments, employers, payers and patients).
This stage allows the healthcare organization to support the true
sharing and use of health and wellness information by consumers
and providers alike. Also at this stage, healthcare organizations use
data warehousing and mining techniques to capture and analyze
care data for performance improvement and advancing the use of
clinical decision support protocols. As such, it is these organizations
that are best positioned to reach Stage 1 meaningful use.
“The reasonable man adapts himself to the world;
the unreasonable one persists in trying to adapt the
world to himself. Therefore, all progress depends upon
the unreasonable man.” –George Bernard Shaw
The following is a list of healthcare organizations that have
achieved Stage 7 of EMR Adoption model (as of December, 2011).
These hospitals exemplify organizations that are using IT as the
supporting infrastructure for their advances.
In 2011, 14 new hospitals were validated as Stage 7, including one
from Germany. They are listed below:
Name
Alfred I. DuPont Hospital for Children
Children’s Medical Center at Legacy
Deaconess Cross Point Center
Deaconess Gateway Hospital
Deaconess Hospital
Florida Hospital – Flagler
The Heart Hospital
Kaiser Permanente - Moanalua Medical Center
Rochester Methodist Hospital
St. Mary’s Hospital of Rochester
Tucson Medical Center
UC San Diego Medical Center – Hillcrest
UC San Diego Medical Center – Thornton Hospital
Universitätsklinikum Hamburg-Eppendorf
City
Wilmington
Plano
Evansville
Newburgh
Evansville
Winter Park
Newburgh
Honolulu
Rochester
Rochester
Tucson
San Diego
La Jolla
Hamburg
State
DE
TX
IN
IN
IN
FL
IN
HI
MN
MN
AZ
CA
CA
GER
Hospitals validated as Stage 7 prior to 2011.
Name
American Family Children’s Hospital
Children’s Hospital Boston
Children’s Hospital of Pittsburgh
Children’s Medical Center of Dallas
Citizens Memorial Healthcare
Evanston Hospital
Glenbrook Hospital
Highland Park Hospital
Kaiser Permanente – Anaheim Medical Center
Kaiser Permanente – Antioch Medical Center
Kaiser Permanente – Baldwin Park Medical Center
Kaiser Permanente – Bellflower Medical Center
Kaiser Permanente – Fontana Medical Center
Kaiser Permanente – Fremont Medical Center
Kaiser Permanente – Fresno Medical Center
Kaiser Permanente – Hayward Medical Center
Kaiser Permanente – Los Angeles Medical Center
Kaiser Permanente – Manteca Medical Center
Kaiser Permanente – Modesto Medical Center
Kaiser Permanente – Moreno Valley Community Hospital
Kaiser Permanente – Oakland Medical Center
Kaiser Permanente – Orange County/Irvine Medical Center
Kaiser Permanente – Panorama City Medical Center
Kaiser Permanente – Richmond Medical Center
Kaiser Permanente – Riverside Medical Center
Kaiser Permanente – Redwood City Medical Center
Kaiser Permanente – Roseville Medical Center
Kaiser Permanente – Sacramento Medical Center
Kaiser Permanente – San Diego Medical Center
Kaiser Permanente – San Francisco Medical Center–Geary
Kaiser Permanente – San Jose Medical Center
Kaiser Permanente – San Rafael Medical Center
Kaiser Permanente – Santa Clara Homestead Medical Center
Kaiser Permanente – Santa Rosa Medical Center
Kaiser Permanente – South Bay Medical Center
Kaiser Permanente – South Sacramento Medical Center
Kaiser Permanente – South San Francisco Medical Center
Kaiser Permanente – Sunnyside Medical Center
Kaiser Permanente – Vacaville Medical Center
Kaiser Permanente – Walnut Creek Medical Center
Kaiser Permanente – West Los Angeles Medical Center
Kaiser Permanente – Woodland Hills Medical Center
Sentara Bayside
Sentara CarePlex
Sentara Leigh Hospital
Sentara Norfolk General Hospital
Sentara Virginia Beach General Hospital
Sentara Williamsburg Regional Medical Center
Skokie Hospital
Stanford Hospital & Clinics
University of Wisconsin – Hospital & Clinics
Seoul National University Bundang Hospital
City
Madison
Boston
Pittsburgh
Dallas
Bolivar
Evanston
Glenview
Highland Park
Anaheim
Antioch
Baldwin Park
Bellflower
Fontana
Fremont
Fresno
Hayward
Los Angeles
Manteca
Modesto
Moreno Valley
Oakland
Irvine
Panorama City
Richmond
Riverside
Redwood City
Roseville
Sacramento
San Diego
San Francisco
San Jose
San Rafael
Santa Clara
Santa Rosa
Harbor City
Sacramento
San Francisco
Clackamas
Vacaville
Walnut Creek
Los Angeles
Woodland Hills
Virginia Beach
Hampton
Norfolk
Norfolk
Virginia Beach
Williamsburg
Skokie
Stanford
Madison
Seoul
State
WI
MA
PA
TX
MO
IL
IL
IL
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
OR
CA
CA
CA
CA
VA
VA
VA
VA
VA
VA
IL
CA
WI
KOR
This is the eighth edition of the Annual Report of the U.S. Hospital
IT Market, and we hope you find it thought-provoking, stimulating,
and informative.
The HIMSS Analytics Research Team
John Hoyt
Lorren Pettit
Jennifer Horowitz
Roger Park
Aviva Zupancic
Nikita Macklin
Bobby Maslowski
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
5
▶▶ 2011 Hospital IT Budget and Expenses
As in past years, this section of the report highlights financial
benchmarks which provide a glimpse into information technology
(IT)-related spending as a percentage of organizations’ overall
spending. Analyses are presented from three different perspectives.
The first set of ratios shows the mean and median IT operating
expense (OPEX) as a percentage of total hospital operating expense.
In this view, capital expenses are excluded from both the numerator
and the denominator. The second set of ratios shows the average
and median spending ratios for the total IT budget, including both
operating and capital expense (CAPEX) for this fiscal year, as a
percentage of the organizations’ overall operating and capital
expenses. The third set of ratios focuses on the IT department
capital expenses for this fiscal year, as a percentage of the hospital’s
total capital expense. Each set of ratios are examined by bed-size
range, hospital type and region.
In our opinion, the sharp and pervasive downward trend in these
ratios from 2009 to 2010 clearly reflects the impact of the economic
crisis. This trend was more pronounced among larger hospitals and
is more evident in the ratios which include capital expense.
Although the start of financial crisis can be traced back to
September, 2007, the rise in unemployment and the worst of the
economic news did not begin to reveal itself until the latter part of
2008 and it was not until the early months of 2009 that the bottom
of the stock market was reached. This period coincides with the
time that the crisis began to directly affect healthcare provider
organizations (HCOs). According to data from HIMSS Analytics,
the percent of hospitals stating that their IT operating budgets were
increasing continued to fall each quarter in 2010, until the 4th
quarter when a return to a normalcy for that statistic occurred.
According to an annual analysis by the Centers for Medicare and
Medicaid Services (CMS), national healthcare spending rose at a
rate of 3.9 percent in 2010, slightly lower than 2009’s record low
growth of 4 percent. The recession and its resulting decline in the
number of people covered by health insurance have been slowing
the rate of healthcare spending since 2007. In 2010, according to
CMS projections, healthcare spending will stay at 17.6 percent of
GDP, the same rate for two years. Healthcare spending slowed
across all sources, including the federal government, state
governments, private employers and individuals.
The impact on hospitals was largely attributable to two factors—
a drop in utilization, which generally tracked to unemployment, and
the 3.4 percent reduction in Medicare’s private health plan payments.
By early 2011, lingering unemployment and the expiration of COBRA
benefits continued to slow elective admissions in many hospitals.
In November and December of 2011, we began to see some growth
in national employment such that the unemployment rate began to
tick down below the 9 percent range where it had been stuck for
most of 2011. The number of layoffs in U.S. hospitals in 2011 was
below the levels in 2009 and 2010 respectively according to the
Bureau of Labor Statistics (BLS). IN 2011, there were an estimated
120 “mass layoffs” at U.S. hospitals (affecting 50 or more employees
at once, a BLS definition) compared to 152 in 2009 and 137 in 2010.
With the growth of employment beginning a new economic cycle,
we believe the number of mass layoffs will continue to decelerate
for the next few years.
6 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Table hB1
% of Total IT Operating Expense/Total
Hospital Operating Expense–Overall
Avg
Median
N
2009
2.67%
2.08%
383
2010
2.40%
1.93%
471
2011
2.39%
2.11%
475
2009
4.45%
3.46%
381
2010
2.77%
2.26%
469
2011
4.87%
3.92%
436
2009
20.10%
14.27%
284
2010
17.32%
10.27%
211
2011
17.89%
12.14%
300
Table hB2
% of Total IT Budget/Total Hospital
Expense–Overall
Avg
Median
N
Table hB 3
% IS Capital Expense Last Year/
Total Hospital Capital Expense–Overall
Avg
Median
N
Some evidence exists to point to an increase in hospital capital
spending, possibly spurred on by the assumption of a decrease in
cash flow after 2014 when planned Medicare reductions take place
due to the Affordable Care Act. Of course, increased admissions
from increased coverage availability may offset that decrease from
Medicare. That remains to be seen.
In 2011, the average ratio of IT department operating expense to
total hospital operating expense remained relatively the same while
the median ratio indicated a slight increase (see Table HB1).
Evaluating the average and median numbers for the ratio of the
total IT budget (includes operating and capital expenses for this
year) to total hospital operating expense, the 2011 data compared
more directly with the 2009 data than 2010. When compared to
2009, the 2011 data indicated an increase in the average and median
ratios. The average ratio increased 0.42 percent from 2009 to 2011
while the median ratio increased by 0.46 percent. The 2010 data
should be interpreted as an anomaly for this particular ratio due to
the recession since hospitals are generally considered a lag indicator
(see Table HB2).
In regard to the ratio of IS department capital expense (from last
fiscal year) to the hospital’s overall capital expense, the average and
median percentage increased from 2010 to 2011. The average ratio
increased by 0.57 percent while the median percentage jumped by
almost two percent (see Table HB3).
The general increase in these ratios appears to be modest; however,
this is a good indicator that the economy has recovered to a point
where hospitals are beginning to feel more at ease with spending
and/or budgeting more in 2011.
IT OPEX as a Percentage of Hospital Total OPEX
From 2009 to 2010, the hospitals in the mid-sized bed range
(301–400 beds and 401–500 beds) showed an increase in IT OPEX
as a percentage of the hospital total OPEX spending, but in 2011,
the increase of IT OPEX spending ratio shifted to smaller (0–100
beds and 101–200 beds) and larger (501–600 and 600+ beds)
segments (see Table HB4). The 501–600 bed segment showed the
most increase at 0.63 percent while the bed segment that indicated
the most decline was in the 201–300 bed segment—a negative 0.45
percent. Segments larger than 200 beds but smaller than 500 beds
demonstrated a slight decrease in average ratio from 2010 to 2011.
▶▶ 2011 Hospital IT Budget and Expenses con tinued
In our opinion, this correlates with the general patterns we have
seen with respect to the acquisition and implementation of
electronic medical records (EMRs)—where hospitals in the higher
bed ranges, particularly academic medical centers, implemented
EMRs in larger numbers earlier than those in the middle and lower
bed-size categories. However, these earlier deployments in larger
institutions, notably academic medical centers (AMCs), were often
more “best of breed-like” in their deployments and many with now
Table HB 4
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
2009
2010
2011
Avg % Total
Avg % Total
Avg % Total
IT Operating
IT Operating
IT Operating
Expense/
Expense/
Expense/
Total Hospital
Total Hospital
Total Hospital
Operating
Operating
Operating
Expense
N
Expense
N
Expense
1.92% 136
1.82% 183
1.97%
2.72% 76
2.09% 77
2.17%
3.40% 63
2.97% 78
2.52%
2.82% 39
3.08% 55
2.81%
3.12% 44
3.43%
41
3.35%
2.88%
8
2.53% 13
3.16%
4.17%
17
2.54% 24
2.73%
2.67% 383
2.40% 471
2.39%
N
171
91
74
60
37
17
25
475
Table HB5
Type
Academic/Teaching
Non-Academic
General Med/Surg
Others
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
2009
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
3.78%
2.55%
2.69%
2.62%
1.91%
2.84%
2.08%
2.77%
3.45%
2.21%
N
39
344
259
124
68
315
54
329
143
240
2010
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
3.20%
2.33%
2.45%
2.31%
1.76%
2.57%
1.69%
2.56%
2.55%
2.32%
N
68
22
53
17
31
45
61
46
40
2010
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.60%
2.82%
2.35%
2.41%
3.20%
2.80%
2.26%
2.41%
1.46%
N
39
432
304
167
102
369
88
383
160
311
2011
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
N
2.89% 37
2.35% 438
2.35% 321
2.48% 154
1.79% 84
2.52% 391
1.79% 66
2.49% 409
2.52% 187
2.31% 288
Table HB6
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2009
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
3.23%
2.46%
3.03%
3.04%
2.70%
2.77%
2.60%
2.26%
1.66%
N
77
14
49
25
46
53
77
58
72
2011
Avg % Total
IT Operating
Expense/
Total Hospital
Operating
Expense
2.34%
3.28%
2.44%
2.34%
2.43%
2.46%
2.36%
2.62%
1.86%
N
72
15
57
18
49
67
82
59
56
State Key for Regions:
New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA, ME, VT, RI, CT, NH
Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NY, NJ, PA
South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD, DE, DC, WV, VA, NC, SC, GA, FL
East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI
East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL
West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE
West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK
Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM
Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI
aging architectures. With the growth of the integrated clinical
systems offerings and the need for ARRA compliance and
reporting, some of these larger institutions have begun replacing
legacy pieces which may be driving this growth. As these larger
institutions progress further into the operational phase of their
EMR deployments, the increase in expenses typically associated
with the implementation phase declines as does the depreciation
expense associated with these capital-intensive projects, which
generally have front-loaded depreciation schedules. During this
same period, the most significant increases in the sales of enterprise
EMR systems were among medium-sized hospitals, i.e., those in
the 301–500 bed range. Here, we found modest increases in the
expense ratios.
Consistent with the findings from the bed segments, an evaluation
of the IT OPEX by hospital type showed that critical access
hospitals, non-general medical/surgical, or those in rural areas
were the only segments to demonstrate growth from 2010 to 2011
(see Table HB5). This is somewhat consistent with the findings
from the bed-size segment since most of the smaller bed-sized
hospitals fall under the category of hospitals that are critical access,
or not general medical/surgical or located in rural areas. All other
hospital types reported a decline in the average ratio percentage.
Examining the IT OPEX ratio on a U.S. regional basis shows that
five of the nine regions indicated increases, with East South Central
and West South Central demonstrating the largest year-over-year
growth (0.46 percent and 0.40 percent, respectively) from 2010 to
2011 (see Table HB6).
Government and private entities in Vermont, Maine and Rhode
Island also actively contributed to large-scale coordinated HIE and
EMR initiatives in 2009 that began to take shape in 2010. However,
the increase seen for the average percentage between 2009 and 2010
in the New England region was more pronounced than the median
increase (see Table HB9), suggesting that the rising tide did not lift
all boats, but rather was characteristic of spending by the larger,
more IT-mature institutions. Also, our EMRAM median scores
show that the top six states in the U.S. are all the six New England
states (MA, ME, VT, RI, CT, NH).
An evaluation of the median total IT operating expense to total
hospital operating expense ratios for hospital bed-size segments
shows virtually all of the segments have increased from 2010 to
2011 except the 401–500 bed segment (see Table HB7). The largest
growth occurred for the 501–600 bed segment at 0.75 percent. The
401–500 bed segmentation showed a slight decrease (0.10 percent).
Table HB7
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
2009
2010
2011
Median % Total
Median % Total
Median % Total
IT Operating
IT Operating
IT Operating
Expense/Total
Expense/Total
Expense/Total
Hospital
Hospital
Hospital
Oper­ating
Oper­ating
Oper­ating
Expense
N
Expense
N
Expense
N
1.47% 136
1.56% 183
1.70% 171
2.17% 76
1.73% 77
1.98% 91
2.36% 63
2.13% 78
2.20% 74
2.37% 39
2.74% 55
2.75% 60
2.73% 44
3.23% 41
3.13% 37
2.32%
8
2.43% 13
3.17% 17
3.37% 17
2.32% 24
2.53% 25
2.08% 383
1.93% 471
2.11% 475
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
7
▶▶ 2011 Hospital IT Budget and Expenses con tinued
Table HB8
Table HB12
2009
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Type
Expense
Academic
2.96%
Non-Academic
1.94%
General Med/Surg
2.11%
Others
1.92%
Critical Access
1.44%
Non-Critical Access
2.24%
Rural
1.38%
Urban
2.19%
Multi-Hospital System
2.53%
Single Hospital System
1.93%
N
39
344
259
124
68
315
54
329
143
240
2010
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Expense
2.78%
1.86%
2.00%
1.86%
1.53%
2.12%
1.34%
2.12%
1.92%
1.93%
N
68
22
53
17
31
45
61
46
40
2010
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Expense
1.75%
2.28%
1.97%
1.93%
2.58%
2.24%
2.12%
2.04%
1.00%
N
39
432
304
167
102
369
88
383
160
311
2011
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Expense
2.80%
2.01%
2.13%
1.99%
1.52%
2.21%
1.53%
2.21%
2.16%
2.07%
N
37
438
321
154
84
391
66
409
187
288
N
77
14
49
25
46
53
77
58
72
2011
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Expense
2.14%
1.83%
2.29%
2.05%
2.38%
2.25%
1.89%
1.88%
1.25%
N
72
15
57
18
49
67
82
59
56
Table HB9
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2009
Median % Total
IT Operating
Expense/Total
Hospital
Oper­ating
Expense
2.07%
1.66%
2.14%
2.53%
2.44%
2.37%
2.02%
2.01%
1.33%
Table HB10
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
2009
2010
2011
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Expense
N
Expense
N
Expense
N
4.08% 122
2.04% 179
4.44% 149
4.05% 79
2.39% 72
4.92% 78
4.77% 65
3.59% 79
4.85% 78
5.14% 38
3.22% 57
5.22% 52
4.55% 44
3.80%
41
6.00% 38
4.20% 12
3.20% 13
5.47%
16
5.89% 21
3.47% 28
4.52% 25
4.45% 381
2.77% 469
4.87% 436
Table HB11
2009
2010
2011
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Type
Expense
N
Expense
N
Expense
N
Academic
5.43% 45
3.34% 46
4.80% 40
Non-Academic
4.32% 336
2.71% 423
4.88% 396
General Med/Surg
4.34% 257
2.84% 300
4.85% 290
Others
4.68% 124
2.64% 169
4.92% 146
Critical Access
4.24% 66
3.06% 148
4.57% 79
Non-Critical Access
4.50% 315
2.63% 321
4.94% 357
Rural
4.71% 51
2.16% 99
4.69% 68
Urban
4.41% 330
2.93% 370
4.91% 368
Multi-Hospital System
5.46% 140
2.02% 86
5.71% 148
Single Hospital System
3.87% 241
2.94% 383
4.44% 288
8 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2009
Median %
Total IT Budget
as % of Total
Hospital
Expense
5.50%
2.87%
4.26%
4.11%
3.52%
5.72%
4.40%
4.25%
3.38%
N
77
21
60
19
36
35
64
43
26
2010
Median %
Total IT Budget
as % of Total
Hospital
Expense
2.70%
3.02%
2.72%
2.76%
3.25%
3.22%
2.95%
2.71%
1.73%
N
87
20
60
21
50
43
77
63
48
2011
Median %
Total IT Budget
as % of Total
Hospital
Expense
4.96%
4.28%
4.64%
7.66%
3.73%
4.92%
6.02%
4.94%
3.69%
N
75
19
59
20
53
39
63
62
46
Upon evaluating the median operating expense ratio by hospital
type, only one segment, critical access hospitals, showed a very
slight decrease (0.01 percent), while all other hospital-type segments
indicated an increase from 0.02 percent to 0.24 percent (hospitals
part of the multi-hospital system) (see Table HB8).
U.S. regions demonstrating growth from 2010 to 2011 were the East
North Central, Middle Atlantic, Mountain, Pacific and West South
Central regions. The growth in each region was relatively modest,
ranging from 0.01 percent to 0.39 percent (see Table HB9). Growth
was largest in the East North Central (0.39 percent). All other
segments indicated a decline from 2010 to 2011 with East South
Central indicating the greatest year-over-year decline (0.45 percent).
IT Spending as a Percentage of Hospital Total Spending Including CAPEX
An evaluation of the average of total IT budget as a percent of the
total hospital operating expense (the average budget ratio) in the
various hospital segments is shown in Tables HB10–HB12. Overall,
the market saw a dramatic decrease from 2009 to 2010 for this ratio.
Based on the 2011 data, it is more likely that the 2010 data was a
data anomaly and that the 2011 and 2009 data are more comparable
than 2011 and 2010 data. In subsequent analysis of this section, we
will compare the average percentage of 2009 with the average
percentage in 2011.
Among the bed segmentation, the average ratio of virtually all of
the bed size segmentation indicated an increase from 2009 to 2011,
ranging from 0.07 percent to 1.45 percent (401–500 beds). The 600+
bed segment is the only exception, declining by 1.37 percent within
the same time frame (see Table HB10). Most of the hospital types
have also indicated an increase in IT spending to total hospital
spending ratio with the exception of academic and rural hospitals
(see Table HB11). As for the region, East North Central and Pacific
are the only areas to indicate a decline in spending ration from 2009
to 2011. All other regions indicated an increase in the spending ratio
with the largest year-over-year spending ratio occurring in the
Mountain region with a 3.55 percent increase (see Table HB12).
An evaluation of the median of total IT budget as a percent of
the total hospital operating expense (median budget ratio) in the
various hospital segments is shown in Tables HB13–HB15. Four
of the seven bed segment categories indicated an increase from
2009 to 2011 with the 401–500 bed segment demonstrating the
largest increase at 1.24 percent. The bed segment with the largest
decline in the same time period is the 600+ bed segment (0.68
percent) (see Table HB13). Almost all of the hospital-type market
segments indicated an increase from 2009 to 2011, ranging from
0.30 percent to 0.98 percent. Academic medical centers are the
▶▶ 2011 Hospital IT Budget and Expenses con tinued
Table HB13
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
Table HB16
2009
2010
2011
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Expense
N
Expense
N
Expense
N
2.76% 122
1.77% 179
3.30% 149
3.61% 79
2.15% 72
4.08% 78
4.12% 65
2.77% 79
3.98% 78
4.06% 38
2.98% 57
4.29% 52
3.88% 44
4.12%
41
5.11% 38
4.30% 12
3.41% 13
4.19%
16
4.82% 21
2.93% 28
4.14% 25
3.46% 381
2.26% 469
3.92% 436
Table HB14
2009
2010
2011
Median %
Median %
Median %
Total IT Budget
Total IT Budget
Total IT Budget
as % of Total
as % of Total
as % of Total
Hospital
Hospital
Hospital
Type
Expense
N
Expense
N
Expense
N
Academic
4.48% 45
3.06% 46
4.09% 40
Non-Academic
3.39% 336
2.16% 423
3.90% 396
General Med/Surg
3.57% 257
2.28% 300
3.87% 290
Others
3.19% 124
2.26% 169
4.09% 146
Critical Access
2.66% 66
1.89% 99
3.64% 79
Non-Critical Access
3.73% 315
2.53% 370
3.96% 357
Rural
2.66% 51
1.71% 86
3.47% 68
Urban
3.64% 330
2.54% 383
4.03% 368
Multi-Hospital System
3.93% 140
2.52% 148
4.58% 148
Single Hospital System
3.23% 241
2.20% 321
3.74% 288
Table HB15
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2009
Median %
Total IT Budget
as % of Total
Hospital
Expense
3.57%
2.50%
3.69%
3.61%
3.23%
4.98%
3.36%
3.46%
2.62%
N
77
21
60
19
36
35
64
43
26
2010
Median %
Total IT Budget
as % of Total
Hospital
Expense
2.23%
2.11%
2.61%
2.49%
2.73%
3.02%
2.32%
2.18%
1.19%
N
87
20
60
21
50
43
77
63
48
2011
Median %
Total IT Budget
as % of Total
Hospital
Expense
4.04%
3.03%
4.32%
4.72%
3.48%
4.24%
3.74%
4.25%
2.74%
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
2009
2010
Avg % Total
Avg % Total
IT Capital
IT Capital
Expense Last
Expense Last
Year/Total
Year/Total
Hospital
Hospital
Capital Expense
N Capital Expense
17.82% 79
17.26%
20.87% 61
18.78%
17.83% 52
16.19%
24.32% 33
15.85%
25.65% 35
19.51%
14.14%
7
25.26%
17.74%
17
13.87%
20.10% 284
17.32%
N
74
33
36
26
22
5
15
211
2011
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
N
17.77% 99
18.01% 54
16.50%
51
17.52%
41
24.73% 27
13.16%
11
15.40%
17
17.89% 300
Table HB17
2009
2010
2011
Avg % Total
Avg % Total
Avg % Total
IT Capital
IT Capital
IT Capital
Expense Last
Expense Last
Expense Last
Year/Total
Year/Total
Year/Total
Hospital
Hospital
Hospital
Type
Capital Expense
N Capital Expense
N Capital Expense
N
Academic
19.23% 36
16.27% 19
14.05% 28
Non-Academic
20.23% 248
17.43% 192
18.28% 272
General Med/Surg
20.82% 201
17.88% 141
18.28% 203
Others
18.37% 83
16.20% 70
17.07% 97
Critical Access
19.42% 39
15.74% 38
18.88% 46
Non-Critical Access
20.21% 245
17.67% 173
17.71% 254
Rural
18.81% 32
17.69% 35
17.60% 38
Urban
20.27% 252
17.25% 176
17.93% 262
Multi-Hospital System
21.61% 87
12.35% 79
16.05% 99
Single Hospital System
19.44% 197
20.30% 132
18.79% 201
Table HB18
N
75
19
59
20
53
39
63
62
46
only hospital type that showed a decrease at negative 0.39 percent
(see Table HB14). As for the U.S. regions, the Pacific region is the
only area that demonstrated decrease of 0.74 percent from 2009
to 2011. All other regions indicated an increase with their median
ratio, with the Mountain demonstrating the largest increase at
1.11 percent (see Table HB15).
IT Capital Expenses as a Percentage of Hospital Total Capital Expenses
An evaluation of average total IT capital expenses (last fiscal year)
to total hospital capital expenses (capital ratios) is shown in Tables
HB16–HB18. Overall, the general ratio increased modestly from
2010 to 2011 after a decline was reported from 2009 to 2010;
perhaps the economic recovery is a driver behind the increase in
capital spending. By bed segments, only the 101–200 and 501–600
bed segments indicated a decrease in the average ratio. The 501–600
bed segment decreased by more than 12 percent, but this decrease is
not statistically significant due to the small population size in 2010
and 2011. All other bed segments showed an increase of the average
ratio, ranging from 0.31 percent to 1.53 percent (see Table HB16).
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
2009
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
18.60%
11.04%
20.08%
17.88%
20.80%
25.17%
21.31%
24.43%
16.25%
N
56
19
38
15
28
26
47
36
19
2010
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
19.08%
8.72%
17.53%
22.12%
19.44%
19.75%
13.46%
18.68%
16.31%
N
28
7
23
10
15
15
29
37
47
2011
Avg % Total
IT Capital
Expense Last
Year/Total
Hospital
Capital Expense
19.38%
25.67%
14.77%
20.97%
19.29%
16.33%
18.92%
17.21%
15.79%
N
52
10
41
10
38
22
41
43
43
An evaluation by hospital types shows that academic medical
centers, rural hospitals and single hospital systems indicated a
decline in capital expenses when compared to the total hospital
capital expense. Academic medical centers decreased by 1.51
percent from 2010. All other hospital types showed increased IT
capital expense to total hospital capital expense ratio, with critical
access hospitals having the highest year-over-year growth at 3.14
percent (see Table HB17). From 2010 to 2011, East South Central,
South Atlantic, and East North Central were the regions where
growth occurred. The ratio for East South Central increased to
16.95 percent in the same time period (see Table HB18).
An evaluation of median total IT capital expenses to total hospital
capital expenses (capital ratios) is shown in Tables HB19–HB21.
Overall, the median ratio increased by more than two percent from
2010 to 2011. An analysis of hospital bed segments indicates that
the larger bed segments (501–600 segment and 600+ bed segment)
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
9
▶▶ 2011 Hospital IT Budget and Expenses con tinued
were the only segments in which there was an decrease for
median results (4.48 percent and 0.96 percent, respectively).
401–500 segments demonstrated the largest increase at 8.01 percent.
The hospital-type analysis shows a decline in budgets over previous
year expenses for rural hospitals and hospitals part of the multisystems. The regional analysis shows that East South Central
regions that had the largest year-over-year increase at 11.87 percent.
East North Central, West North Central and Middle Atlantic are
the only areas that indicated slight to moderate declines.
Market Drivers/Future Outlook
Despite the declines we saw between 2009 and 2010, we expect the
general trend in both average and median ratios to increase as the
country continues on its current path towards economic recovery
and as federal healthcare policies and subsidies combine to drive
IT spending higher. With the growth of the employment numbers,
there is evidence that patient volumes are returning to pre-recession
levels. Also, as cited above, there is some sense that capital
spending in general (for plant and equipment) is seeing an increase
in anticipation of tougher cash flow times ahead with planned
Medicare reimbursements coincident with the increase in U.S.
citizens with coverage as called for by the Affordable Care Act.
Hospitals are facing a series of major IT initiatives with significant
budgetary and cash flow implications. At the top of this list is
the need to continue to acquire, install, expand and optimize
EMR applications to meet the Stage 1 and Stage 2 meaningful
use criteria. In 2011, hospitals must also begin to ramp up for
the implementation of ICD-10-PCS encoding upgrades in 2013,
upgrades that will impact a broad range of financial, health
information management, and clinical systems. By 2014, hospitals
will need to have enhanced their EMRs to meet Stage 2 meaningful
use criteria and, by 2015, Stage 3 or they will begin to face financial
penalties for non-compliance.
For clinicians, the need for ubiquitous access to EMR data of
varying data types from inpatient and ambulatory sources, including
digital images, will necessitate improved wired and wireless network
capacity, higher investments in mobile point-of-care devices,
improved security and more robust remote Web access. These
upgrades to hospital application portfolios will drive spending on
IT infrastructure higher, as well. As more mission-critical patient
clinical data is transformed into digital form, system performance
and reliability will become even more important, and costly, for
those hospitals which host their own data centers. Hospitals will
need to spend more on data center upgrades, security, disaster
recovery and backup site services. While virtualization of both
servers and workstations will help mitigate some of the associated
cost increases, much of these anticipated cost increases will be
inescapable. Even hospitals which remotely host their applications
will see corresponding cost increases as the service partners will
also be forced to provide the necessary additional capacity and
services. One additional growth area where we are seeing anecdotal
evidence is that hospitals are investing heavily in mass storage, as
more imaging data is digitized and departmental PACS systems are
centralized. We also anticipate an increasing growth of mass storage
requirements to the point that many hospitals will begin seeking a
secondary or completely outsourced data center. It is also likely that
10 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Table HB19
Bed Seg
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ beds
All
2009
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
N
11.31% 79
15.59% 61
12.26% 52
24.09% 33
19.96% 35
9.31%
7
14.40%
17
14.27% 284
2010
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
10.13%
9.42%
9.16%
10.24%
10.32%
17.45%
12.92%
10.27%
N
74
33
36
26
22
5
15
211
2011
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
N
12.20% 99
11.04% 54
14.41%
51
11.18%
41
18.33% 27
12.98%
11
11.96%
17
12.14% 300
2009
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
N
13.83% 36
14.76% 248
15.73% 201
12.60% 83
11.31% 39
14.87% 245
12.98% 32
14.27% 252
15.46% 87
13.59% 197
2010
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
N
10.26% 19
10.34% 192
11.34% 141
9.97% 70
8.93% 38
11.34% 173
11.10% 35
10.26% 176
7.13% 79
13.45% 132
2011
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
N
12.39% 28
12.14% 272
11.96% 203
12.32%
97
11.43% 46
12.21% 254
8.99% 38
12.50% 262
10.38% 99
12.96% 201
2009
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
13.40%
9.31%
13.37%
7.68%
14.66%
17.85%
18.24%
19.20%
14.02%
2010
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
14.30%
8.06%
13.24%
14.92%
8.75%
11.10%
9.13%
14.68%
6.64%
2011
Median %
IT Capital
Expense/
Total Hospital
Capital
Expense
11.89%
19.92%
11.84%
18.76%
11.84%
12.56%
11.50%
14.18%
9.86%
Table HB20
Type
Academic
Non-Academic
General Med/Surg
Others
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
Table HB21
Region
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
N
56
19
38
15
28
26
47
36
19
N
28
7
23
10
15
15
29
37
47
N
52
10
41
10
38
22
41
43
43
the virtualization phenomenon that we are seeing with servers and
workstations will rapidly spread to storage, as well.
However, some of the costs associated with these trends may not
necessarily be fully reflected in our metrics. Based on our
experience with past initiatives, many of these anticipated expenses
will be in the form of increased consulting costs and additional
non-IT labor costs, including nursing and other clinical personnel,
and specialty personnel in billing, finance and health information
management. Although attributable to IT projects, these costs are
often not charged back to IT cost centers. Also, increased mass
storage costs directly attributable to medical and pathology imaging
may be charged to those departments. Our evidence shows that this
is more likely in the larger hospital market.
▶▶ Financial Management
With a 95 percent or better adoption rate, three applications in
this market—accounts payable, general ledger and materials
management—represent saturated markets and each application
saw growth of less than one percent (see Table FM1). The financial
management category also includes the enterprise resource planning
(ERP) application. ERP is not as mature as the other three legacybased applications and adoption of this technology is much less
widespread. However, market penetration of ERP applications has
demonstrated year-over-year growth since 2009, growing almost
five percent since 2009. ERP applications typically replace legacy,
standalone accounts payable, general ledger and materials
management and possibly human resource, solutions. As hospital
costs increase and revenues per case decrease, hospitals may begin
to increase their acquisitions of ERP systems to generate more
operational efficiencies with financial and human resources in
their organizations.
Table F M1 | Financial Management
N=4,289
2009
2010
Accounts Payable
99.86%
99.86%
Enterprise Resource Planning
19.56%
22.69%
General Ledger
99.86%
99.86%
Materials Management
97.09%
96.99%
Percentages include installed, contracted or installation in process
2011
99.93%
24.11%
99.91%
97.44%
As expected, planned purchases for the financial management
category are predominantly replacement purchases. All planned
purchases of accounts payable and general ledger will be
replacement purchases (see Table FM2). Most of the materials
management market and ERP purchases (91 percent for each
application) will also replace their current solutions.
An evaluation of the financial management application market
segment by hospital type in 2011 demonstrates the following:
• Accounts payable: this market is almost completely saturated across all
hospital types, allowing little opportunity for growth (see Table FM3).
• ERP: in 2011, academic medical centers had the highest level of
adoption among all hospital types at 46 percent and also
demonstrated the most growth from 2010 to 2011 with an
increase of almost three percent (see Table FM4). Growth in use
among other types of hospitals was less than two percent.
• General ledger: this legacy application shows virtual market
saturation (99 percent penetration or better) across all types of
provider organizations (see Table FM5). This leaves very little
room for additional market activity.
• Materials management: this application has achieved full saturation
for academic medical centers and most other segments are approaching
market saturation. Rural hospitals demonstrated the largest growth
at more than one percent from 2010 to 2011 (see Table FM6).
Table F M2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Accounts Payable
75
100.00%
Enterprise Resource Planning
20
90.91%
General Ledger
76
100.00%
Materials Management
72
91.14%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
0
2
0
7
% of Hospitals Planning
to Purchase Software
for the First Time
0.00%
9.09%
0.00%
8.86%
N = Total Number of
Hospitals Planning
75
22
76
79
Table F M3 | Accounts Payable
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
4,091
2,504
1,779
1,152
3,131
1,004
3,279
2,583
1,700
4,283
Percent
100.00%
99.85%
99.88%
99.83%
99.74%
99.90%
99.70%
99.91%
99.88%
99.82%
99.86%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,091
2,505
1,778
1,151
3,132
1,004
3,279
2,582
1,701
4,283
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
84
889
633
340
113
860
80
893
800
173
973
Percent
100.00%
99.85%
99.92%
99.78%
99.65%
99.94%
99.70%
99.91%
99.85%
99.88%
99.86%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
4,095
2,507
1,779
1,153
3,133
1,007
3,279
2,584
1,702
4,286
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
89
945
672
362
119
915
84
950
848
186
1,034
Percent
99.48%
99.95%
100.00%
99.83%
99.83%
99.97%
100.00%
99.91%
99.92%
99.94%
99.93%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table F M4 | Enterprise Resource Planning
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
75
764
552
287
76
763
54
785
684
155
839
Percent
39.06%
18.65%
22.02%
16.11%
6.58%
24.35%
5.36%
23.92%
26.45%
9.10%
19.56%
2010
Percent
43.75%
21.70%
25.25%
19.08%
9.78%
27.44%
7.94%
27.21%
30.94%
10.16%
22.69%
2011
Source: HIMSS Analytics® Database 2011
Percent
46.35%
23.07%
26.80%
20.31%
10.30%
29.20%
8.34%
28.95%
32.79%
10.92%
24.11%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
11
▶▶ Financial Management con tinued
Table F M5 | General Ledger
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
4,091
2,505
1,778
1,151
3,132
1,004
3,279
2,584
1,699
4,283
Percent
100.00%
99.85%
99.92%
99.78%
99.65%
99.94%
99.70%
99.91%
99.92%
99.77%
99.86%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,091
2,506
1,777
1,150
3,133
1,004
3,279
2,583
1,700
4,283
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,968
2,481
1,679
1,058
3,102
917
3,243
2,554
1,606
4,160
Percent
100.00%
99.85%
99.96%
99.72%
99.57%
99.97%
99.70%
99.91%
99.88%
99.82%
99.86%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
4,094
2,507
1,778
1,152
3,133
1,006
3,279
2,584
1,701
4,285
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,987
2,490
1,689
1,068
3,111
932
3,247
2,560
1,619
4,179
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
99.48%
99.93%
100.00%
99.78%
99.74%
99.97%
99.90%
99.91%
99.92%
99.88%
99.91%
Table F M6 | Materials Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
3,972
2,486
1,678
1,060
3,104
918
3,246
2,561
1,603
4,164
Percent
100.00%
96.95%
99.16%
94.16%
91.77%
99.04%
91.16%
98.90%
99.03%
94.13%
97.09%
2010
When evaluating the market by bed-size segments, we find the
following notable changes from 2010 to 2011:
• 0–100 beds: all of the financial management applications
demonstrated slight year-over-year growth with ERP showing
the largest growth of over one percent (see Table FM7).
• 101–200 beds: ERP demonstrated growth of just over one
percent while general ledger and accounts payable maintained
100 percent full market saturation from 2010 (see Table FM8).
• 201–300 beds: ERP is the only application that demonstrated
year-over-year growth (slightly more than one percent). Market
penetration of the other financial management applications
remained unchanged from 2010, having previously reached
100 percent saturation (see Table FM9).
• 301–400 beds: ERP had the highest growth in this segment
year-over-year at slightly under three percent; there was no
growth for accounts payable and general ledger as these are
fully saturated markets (see Table FM10).
• 401–500 beds: ERP is the only financial management application
that demonstrated year-over-year growth in this bed segment at
less than one percent. All other financial management
applications are at full market saturation and thus are unchanged
from last year (see Table FM11).
• 501–600 beds: ERP is the only financial management application
that demonstrated a growth from 2010 to 2011 at slightly under
two percent; accounts payable and general ledger have decreased
by less than one percent in the same time frame (see Table FM12).
• Over 600 beds: ERP is the only application to indicate a growth
at four percent; all other financial management applications are
completely saturated (see Table FM13).
12 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
100.00%
96.85%
98.96%
94.22%
91.60%
98.98%
91.06%
98.81%
98.76%
94.30%
96.99%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
100.00%
97.32%
99.32%
94.78%
92.47%
99.27%
92.55%
98.93%
98.99%
95.07%
97.44%
Table F M7
0–100 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
2176
253
2176
2061
99.77%
11.60%
99.77%
94.50%
2010
% of 2,181 Hospitals
2175 99.72%
312 14.31%
2175 99.72%
2059 94.41%
2011
2179
338
2178
2074
99.91%
15.50%
99.86%
95.09%
Table F M8
101–200 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
821
172
821
818
99.88%
20.92%
99.88%
99.51%
2010
% of 822 Hospitals
822 100.00%
189 22.99%
822 100.00%
817 99.39%
2011
822 100.00%
199 24.21%
822 100.00%
819 99.64%
Table F M9
201–300 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
504 100.00%
138 27.38%
504 100.00%
504 100.00%
2010
% of 504 Hospitals
504 100.00%
155 30.75%
504 100.00%
504 100.00%
2011
504 100.00%
162 32.14%
504 100.00%
504 100.00%
Table F M10
301–400 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
328 100.00%
103 31.40%
328 100.00%
328 100.00%
2010
% of 328 Hospitals
328 100.00%
121 36.89%
328 100.00%
326 99.39%
2011
328 100.00%
130 39.63%
328 100.00%
328 100.00%
▶▶ Financial Management con tinued
Table F M11
401–500 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
182 100.00%
64 35.16%
182 100.00%
182 100.00%
2010
% of 182 Hospitals
182 100.00%
72 39.56%
182 100.00%
182 100.00%
2011
182 100.00%
73 40.11%
182 100.00%
182 100.00%
Table F M12
501–600 Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
122 100.00%
51 41.80%
122 100.00%
121 99.18%
2010
% of 122 Hospitals
122 100.00%
55 45.08%
122 100.00%
122 100.00%
2011
121 99.18%
57 46.72%
121 99.18%
122 100.00%
Table F M13
600+ Beds
Accounts Payable
Enterprise Resource Planning
General Ledger
Materials Management
2009
150 100.00%
58 38.67%
150 100.00%
150 100.00%
2010
% of 150 Hospitals
150 100.00%
69 46.00%
150 100.00%
150 100.00%
2011
150 100.00%
75 50.00%
150 100.00%
150 100.00%
Table F M14
2011
Accounts Payable
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Enterprise Resource Planning
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
General Ledger
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
138
288
1,002
891
755
3,074
3,074
3,074
3,074
3,074
3,074
3,074
4.49%
9.37%
32.60%
28.99%
24.56%
100.00%
0
20
214
213
104
551
551
551
551
551
551
551
0.00%
3.64%
38.91%
38.73%
18.91%
100.00%
118
280
997
941
737
3,073
3,073
3,073
3,073
3,073
3,073
3,073
3.84%
9.11%
32.44%
30.62%
23.98%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
76
223
758
955
753
2,765
2,765
2,765
2,765
2,765
2,765
2,765
2.75%
8.07%
27.41%
34.54%
27.23%
100.00%
Table F M15
2011
Materials Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
A temporal review of contract signing for financial management
applications in 2011 depicts a market with the majority of contract
activities (more than 60 percent) taking place in the 1995–1999 and
2000–2004 timeframes for all financial management applications
(see Tables FM14–FM15). Almost a quarter of the financial
management applications contracts have been signed between
2005–2011.
We believe that applications purchased prior to 1999 may be
nearing the end of their useful lives particularly because of their
inability to support the dynamic operational process changes that
we expect will take place through 2015. But with the focus on
EMR systems, version 5010 electronic data interchange update
and ICD-10-PCS coding conversion projects, we believe that
organizations will try to extend the useful life of these environments
for at least two to three more years.
Market Drivers/Future Outlook
The financial management IT application market has been and
will continue to be impacted through 2013 by:
• A focus on electronic medical records, version 5010 electronic
data interchange update and ICD-10-PCS coding conversion
projects will leave relatively little capital funding or resources
available for the upgrade or replacement of financial management
applications.
• Access to capital for replacing older legacy applications, and
budget battles that assign financial management system
replacements a lower priority than high profile, governmentmandated clinical and revenue cycle-related applications.
• Replacement of legacy general ledger, accounts payable, and
materials management application systems by ERP systems,
particularly in hospitals over 400 beds.
• Beyond 2013, we see potential resurgence in purchasing activity
in this area, driven by:
• The need to improve supply chain management processes and
lower supply costs.
• The need to incorporate newer, more automated supply chain
workflows.
• The need for more accurate and flexible accounting resulting
from mergers, acquisitions, and divestitures among hospital
systems.
• Improved integration with financial decision support and
business analytics software.
• Satisfying the accounting and financial analysis and
reporting requirements associated with ACOs, patient-centered
medical home and other bundled payment programs related to
healthcare reform.
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
13
▶▶ Financial Decision Support Environment
The financial decision support environment includes the budgeting,
business intelligence, cost accounting, data warehousing − financial,
executive information system, financial modeling and medical
necessity checking content applications. These applications help
healthcare organizations evaluate their financial health by providing
tools such as real-time evaluation and tracking of key operational
metrics and the presentation of these metrics to executives in
specifically designed dashboards.
Among the financial decision support applications, budgeting had
the highest level of adoption with 82 percent in 2011 followed by cost
accounting at 70 percent. In the past year, market penetration
increased for all financial decision support applications with medical
necessity checking content demonstrating the greatest increase by
almost five percent, followed by data business intelligence at slightly
more than four percent (see Table FDS1). None of the applications in
this suite have reached market saturation.
Table F DS1 | Financial Decision Support
N=4,289
2009
2010
Budgeting
80.81%
82.05%
Business Intelligence
34.32%
38.68%
Cost Accounting
67.85%
69.36%
Data Warehousing/Mining – Financial
37.54%
42.88%
Executive Information Systems
60.55%
62.11%
Financial Modeling
31.31%
34.25%
Medical Necessity Checking Content
37.84%
52.60%
Percentage includes installed, contracted or installation in process
2011
82.82%
43.02%
70.04%
46.79%
64.09%
36.23%
57.54%
The majority of purchases in this suite—budgeting, cost accounting,
data warehousing/mining − financial, executive information systems
and medical necessity checking content—will replace existing
solutions. Conversely, nearly two thirds of purchases for business
intelligence and financial modeling will be made by organizations
that are purchasing the solution for the first time (see Table FDS2).
Table F DS 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Budgeting
39
95.12%
Business Intelligence
6
35.29%
Cost Accounting
47
85.45%
Data Warehousing/Mining – Financial
16
69.57%
Executive Information Systems
35
83.33%
Financial Modeling
4
33.33%
Medical Necessity Checking Content
10
62.50%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
2
11
8
7
7
8
6
% of Hospitals Planning
to Purchase Software
for the First Time
4.88%
64.71%
14.55%
30.43%
16.67%
66.67%
37.50%
N = Total Number of
Hospitals Planning
41
17
55
23
42
12
16
Table F DS 3 | Budgeting
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
181
3,285
2,225
1,241
771
2,695
680
2,786
2,240
1,226
3,466
Percent
94.27%
80.18%
88.75%
69.64%
66.75%
85.99%
67.53%
84.89%
86.62%
71.99%
80.81%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
182
3,337
2,246
1,273
801
2,718
704
2,815
2,264
1,255
3,519
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
113
1,546
1,072
587
215
1,444
165
1,494
1,271
388
1,659
Percent
94.79%
81.45%
89.59%
71.44%
69.35%
86.73%
69.91%
85.77%
87.55%
73.69%
82.05%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
180
3,372
2252
1,300
816
2,736
720
2,832
2,271
1,281
3,552
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
126
1,719
1,203
642
244
1,601
195
1,650
1,397
448
1,845
Percent
93.75%
82.30%
89.83%
72.95%
70.65%
87.30%
71.50%
86.29%
87.82%
75.22%
82.82%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table F DS 4 | Business Intelligence
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
91
1,381
952
520
184
1,288
139
1,333
1,138
334
1,472
Percent
47.40%
33.71%
37.97%
29.18%
15.93%
41.10%
13.80%
40.62%
44.01%
19.61%
34.32%
2010
14 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
58.85%
37.73%
42.76%
32.94%
18.61%
46.08%
16.39%
45.52%
49.15%
22.78%
38.68%
2011
Percent
65.63%
41.96%
47.99%
36.03%
21.13%
51.08%
19.36%
50.27%
54.02%
26.31%
43.02%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Financial Decision Support Environment con tinued
Evaluation of hospital-type market segments for the financial
decision support applications in 2011 showed the following when
comparing 2010 to 2011 data:
• Budgeting: the greatest growth for this application was among
rural hospitals, stand-alone hospitals and non-general medical/
surgical hospitals. Each of these segments demonstrated growth
of more than one percent. There was a slight decline in use
among academic medical centers (see Table FDS3).
• Business intelligence: academic medical centers had the highest
growth from 2010 to 2011 at close to seven percent, although the
adoption rate for this segment has slowed when compared to the
11 percent increase from 2009 to 2010. All other segment types
showed moderate growth ranging from approximately three to
five percent. Growth was slowest among rural and critical access
hospitals (see Table FDS4).
• Cost accounting: growth in this application was limited across
most market segments. The growth of slightly more than one
•
•
•
•
percent was noted for rural hospitals, critical access hospitals
and non-general medical/surgical hospitals (see Table FDS5).
Data warehousing/mining (financial): growth of more than five
percent occurred in general medical/surgical hospitals, academic
medical centers and non-critical access hospitals. Growth of
approximately one to four percent was recorded for all other
segments (see Table FDS6).
Executive information systems: growth across most hospital
segments was approximately two percent. The exception is the
academic medical center segment, which saw growth of less
than one percent (see Table FDS7).
Financial modeling: all segments demonstrated growth over the
past year of approximately two percent (see Table FDS8).
Medical necessity checking content: academic medical centers
demonstrated the greatest growth for this application at more than
11 percent. All other segments reported a growth that ranged
from four percent to six percent (see Table FDS9).
Table F DS 5 | Cost Accounting
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
174
2,736
1,950
960
582
2,328
503
2,407
1,905
1,005
2,910
Percent
90.63%
66.78%
77.78%
53.87%
50.39%
74.28%
49.95%
73.34%
73.67%
59.01%
67.85%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
176
2,799
1,990
985
605
2,370
522
2,453
1,951
1,024
2,975
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
118
1,721
1,187
652
273
1,566
207
1,632
1,392
447
1,839
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
142
2,522
1,686
978
514
2,150
438
2,226
1,761
903
2,664
Percent
91.67%
68.32%
79.38%
55.27%
52.38%
75.62%
51.84%
74.74%
75.44%
60.13%
69.36%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
177
2,827
1,999
1,005
618
2,386
537
2,467
1,969
1,035
3,004
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
128
1,879
1,326
681
281
1,726
228
1,779
1,499
508
2,007
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
143
2,606
1,741
1,008
535
2,214
460
2,289
1,809
940
2,749
Percent
92.19%
69.00%
79.74%
56.40%
53.51%
76.13%
53.33%
75.17%
76.14%
60.78%
70.04%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table F DS6 | Data Warehousing/Mining – Financial
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
99
1,511
1,044
566
221
1,389
168
1,442
1,225
385
1,610
Percent
51.56%
36.88%
41.64%
31.76%
19.13%
44.32%
16.68%
43.94%
47.37%
22.61%
37.54%
2010
Percent
61.46%
42.01%
47.35%
36.59%
23.64%
49.97%
20.56%
49.73%
53.83%
26.25%
42.88%
2011
Percent
66.67%
45.86%
52.89%
38.22%
24.33%
55.07%
22.64%
54.20%
57.97%
29.83%
46.79%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table F DS7 | Executive Information Systems
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
140
2,457
1,656
941
483
2,114
415
2,182
1,722
875
2,597
Percent
72.92%
59.97%
66.06%
52.81%
41.82%
67.45%
41.21%
66.48%
66.59%
51.38%
60.55%
2010
Percent
73.96%
61.56%
67.25%
54.88%
44.50%
68.60%
43.50%
67.82%
68.10%
53.02%
62.11%
2011
Source: HIMSS Analytics® Database 2011
Percent
74.48%
63.61%
69.45%
56.57%
46.32%
70.64%
45.68%
69.74%
69.95%
55.20%
64.09%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
15
▶▶ Financial Decision Support Environment con tinued
Table F DS 8 | Financial Modeling
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
91
1,252
881
462
203
1,140
164
1,179
962
381
1,343
Percent
47.40%
30.56%
35.14%
25.93%
17.58%
36.38%
16.29%
35.92%
37.20%
22.37%
31.31%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
101
1,368
953
516
235
1,234
191
1,278
1,057
412
1,469
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
100
2,156
1,503
753
466
1,790
381
1,875
1,518
738
2,256
Percent
52.60%
33.39%
38.01%
28.96%
20.35%
39.37%
18.97%
38.94%
40.87%
24.19%
34.25%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
105
1,449
998
556
253
1,301
214
1,340
1,107
447
1,554
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
122
2,346
1,634
834
522
1,946
430
2,038
1,635
833
2,468
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
54.69%
35.37%
39.81%
31.20%
21.90%
41.51%
21.25%
40.83%
42.81%
26.25%
36.23%
Table F DS9 | Medical Necessity Checking Content
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
69
1,554
1,077
546
329
1,294
280
1,343
1,118
505
1,623
Percent
35.94%
37.93%
42.96%
30.64%
28.48%
41.29%
27.81%
40.92%
43.23%
29.65%
37.84%
2010
An analysis of the financial decision support market by bed-size
segment in 2011 reflects budgeting is approaching saturation in all
segments over 200 beds (more than 90 percent), while cost
accounting is approaching saturation in all segments over 400 beds.
The following describe the application growth rates for each bed
segment from 2010 to 2011:
• 0–100 beds: medical necessity checking content had the highest
growth at more than four percent followed by business intelligence
at slightly more than three percent (see Table FDS10).
• 101–200 beds: in this bed segment, data warehousing/mining –
financial, business intelligence and medical necessity checking
all had growth of more than four percent (see Table FDS11).
• 201–300 beds: medical necessity checking content had the highest
growth at more than eight percent while data warehousing/
mining – financial had the second highest growth for this
segment at over seven percent, followed by business intelligence
at more than five percent. All other applications demonstrated
growth of less than two percent, except for cost accounting which
had no growth in the past year (see Table FDS12).
• 301–400 beds: business intelligence had the highest growth at
more than six percent, followed by medical necessity checking
content and data warehousing/mining – financial (over five
percent each). Cost accounting showed a slight decrease of less
than one percent (see Table FDS13).
• 401–500 beds: both medical necessity checking content and
business intelligence has growth of more than six percent in this
bed segment. Budgeting showed a slight decrease in use in the
past year (see Table FDS14).
16 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
52.08%
52.62%
59.95%
42.26%
40.35%
57.12%
37.84%
57.13%
58.70%
43.34%
52.60%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
63.54%
57.26%
65.18%
46.80%
45.19%
62.09%
42.70%
62.10%
63.23%
48.91%
57.54%
• 501–600 beds: business intelligence, financial modeling and data
warehousing/mining – financial all showed growth of more than
four percent in the past year. Budgeting and cost accounting both
had a slight decrease from 2010 (see Table FDS15).
• Over 600 beds: medical necessity checking content and business
intelligence each showed growth of at least eight percent in the
past year. Budgeting, cost accounting, and executive information
system indicated no change from 2010 (see Table FDS16).
Table F DS10
0–100 Beds
2009
Budgeting
1,538
Business Intelligence
554
Cost Accounting
1,174
Data Warehousing/Mining –
Financial
602
Executive Information Systems 1,144
Financial Modeling
479
Medical Necessity Checking
Content
706
2010
2011
% of 2,181 Hospitals
70.52% 1,585 72.67% 1,615 74.05%
25.40%
619 28.38%
688 31.55%
53.83% 1,215 55.71% 1,242 56.95%
27.60%
52.45%
21.96%
699
1,190
534
32.05%
54.56%
24.48%
753
1,231
577
34.53%
56.44%
26.46%
32.37%
977
44.80%
1,067
48.92%
Table F DS11
101–200 Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
2009
732
337
623
2010
% of 822 Hospitals
89.05%
736 89.54%
41.00%
376 45.74%
75.79%
627 76.28%
2011
738
416
628
89.78%
50.61%
76.40%
369
546
296
44.89%
66.42%
36.01%
402
555
312
48.91%
67.52%
37.96%
443
579
329
53.89%
70.44%
40.02%
366
44.53%
512
62.29%
547
66.55%
▶▶ Financial Decision Support Environment con tinued
Table F DS12
201–300 Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
Table F DS17
2009
459
213
421
2010
% of 504 Hospitals
91.07%
458 90.87%
42.26%
240 47.62%
83.53%
426 84.52%
2011
461
268
426
91.47%
53.17%
84.52%
219
353
199
43.45%
70.04%
39.48%
256
353
216
50.79%
70.04%
42.86%
295
360
225
58.53%
71.43%
44.64%
194
38.49%
285
56.55%
328
65.08%
Table F DS13
301–400 Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
2009
306
148
278
2010
% of 328 Hospitals
93.29%
307 93.60%
45.12%
172 52.44%
84.76%
289 88.11%
2011
307
193
288
93.60%
58.84%
87.80%
169
224
143
51.52%
68.29%
43.60%
195
231
162
59.45%
70.43%
49.39%
212
239
167
64.63%
72.87%
50.91%
148
45.12%
201
61.28%
218
66.46%
Table F DS14
401–500 Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
2009
170
88
163
2010
% of 182 Hospitals
93.41%
174 95.60%
48.35%
95 52.20%
89.56%
163 89.56%
2011
173
106
166
95.05%
58.24%
91.21%
103
128
86
56.59%
70.33%
47.25%
114
133
96
62.64%
73.08%
52.75%
118
136
100
64.84%
74.73%
54.95%
92
50.55%
115
63.19%
126
69.23%
Table F DS15
501–600 Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
2009
118
63
114
2010
% of 122 Hospitals
96.72%
118 96.72%
51.64%
72 59.02%
93.44%
116 95.08%
2011
117
77
115
95.90%
63.11%
94.26%
60
87
68
49.18%
71.31%
55.74%
67
85
71
54.92%
69.67%
58.20%
72
87
76
59.02%
71.31%
62.30%
55
45.08%
80
65.57%
83
68.03%
2011
Budgeting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Business Intelligence
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Cost Accounting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
73
218
455
800
648
2,194
2,194
2,194
2,194
2,194
2,194
2,194
3.33%
9.94%
20.74%
36.46%
29.54%
100.00%
4
33
141
254
300
732
719
719
719
719
719
732
0.56%
4.59%
19.61%
35.33%
41.72%
100.00%
86
260
472
515
525
1,858
1,857
1,857
1,857
1,857
1,857
1,858
4.63%
14.00%
25.42%
27.73%
28.27%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
7
58
100
320
352
837
821
821
821
821
821
837
0.85%
7.06%
12.18%
38.98%
42.87%
100.00%
50
150
423
438
538
1,599
1,593
1,593
1,593
1,593
1,593
1,599
3.14%
9.42%
26.55%
27.50%
33.77%
100.00%
6
107
107
254
194
668
667
667
667
667
667
668
0.90%
16.04%
16.04%
38.08%
29.09%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
3
6
113
82
316
520
520
520
520
520
520
520
0.58%
1.15%
21.73%
15.77%
60.77%
100.00%
Table F DS18
2011
Data Warehousing/Mining – Financial
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Executive Information Systems
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Financial Modeling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table F DS16
600+ Beds
Budgeting
Business Intelligence
Cost Accounting
Data Warehousing/Mining –
Financial
Executive Information Systems
Financial Modeling
Medical Necessity Checking
Content
2009
143
69
137
2010
% of 150 Hospitals
95.33%
141 94.00%
46.00%
85 56.67%
91.33%
139 92.67%
2011
141
97
139
94.00%
64.67%
92.67%
88
115
72
58.67%
76.67%
48.00%
106
117
78
70.67%
78.00%
52.00%
114
117
80
76.00%
78.00%
53.33%
62
41.33%
86
57.33%
99
66.00%
An evaluation of hospitals that signed contracts for financial
decision support applications demonstrates that at least half of the
applications were acquired after 2000 (see Tables FDS17–FDS19).
Contracting for medical necessity checking content contracts was
strongest between 2005 and 2011, when more than 60 percent of
contracts were signed. Applications acquired before 1995 are strong
candidates for replacement since newer versions of financial
Table F DS19
2011
Medical Necessity Checking Content
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
decision support applications offer better analytical functionality
and easier data exchanges with other applications. In particular,
stand alone budgeting and cost accounting is a good example of
replacement opportunities. We believe that hospitals will have an
acute need for new versions of these applications as shared savings
programs and bundled payments grow in adoption.
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
17
▶▶ Financial Decision Support Environment con tinued
Market Drivers/Future Outlook
The general outlook for the financial decision support IT application
market has been (and will continue to be) positive and represents
one of the fastest growing market segments. Growth will continue
to be driven through 2015 by:
• IDNs and AMCs moving aggressively to qualify as an ACO or
other paradigm to prosper under the Medicare shared savings
program.
• Continued focus on quality outcomes measures as driven both by
the ARRA regulations and the general trend towards transparency
and availability of quality and performance metrics to the public
at large.
• Higher rates of adoption of EMR applications and broader and
deeper enhancements of existing implementations will enhance
the value of decision support tools by providing even richer stores
of source information in digital form.
• A slowly growing economy, with tight capital markets and
declining Medicare and Medicaid reimbursements, will continue
to place hospitals under great pressure to reduce operating
expenses in ways that minimize adverse impacts on operating
effectiveness and clinical quality.
• Adoption of ICD-10-CM and ICD-10-PCS coding and the
upgrades of all applications impacted by this coding will
facilitate significantly enhanced cost and quality analyses.
• Increased awareness of and movement toward new models
of service delivery, such as patient-centered medical homes
and ACOs, or other models which may require increased
assumption of risk.
• Increased competitive environment from physicians for
outpatient services and the need to deliver planned operating
margins of joint ventures.
• Increasing pay-for-performance reimbursement models from
private insurers and the government.
• Hospital acquisition/divestiture and merger activities.
• The need to carefully evaluate contemplated new or enhanced
services to ensure viability, and profitability, or to determine
closure or divestiture strategies.
• More mature users of performance management and decision
support tools replacing their earliest efforts—principally data
marts—with more integrated, more functional, enterprise-wide
data warehouses.
• The positive outlook and increased growth in the purchase of
ERP applications, which are often bundled with higher-end
business intelligence tools and some prebuilt applications.
▶▶ Human Resource Environment
The Human Resources (HR) Department IT environment continued
to indicate slight growth over the past two years. Of the four
applications in this environment, payroll systems are at market
saturation (95 percent or better) with benefits administration,
personnel management, and time & attendance systems at or near
90 percent (see Table HR1). The slowing of the general growth in
HR application adoption could be related to the accelerating growth
in ERP purchases, as these applications are typically integral
components of ERP application suites.
HR IT applications support key staff management operations and
as such should be considered mission critical in today’s healthcare
environment where staffing shortages exist for many clinical and
IT professionals (e.g., nursing, pharmacy). IDNs can alleviate some
staff shortages by moving employees between facilities of the IDN.
A common HR system is imperative in such an environment.
In 2011, most of the planned purchases in the HR market were
replacement sales; this is to be expected in a market in which there
Table HR1 | Human Resources
N=4,289
2009
2010
Benefits Administration
88.13%
88.76%
Payroll
98.39%
98.81%
Personnel Management
87.67%
88.76%
Time & Attendance
91.35%
93.03%
Percentage include installed, contracted or installation in process
2011
89.67%
99.04%
89.93%
94.15%
18 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
is such a high rate of penetration across all applications. Time &
attendance was the application for which the most first-time
purchases were expected; approximately more than one-quarter of
all purchases for this application were expected to be first-time
purchases (see Table HR2).
Analyzing this market using segments for hospital types shows the
following year-over-year changes from 2010 to 2011:
• Benefits administration: rural hospitals demonstrated the highest
year-over-year growth (close to three percent), followed by single
hospital systems. Academic hospitals are the only segment to
show a decrease from 2010, but this decrease is less than one-half
percent (see Table HR3).
• Payroll: in general, there is slight growth across all hospital types
except the academic medical center segment which has achieved
100 percent market penetration. Rural hospitals showed the
largest increase (see Table HR4).
• Personnel management: rural hospitals demonstrated the highest
year-over-year growth (more than three percent) followed by
single hospitals and critical access hospitals at more than two
percent each (see Table HR5).
• Time & attendance: at approximately two and a half percent,
single hospital systems demonstrated the highest growth for this
application, followed by rural hospitals and critical access
hospitals at slightly over two percent each (see Table HR6).
▶▶ Human Resource Environment con tinued
Table HR 2 | 2010
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Benefits Administration
24
92.31%
Payroll
32
100.00%
Personnel Management
25
89.29%
Time & Attendance
8
72.73%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
2
0
3
3
% of Hospitals Planning
to Purchase Software
for the First Time
7.69%
0.00%
10.71%
27.27%
N = Total Number of
Hospitals Planning
26
32
28
11
Table HR3 | Benefits Administration
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
190
3,590
2,382
1,398
804
2,976
708
3,072
2,478
1,302
3,780
Percent
98.96%
87.63%
95.01%
78.45%
69.61%
94.96%
70.31%
93.60%
95.82%
76.45%
88.13%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
190
3,617
2,376
1,431
830
2,977
726
3,081
2,485
1,322
3,807
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,046
2,493
1,745
1,129
3,109
983
3,255
2,566
1,672
4,238
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,615
2,397
1,410
806
3,001
711
3,096
2,491
1,316
3,807
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,801
2,431
1,559
952
3,038
840
3,150
2,519
1,471
3,990
Percent
98.96%
88.28%
94.77%
80.30%
71.86%
94.99%
72.10%
93.88%
96.09%
77.63%
88.76%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,657
2,393
1,453
850
2,996
753
3,093
2,491
1,355
3,846
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,056
2,498
1,750
1,131
3,117
987
3,261
2,571
1,677
4,248
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,665
2,419
1,438
833
3,024
743
3,114
2,499
1,358
3,857
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,849
2,452
1,586
977
3,061
862
3,176
2,527
1,511
4,038
Percent
98.44%
89.26%
95.45%
81.54%
73.59%
95.60%
74.78%
94.24%
96.33%
79.57%
89.67%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HR4 | Payroll
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
4,028
2,489
1,731
1,124
3,096
978
3,242
2,556
1,664
4,220
Percent
100.00%
98.32%
99.28%
97.14%
97.32%
98.79%
97.12%
98.78%
98.84%
97.71%
98.39%
2010
Percent
100.0%
98.76%
99.44%
97.92%
97.75%
99.20%
97.62%
99.18%
99.23%
98.18%
98.81%
2011
Percent
100.0%
99.00%
99.64%
98.20%
97.92%
99.46%
98.01%
99.36%
99.42%
98.47%
99.04%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HR5 | Personnel Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
3,568
2,387
1,373
776
2,984
694
3,066
2,473
1,287
3,760
Percent
100.00%
87.09%
95.21%
77.05%
67.19%
95.21%
68.92%
93.42%
95.63%
75.57%
87.67%
2010
Percent
100.0%
88.24%
95.61%
79.12%
69.78%
95.76%
70.61%
94.33%
96.33%
77.28%
88.76%
2011
Percent
100.0%
89.46%
96.49%
80.70%
72.12%
96.49%
73.78%
94.88%
96.64%
79.74%
89.93%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HR6 | Time & Attendance
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
188
3,730
2,407
1,511
911
3,007
813
3,105
2,490
1,428
3,918
Percent
97.92%
91.04%
96.01%
84.79%
78.87%
95.95%
80.73%
94.61%
96.29%
83.85%
91.35%
2010
Percent
98.44%
92.78%
96.97%
87.49%
82.42%
96.94%
83.42%
95.98%
97.41%
86.38%
93.03%
2011
Source: HIMSS Analytics® Database 2011
Percent
98.44%
93.95%
97.81%
89.00%
84.59%
97.67%
85.60%
96.77%
97.72%
88.73%
94.15%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
19
▶▶ Human Resource Environment con tinued
When evaluating the market by bed-size segments, we find the
following notable changes from 2010 to 2011:
• 0–100 beds: adoption of personnel management application
increased the most when compared to the other HR applications
from 2010 to 2011 at slightly under two percent; time &
attendance and benefits administration increased by little over
one percent each (see Table HR7).
• 101–200 beds: growth of all HR applications in this bed-size
segment was less than one percent; growth was greatest for
time & attendance (see Table HR8).
• 201–300 beds: growth for all HR applications in hospitals in this
bed-size segment was less than one percent; growth was greatest
for the benefits administration application (see Table HR9).
Table HR7
0–100 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
1,718
2,120
1,688
1,877
78.77%
97.20%
77.40%
86.06%
2010
2011
% of 2,181 Hospitals
1,752 80.33% 1,781 81.66%
2,136 97.94% 2,143 98.26%
1,731 79.37% 1,774 81.34%
1,934 88.67% 1,970 90.33%
Table HR8
101–200 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
798
816
798
787
97.08%
99.27%
97.08%
95.74%
2010
% of 822 Hospitals
795 96.72%
819 99.64%
801 97.45%
797 96.96%
2011
800
820
804
804
97.32%
99.76%
97.81%
97.81%
Table HR9
201–300 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
497
503
495
485
98.61%
99.80%
98.21%
96.23%
2010
% of 504 Hospitals
494 98.02%
503 99.80%
496 98.41%
492 97.62%
2011
497
503
497
494
98.61%
99.80%
98.61%
98.02%
Table HR10
301–400 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
323 98.48%
328 100.00%
327 99.70%
322 98.17%
2010
% of 328 Hospitals
321 97.87%
326 99.39%
325 99.09%
319 97.26%
2011
323 98.48%
328 100.00%
328 100.00%
322 98.17%
Table HR11
401–500 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
180 98.90%
182 100.00%
182 100.00%
181 99.45%
2010
% of 182 Hospitals
180 98.90%
182 100.00%
182 100.00%
180 98.90%
2011
180 98.90%
182 100.00%
182 100.00%
180 98.90%
Table HR12
501–600 Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
119
121
120
119
97.54%
99.18%
98.36%
97.54%
2010
% of 122 Hospitals
120 98.36%
122 100.00%
122 100.00%
120 98.36%
2011
120 98.36%
122 100.00%
122 100.00%
119 97.54%
Table HR13
600+ Beds
Benefits Administration
Payroll
Personnel Management
Time & Attendance
2009
114 76.00%
150 100.00%
150 100.00%
147 98.00%
2010
% of 150 Hospitals
145 96.67%
150 100.00%
150 100.00%
148 98.67%
2011
145 96.67%
150 100.00%
150 100.00%
149 99.33%
20 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
• 301–400 beds: payroll and personnel management reached
100 percent market saturation, while time & attendance and
benefits administration demonstrated a slight increase, less
than one percent (see Table HR10).
• 401–500 beds: market penetration remained unchanged in this
segment across all HR applications. Payroll and personnel
management are the only applications at 100 percent market
saturation in 2011 (see Table HR11).
• 501–600 beds: with the exception of time & attendance, all
of the applications remained unchanged; time & attendance
showed approximately a one percent decrease in market
penetration (see Table HR12).
• 600+ beds: time & attendance increased by approximately one
percent in the past year, while the other applications remained
unchanged (see Table HR13).
Nearly one-quarter of HR contracts have been signed between 2005
and 2011. As such, many hospitals are using HR applications that
may be nearing end of useful life capabilities in their environments
and are making efforts to replace these solutions (Table HR14 and
HR15). It is a reasonable assumption that the replacement market
will continue to be active and some hospitals may elect to replace
these applications as part of an ERP suite.
Future purchase of HR applications may be deferred as a result of
federal initiatives, including ICD-10-PCS and HIPAA 5010
implementations, as well as EMR implementations driven by
Medicare and Medicaid incentive funding. For this reason, it’s
logical to assume that hospitals will not be replacing older HR
applications unless it truly does not meet minimal requirements or
has been sunset by the vendor.
Table HR14
2011
Benefits Administration
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Payroll
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Personnel Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
117
272
894
787
583
2,653
2653
2653
2653
2653
2653
2,653
4.41%
10.25%
33.70%
29.66%
21.98%
100.00%
124
293
1,007
841
684
2,949
2949
2949
2949
2949
2949
2,949
4.20%
9.94%
34.15%
28.52%
23.19%
100.00%
128
274
920
789
579
2,690
2,689
2,689
2,689
2,689
2,689
2,690
4.76%
10.19%
34.21%
29.34%
21.53%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
45
182
827
806
492
2,352
2,352
2,352
2,352
2,352
2,352
2,352
1.91%
7.74%
35.16%
34.27%
20.92%
100.00%
Table HR15
2011
Time & Attendance
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
▶▶ Human Resource Environment con tinued
Market Drivers/Future Outlook
The HR Department IT application market has been and will
continue to be impacted through 2015 by:
• A weak economy and higher IT application priorities, such as
EMR and RCM applications, should drive most hospitals to
extend the useful life of these applications for as long as possible.
• The need to track security training and policies for all hospital
employees.
• Outsourcing services for the HR application suite that reduce
capital requirements.
• Continued shortages of clinicians, especially pharmacists,
nurses, and IT staff will drive interest in manpower planning,
skills training and enhanced recruiting tools.
• The need for a centralized HR capability in a growing IDN where
employees are internally mobile.
• Acquisitions and mergers of healthcare IT vendors; the current
economy will drive this activity.
• Service as a Software (SaaS)/Application solutions provider
(ASP) products which will appeal to smaller hospitals that don’t
have the IT staff to support a large portfolio of IT applications.
• Potential government regulations (e.g., nurse staffing ratios,
healthcare savings accounts, public insurance options).
• Innovative benefits packages crafted to attract and retain skilled
clinicians.
• The necessity to track clinician credentials and continuing
education for all hospital employees.
• The need to drive efficiencies in HR departments through
the expanded use of e-HR functions such as e-recruiting,
HR Portals, etc.
▶▶ Revenue Cycle Management Environment
A successful healthcare revenue cycle management (RCM)
environment enables a healthcare organization to accelerate
revenue cycles by reducing the number of denied claims, avoiding
insurance underpayments, eliminating billing errors, improving
operational efficiencies and reducing the number of days in
accounts receivable (A/R). Eight RCM applications are tracked
in this report: ADT/registration, bed management, contract
management, credits/collections, electronic data interchangeclearinghouse vendor (EDI), enterprise master person index
(EMPI), patient billing and patient scheduling.
As one of the most mature of hospital applications, ADT/
registration, patient billing and patient scheduling continue to be at
market saturation (over 95 percent) in 2011. Use of credit/collection
solutions is also approaching market saturation (92 percent). Bed
management and EDI–clearinghouse both showed growth of over
four percent in the last year; growth of EMPI was also at nearly four
percent. All other applications demonstrated growth, although the
Table RCM1 | Revenue Cycle Management
N=4,289
2009
2010
ADT/Registration
99.46%
99.63%
Bed Management
29.63%
33.46%
Contract Management
64.63%
66.24%
Credit/Collections
89.88%
90.93%
EDI – Clearinghouse Vendor
74.33%
80.02%
Enterprise Master Person Index (EMPI)
44.30%
48.40%
Patient Billing
99.30%
99.35%
Patient Scheduling
94.99%
96.01%
Percentages include installed, contracted or installation in process
2011
99.72%
37.96%
67.68%
91.68%
84.36%
51.95%
99.88%
96.85%
growth is relatively small (see Table RCM1). It is important to
note that EMPI capabilities are seen as essential for provider
organizations seeking higher levels of integration in care delivery
either within their own enterprises or in their relationships with
their attending physicians’ private practices and other provider
organizations in their communities—capabilities that will be
essential to comply with meaningful use. We also sense an increase
in the merger and acquisition rate which will also drive EMPI and
related consulting services.
The majority of reported purchasing plans for the RCM applications
tracked in this report were replacement purchases. All purchase
plans for ADT/registration, credit/collections, EDI and patient
billing will be made by hospitals that plan to replace their current
solutions. EMPI is the market that is most likely to hospitals
purchasing a solution for the first time; approximately one quarter
of the EMPI purchase plans will be first-time purchases (see Table
RCM2). High replacement purchases indicate that many installed
RCM applications are reaching the end of their product life cycles
(e.g., patient billing, ADT/registration, patient scheduling, and
credit/collections). We expect that replacement purchasing will
continue to grow significantly for RCM applications through 2015
due to impending federal regulation implementation dates that
will require significant changes for the RCM environment such as
ICD-10 coding adoption and the looming bundled payment revolution.
This market will also be impacted by the healthcare reform
legislative provisions and other information and process changes
demanded of hospitals by both public and private insurers.
Table RCM2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
ADT/Registration
75
100.00%
Bed Management
33
84.62%
Contract Management
42
89.36%
Credit/Collections
44
100.00%
EDI – Clearinghouse Vendor
16
100.00%
Enterprise Master Person Index (EMPI)
33
76.74%
Patient Billing
72
100.00%
Patient Scheduling
74
96.10%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
0
6
5
0
0
10
0
3
% of Hospitals Planning
to Purchase Software
for the First Time
0.00%
15.38%
10.64%
0.00%
0.00%
23.26%
0.00%
3.90%
Source: HIMSS Analytics® Database 2011
N = Total Number of
Hospitals Planning
75
39
47
44
16
43
72
77
©2012 HIMSS Analytics.
21
▶▶ Revenue Cycle Management Environment con tinued
An evaluation of hospital type market segments for RCM
applications for 2010–2011 shows:
• ADT/Registration: the ADT/registration market is virtually
saturated (99 percent or better) for all segments. As such, there is
very little room for increased market penetration and no segment
showed growth of more than one percent (see Table RCM3).
• Bed management: academic medical centers have nearly eight
percent growth for this application in the past year. All other
segments indicated an increase ranging from three to five percent
(see Table RCM4).
• Contract management: none of the hospitals segments
showed growth of more than two percent for this application
(see Table RCM5).
• Credit/collections: many market segments are at or near market
saturation for this application. At slightly less than two percent,
critical access and rural hospitals showed the best growth in the
past year (see Table RCM6).
• EDI: this application demonstrated consistent growth
across all market segments, ranging from three to five percent
(see Table RCM7).
• EMPI: hospitals across all segments reported growth ranging
from three to four percent; academic medical centers
demonstrating the highest growth in 2011 at slightly more than
four percent (see Table RCM8).
• Patient billing: all market segments have installation rates of at
least 99 percent. The only segment to demonstrate growth of
more than one percent was non-general medical/surgical facilities
(see Table RCM9).
• Patient scheduling: the market has achieved (or is approaching)
market segmentation across all hospital segments. The strongest
growth (at nearly three percent) was among rural hospitals (see
Table RCM10).
Table RCM3 | ADT/Registration
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
4,074
2,500
1,766
1,140
3,126
994
3,272
2,578
1,688
4,266
Percent
100.00%
99.44%
99.72%
99.10%
98.70%
99.74%
98.71%
99.70%
99.69%
99.12%
99.46%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,081
2,503
1,770
1,144
3,129
998
3,275
2,580
1,693
4,273
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
129
1,306
1,047
388
177
1,258
134
1,301
974
461
1,435
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
161
2,680
1,863
978
482
2,359
418
2,423
1,986
855
2,841
Percent
100.00%
99.61%
99.84%
99.33%
99.05%
99.84%
99.11%
99.79%
99.77%
99.41%
99.63%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,085
2,504
1,773
1,146
3,131
1,001
3,276
2,581
1,696
4,277
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
144
1,484
1,151
477
227
1,401
171
1,457
1,103
525
1,628
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
162
2,741
1,903
1,000
492
2,411
433
2,470
2,025
878
2,903
Percent
100.00%
99.71%
99.88%
99.49%
99.22%
99.90%
99.40%
99.82%
99.81%
99.59%
99.72%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RCM4 | Bed Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
101
1,041
848
294
125
1,017
104
1,038
781
361
1,142
Percent
52.60%
25.41%
33.83%
16.50%
10.82%
32.45%
10.33%
31.63%
30.20%
21.20%
26.63%
2010
Percent
67.19%
31.88%
41.76%
21.77%
15.32%
40.14%
13.31%
39.64%
37.66%
27.07%
33.46%
2011
Percent
75.00%
36.22%
45.91%
26.77%
19.65%
44.70%
16.98%
44.39%
42.65%
30.83%
37.96%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RCM5 | Contract Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
152
2,620
1,829
943
460
2,312
403
2,369
1,934
838
2,772
Percent
79.17%
63.95%
72.96%
52.92%
39.83%
73.77%
40.02%
72.18%
74.79%
49.21%
64.63%
2010
22 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
83.85%
65.41%
74.31%
54.88%
41.73%
75.27%
41.51%
73.83%
76.80%
50.21%
66.24%
2011
Percent
84.38%
66.90%
75.91%
56.12%
42.60%
76.93%
43.00%
75.26%
78.31%
51.56%
67.68%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Revenue Cycle Management Environment con tinued
Table RCM6 | Credit/Collections
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
179
3,676
2,382
1,473
918
2,937
796
3,059
2,421
1,434
3,855
Percent
93.23%
89.72%
95.01%
82.66%
79.48%
93.71%
79.05%
93.21%
93.62%
84.20%
89.88%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
3,717
2,387
1,513
944
2,956
821
3,079
2,431
1,469
3,900
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
168
3,264
2,047
1,385
864
2,568
741
2,691
2,084
1,348
3,432
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
138
1,938
1,358
718
444
1,632
357
1,719
1,383
693
2,076
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,069
2,506
1,755
1,150
3,111
1,004
3,257
2,562
1,699
4,261
Percent
95.31%
90.72%
95.21%
84.90%
81.73%
94.32%
81.53%
93.81%
94.01%
86.26%
90.93%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
184
3,748
2,406
1,526
962
2,970
837
3,095
2,448
1,484
3,932
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
174
3,444
2,154
1,464
912
2,706
779
2,839
2,204
1,414
3,618
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
146
2,082
1,458
770
482
1,746
388
1,840
1,485
1,840
2,228
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,092
2,506
1,778
1,151
3,133
1,006
3,278
2,582
1,702
4,284
Percent
95.83%
91.48%
95.97%
85.63%
83.29%
94.77%
83.12%
94.30%
94.66%
87.14%
91.68%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RCM7 | EDI – Clearinghouse Vendor
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
154
3,034
1,914
1,274
777
2,411
665
2,523
1,967
1,221
3,188
Percent
80.21%
74.05%
76.35%
71.49%
67.27%
76.93%
66.04%
76.87%
76.06%
71.70%
74.33%
2010
Percent
87.50%
79.67%
81.65%
77.72%
74.81%
81.94%
73.58%
81.99%
80.59%
79.15%
80.02%
2011
Percent
90.63%
84.06%
85.92%
82.15%
78.96%
86.34%
77.36%
86.50%
85.23%
83.03%
84.36%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RCM8 | Enterprise Master Person Index (EMPI)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
121
1,779
1,243
657
398
1,502
323
1,577
1,273
627
1,900
Percent
63.02%
43.42%
49.58%
36.87%
34.46%
47.93%
32.08%
48.05%
49.23%
36.82%
44.30%
2010
Percent
71.88%
47.30%
54.17%
40.29%
38.44%
52.07%
35.45%
52.38%
53.48%
40.69%
48.40%
2011
Percent
76.04%
50.82%
58.16%
43.21%
41.73%
55.71%
38.53%
56.06%
57.42%
43.63%
51.95%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RCM9 | Patient Billing
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
4,067
2,505
1,754
1,149
3,110
1,001
3,258
2,563
1,696
4,259
Percent
100.00%
99.27%
99.92%
98.43%
99.48%
99.23%
99.40%
99.27%
99.11%
99.59%
99.30%
2010
Percent
100.00%
99.32%
99.96%
98.48%
99.57%
99.27%
99.70%
99.24%
99.07%
99.77%
99.35%
2011
Source: HIMSS Analytics® Database 2011
Percent
100.00%
99.88%
99.96%
99.78%
99.65%
99.97%
99.90%
99.88%
99.85%
99.94%
99.88%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
23
▶▶ Revenue Cycle Management Environment con tinued
Table RCM10 | Patient Scheduling
2009
Segment
Count
191
3,883
2,463
1,611
994
3,080
879
3,195
2,512
1,562
0
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
99.48%
94.78%
98.24%
90.40%
86.06%
98.28%
87.29%
97.35%
97.14%
91.72%
0.00%
The analysis of this market by bed size in 2011 showed that ADT/
registration, patient billing, and patient scheduling are at, or near,
saturation for all bed segments; therefore, the growth opportunities
are limited for these applications. Bed management, EDI, and EMPI
share the top three growth rates across all segments from 2010 to
2011 (see Tables RCM11–RCM17) as follows:
• 0–100 beds: bed management and EDI showed the most growth,
at more than four percent each (see Table RCM11).
• 101–200 beds: the largest growth was demonstrated by EMPI at
about five percent. EDI also had growth of more than four
percent (see Table RCM12).
• 201–300 beds: EDI demonstrated a growth of more than five
percent while bed management and EMPI grew by more than
four percent. Patient billing reported a slight decrease from last
year (see Table RCM13).
• 301–400 beds: bed management demonstrated a growth of more
than six percent for this bed segment, followed by EDI at more
than five percent (see Table RCM14).
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
2009
2,160
317
1,127
1,833
1,543
99.04%
14.53%
51.67%
84.04%
70.75%
760
2,152
1,986
34.85%
98.67%
91.06%
2010
2011
% of 2,181 Hospitals
2,166 99.31% 2,170 99.50%
412 18.89%
506 23.20%
1,159 53.14% 1,198 54.93%
1,879 86.15% 1,901 87.16%
1,686 77.30% 1,775 81.38%
829
2,154
2,025
38.01%
98.76%
92.85%
901
2,177
2,059
41.31%
99.82%
94.41%
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
Segment
Count
192
3,962
2,485
1,669
1,049
3,105
921
3,233
2,547
1,607
0
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
100.00%
96.70%
99.12%
93.66%
90.82%
99.07%
91.46%
98.51%
98.49%
94.36%
0.00%
• 401–500 beds: bed management and EDI have the largest growth
in this segment at more than three percent (see Table RCM15).
• 501–600 beds: more than four percent growth was reported for
bed management and EMPI. EDI had a growth of three percent
in this segment (see Table RCM16).
• Over 600 beds: there was an eight percent increase for bed
management, while EDI utilization grew by more than four
percent (see Table RCM17).
Table rcm13
201–300 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
2009
504 100.00%
182 36.11%
387 76.79%
482 95.63%
379 75.20%
2010
% of 504 Hospitals
504 100.00%
239 47.42%
399 79.17%
480 95.24%
407 80.75%
2011
259 51.39%
504 100.00%
498 98.81%
288 57.14%
504 100.00%
500 99.21%
2009
328 100.00%
149 45.43%
268 81.71%
313 95.43%
265 80.79%
2010
% of 328 Hospitals
328 100.00%
183 55.79%
272 82.93%
312 95.12%
278 84.76%
328 100.00%
205 62.50%
274 83.54%
316 96.34%
295 89.94%
184 56.10%
328 100.00%
327 99.70%
202 61.59%
328 100.00%
327 99.70%
211 64.33%
328 100.00%
327 99.70%
2009
2011
182 100.00%
96 52.75%
155 85.16%
175 96.15%
138 75.82%
2010
% of 182 Hospitals
182 100.00%
112 61.54%
156 85.71%
175 96.15%
147 80.77%
182 100.00%
119 65.38%
157 86.26%
176 96.70%
153 84.07%
106 58.24%
182 100.00%
182 100.00%
116 63.74%
182 100.00%
182 100.00%
117 64.29%
182 100.00%
182 100.00%
504 100.00%
263 52.18%
407 80.75%
482 95.63%
435 86.31%
310
503
501
61.51%
99.80%
99.40%
301–400 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
2011
Table rcm15
Table rcm12
101–200 Beds
Percent
100.00%
95.83%
98.64%
92.31%
88.74%
98.69%
88.88%
98.20%
97.91%
93.13%
0.00%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table rcm14
Table rcm11
0–100 Beds
Segment
Count
192
3,926
2,473
1,645
1,025
3,093
895
3,223
2,532
1,586
0
2009
820
240
614
794
646
99.76%
29.20%
74.70%
96.59%
78.59%
417
821
811
50.73%
99.88%
98.66%
2010
% of 822 Hospitals
821 99.88%
300 36.50%
627 76.28%
793 96.47%
675 82.12%
453
821
813
55.11%
99.88%
98.91%
2011
821
328
635
795
711
99.88%
39.90%
77.25%
96.72%
86.50%
492 59.85%
822 100.00%
813 98.91%
24 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
401–500 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
▶▶ Revenue Cycle Management Environment con tinued
Table rcm16
501–600 Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
Table RCM18
2009
122 100.00%
66 54.10%
102 83.61%
116 95.08%
97 79.51%
2010
% of 122 Hospitals
122 100.00%
78 63.93%
103 84.43%
117 95.90%
107 87.70%
2011
122 100.00%
83 68.03%
103 84.43%
117 95.90%
111 90.98%
75 61.48%
122 100.00%
121 99.18%
75 61.48%
122 100.00%
121 99.18%
80 65.57%
122 100.00%
122 100.00%
2009
2011
150 100.00%
92 61.33%
119 79.33%
142 94.67%
120 80.00%
2010
% of 150 Hospitals
150 100.00%
111 74.00%
125 83.33%
144 96.00%
132 88.00%
150 100.00%
124 82.67%
129 86.00%
145 96.67%
138 92.00%
99 66.00%
150 100.00%
149 99.33%
113 75.33%
150 100.00%
150 100.00%
117 78.00%
150 100.00%
150 100.00%
Table rcm17
600+ Beds
ADT/Registration
Bed Management
Contract Management
Credit/Collections
EDI–Clearinghouse Vendor
Enterprise Master Person
Index (EMPI)
Patient Billing
Patient Scheduling
In evaluating the contract purchasing timeframes for RCM
applications in 2010, more than 85 percent of the bed management
purchases were completed in 2000 or later, with the majority of
these purchases (61 percent) occurring since 2005 (see Tables
RCM18 to RCM20). Close to half of the contracts for EDI occurred
between 2005 and 2011. Since the legacy-based RCM applications
such as ADT/ registration, credits/collections, patient scheduling
and patient billing have reached or are on the verge of achieving
market saturation, these applications are most likely subject to
replacement over the next three to five years.
Market Drivers/Future Outlook
The RCM IT application market has been and will continue to
be impacted through 2015 by:
• The conversion to ICD-10 coding; currently scheduled for
October 1, 2013.
• The need of many organizations to update or replace their
legacy RCM environments to effectively meet ICD-10 upgrade
and conversion requirements.
• The emergence of shared savings bundled reimbursement
models, in response to pay-for-performance initiatives from
federal programs as well as private insurers.
• Tight capital markets and limited capital budgets.
• The focus on consumer/patient satisfaction (e.g., pricing
transparency, consumer friendly billing formats, on-line bill
paying, self-scheduling, pre-registration and other Web-based,
self-service applications).
• The need to more effectively integrate financial and clinical
data for business analysis and government reporting.
• The need to more effectively integrate financial decision
support into the RCM environment.
2011
ADT/Registration
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Bed Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Contract Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
153
406
851
866
886
3,162
3,162
3,162
3,162
3,162
3,162
3,162
4.84%
12.84%
26.91%
27.39%
28.02%
100.00%
8
25
45
132
328
538
538
538
538
538
538
538
1.49%
4.65%
8.36%
24.54%
60.97%
100.00%
57
112
427
607
539
1,742
1,742
1,742
1,742
1,742
1,742
1,742
3.27%
6.43%
24.51%
34.85%
30.94%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
133
412
774
727
778
2,824
2,824
2,824
2,824
2,824
2,824
2,824
4.71%
14.59%
27.41%
25.74%
27.55%
100.00%
16
46
260
336
536
1,194
1,194
1,194
1,194
1,194
1,194
1,194
1.34%
3.85%
21.78%
28.14%
44.89%
100.00%
13
71
210
463
460
1,217
1,217
1,217
1,217
1,217
1,217
1,217
1.07%
5.83%
17.26%
38.04%
37.80%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
170
408
865
837
856
3,136
3,136
3,136
3,136
3,136
3,136
3,136
5.42%
13.01%
27.30%
26.69%
27.30%
100.00%
53
269
614
861
857
2,654
2,654
2,654
2,654
2,654
2,654
2,654
2.00%
10.14%
23.13%
32.44%
32.29%
100.00%
Table RCM19
2011
Credit/Collections
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
EDI–Clearinghouse Vendor
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Enterprise Master Person Index (EMPI)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table RCM20
2011
Patient Billing
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Patient Scheduling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
25
▶▶ Next Generation Revenue Cycle Management
Next generation revenue cycle management (NGRCM) functions are
intended to reflect trends in the adoption of the latest generation of
RCM solutions designed to complement and enhance core legacy
RCM applications. These are solutions that focus on improving
collection rate, business office workflows, productivity and the
overall efficiency of the RCM process, while also improving patient
satisfaction and convenience.
This index is based on five NGRCM components that improve
both upstream and downstream processes in the RCM environment.
Each component contains several solutions and this report will
focus on 13 different solutions across the five NGRCM components:
• Consumer focus: this NGRCM environment provides the ability
to extend B2C (Business to Consumer) Web services to patients
to facilitate on-line pre-registration, self-scheduling, and bill
payment to enhance patient service efficiency and convenience.
• Eligibility verification: this NGRCM environment supports realtime insurance eligibility verification transactions to mitigate the
risk of providing services that are not covered by the patient’s
insurance.
• Rules capability for billing and payment processing: this
NGRCM environment includes rules engines which facilitate
medical necessity checking during patient scheduling and
registration functions; determine self-pay patient liability prior to
or at the point of registration; and compare submitted, allowed
and paid claims against contractual terms to identify and
facilitate claims resubmissions. It also allows business office
personnel to edit bills on-line prior to submission, if needed, to
improve billing accuracy and compliance with contractual terms
and to provide the necessary updates to all billing and accounts
receivable files related to those edits. NGRCM tools can also
accommodate the autoencoding of clinical information from the
EMR system, determine claims attachment requirements and
automatically create required attachments (when such supporting
data exists in digital form, such as in the EMR) prior to claim
submission to avoid denied or pended claims and improve the
efficiency and accuracy of the billing process.
• Claims processing: this NGRCM environment provides the
ability to submit claims directly to payers, eliminating the need
for third-party clearinghouse intermediary, accepts direct
electronic claims remittance transactions from payers and directly
posts third-party payments against patient specific receivables
from bundled remittance transactions.
Table NGRCM1 | Next Generation Revenue Cycle Management
N=4,289
2009
2010
Biller’s Dash Board
18.00%
22.48%
Claims Attachment Rules
18.86%
25.95%
Claims Remittance Updates AR
12.50%
15.43%
Denial Rules
17.04%
26.67%
Direct Payer Claims
10.73%
12.38%
EFT Transaction
17.00%
24.20%
Eligibility Transaction with Payer
12.31%
15.55%
EMR Documentation for Claims
8.39%
4.08%
Necessity Alert @ Registration
23.57%
35.60%
Necessity Alert @ Scheduling
13.94%
21.31%
Web PreRegister
16.90%
16.85%
Web Schedule
7.53%
6.81%
Web Self Pay
28.35%
26.77%
Percentage include installed, contracted or installation in process
2011
25.46%
28.54%
16.93%
30.12%
13.10%
26.00%
16.97%
2.96%
37.93%
22.94%
19.21%
6.95%
32.41%
26 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
• Treasury functions: this NGRCM environment provides
electronic funds transfers (EFT) from third-party payers directly
to the provider organization’s bank accounts to improve cash flow
and facilitate financial reconciliation processes for the
organization.
• In general, most of the NGRCM solutions indicated an increased
adoption rate from 2010 to 2011 except for EMR documentation
for claims and necessity alert at scheduling. The growth ranged
from slightly less than six percent for Web self pay to less than
one percent for Web scheduling and direct payer claims. The
decrease reported by EMR documentation for claims and
necessity alert at scheduling were minimal (slightly over one
percent). One reason for the decline in EMR documentation for
claims could be attributed to the change in data collection that
occurred in 2010. The method of collecting changed after 2009
as the definition was updated that narrowly defined this market.
The highest market penetration for the next generation RCM
applications tracked in this report is necessity alert at registration
at 38 percent, followed by Web self pay (see Table NGRCM1).
Hospital requirements for adoption will be based on business needs,
strategies and their competitive environment. Hospitals must be
aware of the impact that ICD-10 coding upgrades will have on
many of these applications and, with the deadline approaching in
October of 2013, they should be implementing their upgrade
strategies now. The NGRCM index is designed to allow hospitals to
compare their use of NGRCM capabilities against the market and
their peers. Unlike the other sections of the annual report, planned
purchase data is not available for NGRCM applications.
An evaluation of this market in 2011 by hospital type shows the
following trends:
Consumer Focus
• Web pre-registration: from 2010 to 2011, the adoption rate
increased the highest for the general medical/surgical segment at
slightly under four percent. Most of the other segments with the
exception of academic medical centers indicated an increase over
the same timeframe. The adoption rate for the academic medical
center segment decreased by three percent (see Table NGRCM2).
• Web scheduling: growth for this application across all market
segments is limited; there was a slight decrease in utilization
in the academic medical center and single hospital segments
(see Table NGRCM3).
• Web self pay: growth across most of the key hospital segments
for this application was between four and six percent, with the
exception of medical/surgical hospitals and critical access
hospitals which exceeded six percent. There was a slight decrease
in use among academic medical centers (see Table NGRCM4).
Eligibility Verification
• Medical necessity alerts at the point of scheduling: the highest
growth in adoption occurred in the academic medical center
segment at more than three percent. Growth in most of the other
market segments was two percent or less (see Table NGRCM5).
• Medical necessity alerts at point of registration: every segment
indicated low to moderate growth from 2010 to 2011; ranging
from one percent to more than six percent. Academic medical
center segments demonstrated an increase of more than six
percent (see Table NGRCM6).
▶▶ Next Generation Revenue Cycle Management con tinued
Rules and Billing Capabilities
• Claims attachment rules: the academic medical center segment
has the highest growth in adoption rates at close to five percent,
followed by the single hospital system segment at nearly four
percent (see Table NGRCM7).
• Denials rules: the academic medical center segment indicated
the largest growth at slightly more than six percent while the
single hospital system segment has growth of more than five
percent. Growth among the remaining segments was between
two and three percent (see Table NGRCM8).
• Biller’s dashboard: the single hospital segment has the
highest growth rate at more than four percent followed by
academic medical centers at nearly three percent. Growth
for the remaining markets was between two and three percent
(see Table NGRCM9).
• EMR documentation for claims: there was a decline in utilization
for this application across all market segments. The greatest
decline was among academic medical centers at slightly more
than three percent (see Table NGRCM10).
Claims Processing
• Direct payer claims (no clearinghouse): very little growth was
reported for this solution across all the hospital segments.
Academic medical centers have the highest growth in the past
year (more than two percent) followed by the single hospital
system segment (more than one percent). All other segments
indicated growth of less than one percent (see Table NGRCM11).
• Claims remittance with accounts receivable update: the academic
medical center segment demonstrated the highest growth rate in
the past year at more than five percent. Growth in all remaining
segments was less than two percent (see Table NGRCM12).
• Eligibility transaction with payer (no clearinghouse): the single
hospital systems segment has the highest growth from 2010 to
2011 at more than two percent (see Table NGRCM13).
Treasury Funds
• Electronic funds transfer transactions (direct to organization’s
bank): this application demonstrated growth of more than five
percent at academic medical centers. All other segments reported
growth between one to two percent (see Table NGRCM14).
Table NGRCM2 | Web Pre-Register
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
38
687
561
164
89
636
81
644
610
115
725
Percent
19.79%
16.77%
22.38%
9.20%
7.71%
20.29%
8.04%
19.62%
23.59%
6.75%
16.90%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
38
687
552
170
99
623
84
638
609
113
723
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
40
252
203
89
28
264
21
271
250
42
292
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
66
1,082
830
318
198
950
174
974
885
263
1,148
Percent
19.79%
16.77%
22.02%
9.54%
8.57%
19.88%
8.34%
19.44%
23.55%
6.64%
16.85%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
32
792
650
174
104
720
106
718
701
123
824
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
33
265
213
85
30
268
27
271
262
36
298
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
65
1,325
1,002
388
270
1,120
234
1,156
1,033
357
1,390
Percent
16.67%
19.33%
25.93%
9.76%
9.00%
22.97%
10.53%
21.88%
27.11%
7.22%
19.21%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM3 | Web Schedule
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
41
282
221
102
38
285
27
296
272
51
323
Percent
21.35%
6.88%
8.82%
5.72%
3.29%
9.09%
2.68%
9.02%
10.52%
2.99%
7.53%
2010
Percent
20.83%
6.15%
8.10%
4.99%
2.42%
8.42%
2.09%
8.26%
9.67%
2.47%
6.81%
2011
Percent
17.19%
6.47%
8.50%
4.77%
2.60%
8.55%
2.68%
8.26%
10.13%
2.11%
6.95%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM4 | Web Self Pay
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
68
1,148
915
301
175
1,041
172
1,044
980
236
1,216
Percent
35.42%
28.02%
36.50%
16.89%
15.15%
33.22%
17.08%
31.81%
37.90%
13.86%
28.35%
2010
Percent
34.38%
26.41%
33.11%
17.85%
17.14%
30.31%
17.28%
29.68%
34.22%
15.44%
26.77%
2011
Source: HIMSS Analytics® Database 2011
Percent
33.85%
32.34%
39.97%
21.77%
23.38%
35.74%
23.24%
35.22%
39.95%
20.96%
32.41%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
27
▶▶ Next Generation Revenue Cycle Management con tinued
Table NGRCM5 | Necessity Alert @ Scheduling
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
19
579
447
151
108
490
82
516
418
180
598
Percent
9.90%
14.13%
17.83%
8.47%
9.35%
15.63%
8.14%
15.72%
16.16%
10.57%
13.94%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
33
881
1,003
524
177
737
137
777
618
296
941
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
62
1,465
1,003
524
310
1,217
269
1,258
1,048
479
1,527
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
56
1,057
716
397
199
914
173
940
671
442
1,113
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
66
1,078
723
421
207
937
182
962
675
469
1,144
Percent
17.19%
21.50%
26.69%
13.75%
15.32%
23.52%
13.60%
23.67%
23.90%
17.38%
21.31%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
39
945
721
263
184
800
145
839
643
341
984
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
74
1,553
1,069
558
327
1,300
286
1,341
1,098
529
1,627
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
65
1,159
783
441
231
993
192
1,032
717
507
1,224
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
78
1,214
810
482
248
1,044
210
1,082
728
564
1,292
Percent
20.31%
23.07%
28.76%
14.76%
15.93%
25.53%
14.40%
25.56%
24.86%
20.02%
22.94%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM6 | Necessity Alert @ Registration
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
34
977
652
359
199
812
174
837
710
301
1,011
Percent
17.71%
23.85%
26.01%
20.15%
17.23%
25.91%
17.28%
25.50%
27.46%
17.67%
23.57%
2010
Percent
32.29%
35.76%
40.01%
29.41%
26.84%
38.83%
26.71%
38.33%
40.53%
28.13%
35.60%
2011
Percent
38.54%
37.91%
42.64%
31.31%
28.31%
41.48%
28.40%
40.86%
42.46%
31.06%
37.93%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM7 | Claims Attachment Rules
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
40
769
513
296
129
680
113
696
526
283
809
Percent
20.83%
18.77%
20.46%
16.61%
11.17%
21.70%
11.22%
21.21%
20.34%
16.62%
18.86%
2010
Percent
29.17%
25.80%
28.56%
22.28%
17.23%
29.16%
17.18%
28.64%
25.95%
25.95%
25.95%
2011
Percent
33.85%
28.29%
31.23%
24.75%
20.00%
31.68%
19.07%
31.44%
27.73%
29.77%
28.54%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM8 | Denial Rules
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
44
687
446
285
118
613
101
630
465
266
731
Percent
22.92%
16.77%
17.79%
15.99%
10.22%
19.56%
10.03%
19.20%
17.98%
15.62%
17.04%
2010
28 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
34.38%
26.31%
28.84%
23.63%
17.92%
29.90%
18.07%
29.31%
26.10%
27.54%
26.67%
2011
Percent
40.63%
29.63%
32.31%
27.05%
21.47%
33.31%
20.85%
32.97%
28.15%
33.12%
30.12%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Next Generation Revenue Cycle Management con tinued
Table NGRCM9 | Biller’s Dashboard
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
42
730
457
315
155
617
152
620
480
292
772
Percent
21.88%
17.82%
18.23%
17.68%
13.42%
19.69%
15.09%
18.89%
18.56%
17.15%
18.00%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
53
911
570
394
207
757
190
774
558
406
964
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
17
158
123
52
26
149
27
148
85
90
175
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
36
495
337
194
125
406
105
426
287
244
531
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
43
619
371
291
125
537
102
560
388
274
662
Percent
27.60%
22.24%
22.74%
22.11%
17.92%
24.15%
18.87%
23.58%
21.58%
23.84%
22.48%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
60
1,032
652
440
238
854
216
876
612
480
1,092
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
11
116
88
39
20
107
18
109
68
59
127
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
41
521
352
210
128
434
108
454
293
269
562
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
53
673
418
308
128
598
104
622
423
303
726
Percent
31.25%
25.19%
26.01%
24.69%
20.61%
27.25%
21.45%
26.69%
23.67%
28.19%
25.46%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM10 | EMR Documentation for Claims
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
31
329
246
114
66
294
62
298
210
150
360
Percent
16.15%
8.03%
9.81%
6.40%
5.71%
9.38%
6.16%
9.08%
8.39%
8.81%
8.39%
2010
Percent
8.85%
3.86%
4.91%
2.92%
2.25%
4.75%
2.68%
4.51%
4.12%
5.28%
4.08%
2011
Percent
5.73%
2.83%
3.51%
2.19%
1.73%
3.41%
1.79%
3.32%
2.96%
3.46%
2.96%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM11 | Direct Payer Claims
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
29
431
300
160
104
356
93
367
270
190
460
Percent
15.10%
10.52%
11.97%
8.98%
9.00%
11.36%
9.24%
11.18%
10.44%
11.16%
10.73%
2010
Percent
18.75%
12.08%
13.44%
10.89%
10.82%
12.95%
10.43%
12.98%
11.10%
14.33%
12.38%
2011
Percent
21.35%
12.72%
14.04%
11.78%
11.08%
13.85%
10.72%
13.83%
11.33%
15.80%
13.10%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM12 | Claims Remittance Updates AR
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
34
502
294
242
95
441
79
457
344
192
536
Percent
17.71%
12.25%
11.73%
13.58%
8.23%
14.07%
7.85%
13.92%
13.30%
11.27%
12.50%
2010
Percent
22.40%
15.11%
14.80%
16.33%
10.82%
17.13%
10.13%
17.06%
15.00%
16.09%
15.43%
2011
Source: HIMSS Analytics® Database 2011
Percent
27.60%
16.43%
16.67%
17.28%
11.08%
19.08%
10.33%
18.95%
16.36%
17.79%
16.93%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
29
▶▶ Next Generation Revenue Cycle Management con tinued
Table NGRCM13 | Eligibility Transaction with Payer
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
23
505
289
239
104
424
82
446
330
198
528
Percent
11.98%
12.33%
11.53%
13.41%
9.00%
13.53%
8.14%
13.59%
12.76%
11.63%
12.31%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
36
631
370
297
142
525
109
558
386
281
667
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
60
978
619
419
226
812
192
846
600
438
1,038
Percent
18.75%
15.40%
14.76%
16.67%
12.29%
16.75%
10.82%
17.00%
14.93%
16.50%
15.55%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
39
689
406
322
156
572
121
607
406
322
728
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
70
1,045
654
461
250
865
208
907
625
490
1,115
Percent
20.31%
16.82%
16.19%
18.07%
13.51%
18.25%
12.02%
18.49%
15.70%
18.91%
16.97%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table NGRCM14 | EFT Transaction
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
41
688
407
322
158
571
140
589
429
300
729
Percent
21.35%
16.79%
16.23%
18.07%
13.68%
18.22%
13.90%
17.95%
16.59%
17.62%
17.00%
2010
An evaluation of adoption of NGRCM functions by hospital bedsize segments provides the following insights in adoption from 2010
to 2011 (see Tables NGRCM15–NGRCM21):
• 0–100 beds: in this bed segment, Web self pay demonstrated the
largest increase in adoption from 2010 to 2011 at more than five
percent. Most of the other NGRCM applications, except EMR
documentation for claims, showed increases in adoption (see
Table NGRCM15).
• 101–200 beds: at more than seven percent, Web self pay reported
the largest increase from 2010 to 2011. The next highest growth
was reported for Web pre-register at slightly less than five
percent. EMR documentation for claims is the only solution to
indicate a decline, while the adoption rate for the other solutions
grew in the same timeframe (see Table NGRCM16).
• 201–300 beds: growth for Web self pay, claims attachment rules,
denial rules and Web pre-register was more than five percent for
each application. With the exception of EMR documentation for
claims and Web scheduling, growth for the remaining segments
was between two and four percent (see Table NGRCM17).
• 301–400 beds: the majority of applications demonstrated
growth of one to three percent. However, growth for Web self
pay was nearly five percent. A decrease in utilization occurred
for EMR documentation for claims and Web pre-register
(see Table NGRCM18).
• 401–500 beds: Web self pay reported an increase of more than
seven percent from 2010 to 2011. Web pre-register, EMR
documentation for claims and direct payer claims reported a
decline in utilization (see Table NGRCM19).
30 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
31.25%
23.87%
24.69%
23.51%
19.57%
25.91%
19.07%
25.78%
23.20%
25.72%
24.20%
2011
Percent
36.46%
25.51%
26.09%
25.87%
21.65%
27.60%
20.66%
27.64%
24.17%
28.77%
26.00%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
• 501–600 beds: Web self pay, claims attachment rules and claims
remittance updates AR had the highest growth at slightly more
than four percent. Web scheduling and EMR documentation for
claims were two areas that reported a decrease in utilization in
the past year (see Table NGRCM20).
• 600+ beds: Web schedule and EMR documentation for claims
were the only applications to decrease in utilization in the
past year. Necessity alert at registration had the highest increase
in adoption from 2010 to 2011 at more than seven percent
(see Table NGRCM21).
Market Drivers/Future Outlook
The NGRCM market is still in its infancy, but these applications
will become critical solutions for all hospitals within the next few
years as indicated in the summary (see Table NGRCM1). This
market will continue to be impacted through 2015 by:
• In the short run, capital constraints and the intense competition
of IT capital funds, which will drive many hospitals to acquire
bolt-on NGRCM applications to enhance their existing legacy
RCM environments, extending their useful life.
• Many NGRCM applications in each of the product categories
described are currently marketed by relatively small, specialty
vendors. Over time, we expect that the larger RCM vendors will
introduce similar capabilities as an integral component of new
versions; hospitals upgrading to these new versions will displace
these niche products.
• In addition, over the longer term, as more small to mid-sized
hospitals contract for EMRs, many of these will also to take the
▶▶ Next Generation Revenue Cycle Management con tinued
Table NGRCM15
0–100 Beds
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
Table NGRCM18
2009
222
80
406
212
454
358
330
374
128
186
260
263
372
10.18%
3.67%
18.62%
9.72%
20.82%
16.41%
15.13%
17.15%
5.87%
8.53%
11.92%
12.06%
17.06%
2010
% of 2,181 Hospitals
231 10.59%
64
2.93%
430 19.72%
337 15.45%
683 31.32%
499 22.88%
517 23.70%
473 21.69%
60
2.75%
235 10.77%
322 14.76%
338 15.50%
503 23.06%
2011
269
68
542
353
723
540
580
529
42
249
333
368
540
12.33%
3.12%
24.85%
16.19%
33.15%
24.76%
26.59%
24.25%
1.93%
11.42%
15.27%
16.87%
24.76%
Table NGRCM16
101–200 Beds
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
2009
84
44
119
62
98
70
59
60
37
52
46
40
54
25.61%
13.41%
36.28%
18.90%
29.88%
21.34%
17.99%
18.29%
11.28%
15.85%
14.02%
12.20%
16.46%
2010
% of 328 Hospitals
85 25.91%
40 12.20%
114 34.76%
96 29.27%
145 44.21%
104 31.71%
100 30.49%
84 25.61%
18
5.49%
52 15.85%
53 16.16%
50 15.24%
87 26.52%
2011
83
47
130
100
148
109
109
91
17
56
62
51
93
25.30%
14.33%
39.63%
30.49%
45.12%
33.23%
33.23%
27.74%
5.18%
17.07%
18.90%
15.55%
28.35%
Table NGRCM19
2009
175
69
323
156
223
163
145
132
65
83
83
91
126
21.29%
8.39%
39.29%
18.98%
27.13%
19.83%
17.64%
16.06%
7.91%
10.10%
10.10%
11.07%
15.33%
2010
% of 822 Hospitals
179 21.78%
71
8.64%
284 34.55%
219 26.64%
329 40.02%
217 26.40%
227 27.62%
159 19.34%
36
4.38%
88 10.71%
107 13.02%
113 13.75%
187 22.75%
2011
219
72
347
244
350
241
261
188
24
94
125
124
203
26.64%
8.76%
42.21%
29.68%
42.58%
29.32%
31.75%
22.87%
2.92%
11.44%
15.21%
15.09%
24.70%
Table NGRCM17
201–300 Beds
301–400 Beds
401–500 Beds
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
2009
55
21
73
40
62
51
46
44
33
41
36
30
40
30.22%
11.54%
40.11%
21.98%
34.07%
28.02%
25.27%
24.18%
18.13%
22.53%
19.78%
16.48%
21.98%
2010
% of 182 Hospitals
48 26.37%
17
9.34%
61 33.52%
53 29.12%
82 45.05%
68 37.36%
67 36.81%
56 30.77%
15
8.24%
42 23.08%
43 23.63%
40 21.98%
61 33.52%
2011
44
17
74
59
88
71
71
62
9
37
47
41
62
24.18%
9.34%
40.66%
32.42%
48.35%
39.01%
39.01%
34.07%
4.95%
20.33%
25.82%
22.53%
34.07%
Table NGRCM20
2009
120
65
188
83
113
103
86
103
59
61
72
70
83
23.81%
12.90%
37.30%
16.47%
22.42%
20.44%
17.06%
20.44%
11.71%
12.10%
14.29%
13.89%
16.47%
2010
% of 504 Hospitals
106 21.03%
59 11.71%
156 30.95%
137 27.18%
187 37.10%
137 27.18%
138 27.38%
117 23.21%
25
4.96%
62 12.30%
83 16.47%
77 15.28%
124 24.60%
2011
132
60
187
147
205
166
164
136
19
72
94
86
135
26.19%
11.90%
37.10%
29.17%
40.67%
32.94%
32.54%
26.98%
3.77%
14.29%
18.65%
17.06%
26.79%
opportunity to acquire complete application suites, including
replacement of legacy RCM applications with versions which
incorporate these features. In the meantime, it is possible that
some previous niche products will be decommissioned by the
providers while the newer comprehensive system is being
implemented to its fullest capabilities. This could explain the
small decreases in utilization of some NGRM features in
academic medical centers.
• It is also important to keep in mind that electronic insurance
eligibility verification and electronic claims submission were
requirements in the draft Stage 1 meaningful use requirements
originally published in December, 2009. Although these were
eliminated from the July, 2010 final rule, look for them to be
incorporated into the Stage 2 requirements that will take effect
in 2014 with the one-year extension.
501–600 Beds
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
2009
32
12
49
22
30
30
31
26
15
18
17
16
24
26.23%
9.84%
40.16%
18.03%
24.59%
24.59%
25.41%
21.31%
12.30%
14.75%
13.93%
13.11%
19.67%
2010
% of 122 Hospitals
38 31.15%
14 11.48%
49 40.16%
33 27.05%
50 40.98%
37 30.33%
40 32.79%
34 27.87%
6
4.92%
23 18.85%
23 18.85%
22 18.03%
30 24.59%
2011
38
12
54
34
51
42
44
38
5
24
28
25
32
31.15%
9.84%
44.26%
27.87%
41.80%
34.43%
36.07%
31.15%
4.10%
19.67%
22.95%
20.49%
26.23%
Table NGRCM21
600+ Beds
Web PreRegister
Web Schedule
Web Self Pay
Necessity Alert @ Scheduling
Necessity Alert @ Registration
Claims Attachment Rules
Denial Rules
Biller’s Dash Board
EMR Documentation for Claims
Direct Payer Claims
Claims Remittance Updates AR
Eligibility Transaction with Payer
EFT Transaction
2009
37
32
58
23
31
34
34
33
23
19
22
18
30
24.67%
21.33%
38.67%
15.33%
20.67%
22.67%
22.67%
22.00%
15.33%
12.67%
14.67%
12.00%
20.00%
2010
% of 150 Hospitals
35 23.33%
27 18.00%
54 36.00%
39 26.00%
51 34.00%
51 34.00%
55 36.67%
41 27.33%
15 10.00%
29 19.33%
31 20.67%
27 18.00%
46 30.67%
Source: HIMSS Analytics® Database 2011
2011
39
22
56
47
62
55
63
48
11
30
37
33
50
26.00%
14.67%
37.33%
31.33%
41.33%
36.67%
42.00%
32.00%
7.33%
20.00%
24.67%
22.00%
33.33%
©2012 HIMSS Analytics.
31
▶▶ Health Information Management
Eleven different applications comprise the Health Information
Management (HIM) IT market segment. Two of these applications,
abstracting and encoder, have reached the market saturation
threshold (at least 95 percent market penetration) in 2011. With
installation rates of at least 90 percent, chart deficiency, chart
tracking/locator and dictation are approaching market saturation
(see Table HIM1). Over time, it is expected that chart deficiency
and chart tracking/locator applications will become obsolete as the
adoption of EMR applications become more prevalent. However,
until dependence on paper documentation is completely eliminated,
these applications will maintain a healthy market presence. With
the exception of in-house transcription, all other HIM applications
demonstrated an increase from 2010 to 2011, ranging from one to
seven percent.
The HIM applications with the best growth potential are
computer-assisted coding, dictation with speech recognition and
data warehousing/mining – clinical. An increasing trend towards
more highly integrated, enterprise-wide architectures to support
business and clinical intelligence, quality and outcomes reporting
can be expected to lead to a corresponding de-emphasis of (and
decline in) specialized, department-specific data marts. There may
be significant portions of the growth reported in the adoption of
the data warehousing/mining – clinical and outcomes and quality
management applications in this market segment since they
complement the growth numbers highlighted previously in the
Financial Decision Support section of this report.
Although more than 96 percent of hospitals have adopted encoders,
upgrades or replacement of encoders as a result of ICD-10 upgrade
requirements may yield additional market activity. Outcomes and
quality also represents an application with good growth opportunity
due to the ARRA meaningful use reporting. Hospitals will continue
Table HIM1 | Health Information Management
N=4,289
2009
2010
Abstracting
95.29%
95.80%
Case Mix Management
77.15%
78.83%
Chart Deficiency
89.86%
91.00%
Chart Tracking/Locator
87.99%
89.76%
Computer-Assisted Coding
N/A
14.57%
Data Warehousing/Mining – Clinical
27.14%
32.83%
Dictation
87.62%
89.02%
Dictation with Speech Recognition
12.78%
33.62%
Encoder
95.50%
96.06%
Outcomes and Quality Management
65.96%
68.83%
In-House Transcription
74.19%
77.55%
Percentages include installed, contracted or installation in process
2011
96.78%
79.95%
92.52%
91.33%
17.09%
38.07%
91.51%
40.69%
96.69%
70.39%
76.73%
to rely heavily on dictation/ transcription processes to capture
clinical information and will continue to move toward increasingly
virtual transcription services, a model in which transcriptionists
work remotely from their homes. Standardization of the document
templates for transcribed documents will improve the ability of
hospitals to share standard patient information with one another
(see www.HealthStory.com).
Six of eleven HIM applications in this report represent
predominately replacement markets for the future. The majority of
purchase plans for computer-assisted coding, dictation, dictation
with speech recognition and encoder applications will primarily be
first-time purchases. Purchase plans for data warehousing/mining –
clinical are almost split evenly between replacements and first-time
purchases in 2011 (see Table HIM2).
As already noted, two government mandates will significantly
impact this market through 2015. The first is the requirement to
upgrade encoding systems to use ICD-10-PCS codes by October 1,
2013. The other is the requirement to report on clinical outcomes as
part of the ARRA meaningful use requirements in 2011, 2014 and
2015. Health reform, and changes in reimbursement methods
demanded by both public and private insurers, will increase the
need for hospitals to report on process and outcomes measures in
order to justify reimbursement or qualify for pay-for-performance
bonus payments. These mandates will drive increased HIM
application upgrades, if not outright system replacements.
An evaluation of hospital-type market segments for highest growth
per segment from 2010–2011 shows the following:
• Abstracting: there was one percent to a little fewer than three
percent year-over-year growth for abstracting across all hospitaltype segments. The largest growth was among critical access
hospitals (see Table HIM3)
• Case mix: all hospital segments indicated a growth of
approximately one percent. Non-critical access hospitals and
those that are part of a multi-hospital system had the greatest
growth (see Table HIM4).
• Chart deficiency: critical access and rural hospitals had the
highest increase in the past year, each with growth of slightly
more than three percent (see Table HIM5).
• Chart tracking/locator: at three percent each, rural and critical
access demonstrated the highest increase for the implementation
of this application from 2010 to 2011. There was a very slight
decrease in the use of this technology at academic medical
centers (see Table HIM6).
Table hiM2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Abstracting
60
98.36%
Case Mix Management
35
92.11%
Chart Deficiency
58
95.08%
Chart Tracking/Locator
56
93.33%
Computer-Assisted Coding
0
0.00%
Data Warehousing/Mining – Clinical
7
46.67%
Dictation
12
25.53%
Dictation with Speech Recognition
7
16.28%
Encoder
7
38.89%
Outcomes and Quality Management
9
75.00%
In-House Transcription
17
65.38%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
32 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
# of Hospitals Planning
to Purchase Software
for the First Time
1
3
3
4
35
8
35
36
11
3
9
% of Hospitals Planning
to Purchase Software
for the First Time
1.64%
7.89%
4.92%
6.67%
100.00%
53.33%
74.47%
83.72%
61.11%
25.00%
34.62%
N = Total Number of
Hospitals Planning
61
38
61
60
35
15
47
43
18
12
26
▶▶ Health Information Management con tinued
• Computer-assisted coding: academic medical centers
demonstrated the largest year-over-year growth at slightly more
than three percent. All other segments reported growth ranging
from two to three percent (see Table HIM7).
• Data warehousing-clinical: growth a number of segments was
greater than six percent. These include academic medical centers,
general medical/surgical, hospitals from multi-hospital systems,
non-critical access hospitals and urban hospitals at more than
six percent (see Table HIM8).
• Dictation: the greatest growth was in the rural and critical
access hospital segments (nearly four percent). All other hospital
segments reported an increase ranging from approximately one
percent to three percent (see Table HIM9).
• Dictation with speech recognition: general medical/surgical
hospitals demonstrated the highest year-over-year growth at more
than eight percent. The urban segment is the only other segment
to demonstrate an increase of more than eight percent. All other
segments reported an increase between three and seven percent
(see Table HIM10).
• Encoder: the academic medical center has reached full market
saturation. Critical access hospitals and rural hospitals are the
only hospital segments that have not exceeded 90 percent
adoption. Growth across most market segments was less than
two percent (see Table HIM11).
• Outcomes and quality management: this segment experienced
one percent to two percent growth from 2010 to 2011 for all
segments. Critical access and rural hospitals had the highest
growth at slightly more than two percent (see Table HIM12).
• In-house transcription: most of the segments demonstrated slight
decline from 2010 to 2011, with the exception of critical access
hospitals and other non-general medical/surgical hospitals (see
Table HIM13). Academic medical centers reported a decline of
more than five percent.
Table HIM3 | Abstracting
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
190
3,897
2,477
1,610
1,001
3,086
876
3,211
2,532
1,555
4,087
Percent
98.96%
95.12%
98.80%
90.35%
86.67%
98.47%
86.99%
97.84%
97.91%
91.31%
95.29%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
190
3,919
2,480
1,629
1,019
3,090
891
3,218
2,534
1,575
4,109
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
181
3,200
2,181
1,200
669
2,712
590
2,791
2,214
1,167
3,381
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,712
2,444
1,459
854
3,049
755
3,148
2,475
1,428
3,903
Percent
98.96%
95.66%
98.92%
91.41%
88.23%
98.60%
88.48%
98.05%
97.99%
92.48%
95.80%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,960
2,486
1,665
1,049
3,102
914
3,237
2,548
1,603
4,151
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
182
3,247
2,210
1,219
675
2,754
598
2,831
2,248
1,181
3,429
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,777
2,460
1,508
895
3,073
790
3,178
2,501
1,467
3,968
Percent
99.48%
96.66%
99.16%
93.43%
90.82%
98.98%
90.76%
98.63%
98.53%
94.13%
96.78%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM4 | Case Mix Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
178
3,131
2,149
1,160
636
2,673
563
2,746
2,173
1,136
3,309
Percent
92.71%
76.42%
85.72%
65.10%
55.06%
85.29%
55.91%
83.67%
84.03%
66.71%
77.15%
2010
Percent
94.27%
78.11%
87.00%
67.34%
57.92%
86.53%
58.59%
85.04%
85.61%
68.53%
78.83%
2011
Percent
94.79%
79.25%
88.15%
68.41%
58.44%
87.87%
59.38%
86.26%
86.93%
69.35%
79.95%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM5 | Chart Deficiency
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
191
3,663
2,428
1,426
821
3,033
725
3,129
2,463
1,391
3,854
Percent
99.48%
89.41%
96.85%
80.02%
71.08%
96.78%
72.00%
95.34%
95.24%
81.68%
89.86%
2010
Percent
99.48%
90.60%
97.49%
81.87%
73.94%
97.29%
74.98%
95.92%
95.71%
83.85%
91.00%
2011
Source: HIMSS Analytics® Database 2011
Percent
99.48%
92.19%
98.13%
84.62%
77.49%
98.05%
78.45%
96.83%
96.71%
86.14%
92.52%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
33
▶▶ Health Information Management con tinued
Table HIM6 | Chart Tracking/Locator
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
190
3,584
2,393
1,381
786
2,988
700
3,074
2,426
1,348
3,774
Percent
98.96%
87.48%
95.45%
77.50%
68.05%
95.34%
69.51%
93.66%
93.81%
79.15%
87.99%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
190
3,660
2,418
1,432
836
3,014
740
3,110
2,457
1,393
3,850
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
43
582
425
200
123
502
99
526
386
239
625
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
102
1,306
929
479
210
1,198
177
1,231
1,015
393
1,408
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
3,630
2,384
1,434
931
2,887
819
2,999
2,353
1,465
3,818
Percent
98.96%
89.33%
96.45%
80.36%
72.38%
96.17%
73.49%
94.76%
95.01%
81.80%
89.76%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,728
2,432
1,485
876
3,041
775
3,142
2,485
1,432
3,917
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
50
683
486
247
148
585
114
619
461
272
733
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
115
1,518
1,095
538
232
1,401
200
1,433
1,185
448
1,633
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,736
2,433
1,492
974
2,951
858
3,067
2,417
1,508
3,925
Percent
98.44%
90.99%
97.01%
83.33%
75.84%
97.03%
76.96%
95.73%
96.09%
84.09%
91.33%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM7 | Computer-Assisted Coding
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
N/A
N/A
N/A N/A
N/A
N/A N/A N/A N/A N/A N/A
Percent
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
2010
Percent
22.40%
14.21%
16.95%
11.22%
10.65%
16.02%
9.83%
16.03%
14.93%
14.03%
14.57%
2011
Percent
26.04%
16.67%
19.39%
13.86%
12.81%
18.67%
11.32%
18.86%
17.83%
15.97%
17.09%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM8 | Data Warehousing/Mining – Clinical
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
89
1,075
774
390
157
1,007
129
1,035
837
327
1,164
Percent
46.35%
26.24%
30.87%
21.89%
13.59%
32.13%
12.81%
31.54%
32.37%
19.20%
27.14%
2010
Percent
53.13%
31.88%
37.06%
26.88%
18.18%
38.23%
17.58%
37.51%
39.25%
23.08%
32.83%
2011
Percent
59.90%
37.05%
43.68%
30.19%
20.09%
44.70%
19.86%
43.66%
45.82%
26.31%
38.07%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM9 | Dictation
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
186
3,572
2,373
1,385
885
2,873
783
2,975
2,350
1,408
3,758
Percent
96.88%
87.19%
94.65%
77.72%
76.62%
91.67%
77.76%
90.65%
90.87%
82.68%
87.62%
2010
34 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
97.92%
88.60%
95.09%
80.47%
80.61%
92.12%
81.33%
91.38%
90.99%
86.02%
89.02%
2011
Percent
98.44%
91.19%
97.05%
83.73%
84.33%
94.16%
85.20%
93.45%
93.46%
88.55%
91.51%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Health Information Management con tinued
Table HIM10 | Dictation with Speech Recognition
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
91
1,005
768
328
158
938
124
972
779
317
548
Percent
47.40%
24.53%
30.63%
18.41%
13.68%
29.93%
12.31%
29.62%
30.12%
18.61%
12.78%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
121
1,321
1,026
416
193
1,249
158
1,284
1,030
412
1,442
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,928
2,496
1,624
1,013
3,107
888
3,232
2,553
1,567
4,120
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
165
2,787
1,952
1,000
468
2,484
429
2,523
2,086
866
2,952
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
148
3,178
2,000
1,326
900
2,426
802
2,524
1,983
1,343
3,326
Percent
63.02%
32.24%
40.93%
23.34%
16.71%
39.85%
15.69%
39.12%
39.83%
24.19%
33.62%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
136
1,609
1,244
501
267
1,478
197
1,548
1,221
524
1,745
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,955
2,498
1,649
1,031
3,116
906
3,241
2,558
1,589
4,147
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
167
2,852
1,986
1,033
494
2,525
451
2,568
2,123
896
3,019
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
138
3,153
1,962
1,329
902
2,389
800
2,491
1,977
1,314
3,291
Percent
70.83%
39.27%
49.62%
28.11%
23.12%
47.16%
19.56%
47.17%
47.22%
30.77%
40.69%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM11 | Encoder
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
3,904
2,491
1,605
996
3,100
872
3,224
2,546
1,550
4,096
Percent
100.00%
95.29%
99.36%
90.07%
86.23%
98.92%
86.59%
98.23%
98.45%
91.02%
95.50%
2010
Percent
100.00%
95.88%
99.56%
91.13%
87.71%
99.14%
88.18%
98.48%
98.72%
92.01%
96.06%
2011
Percent
100.0%
96.53%
99.64%
92.54%
89.26%
99.43%
89.97%
98.75%
98.92%
93.31%
96.69%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM12 | Outcomes and Quality Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
159
2,670
1,900
929
417
2,412
395
2,434
1,996
833
2,829
Percent
82.81%
65.17%
75.79%
52.13%
36.10%
76.96%
39.23%
74.16%
77.18%
48.91%
65.96%
2010
Percent
85.94%
68.03%
77.86%
56.12%
40.52%
79.26%
42.60%
76.87%
80.67%
50.85%
68.83%
2011
Percent
86.98%
69.61%
79.22%
57.97%
42.77%
80.57%
44.79%
78.24%
82.10%
52.61%
70.39%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table HIM13 | In-House Transcription
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
142
3,040
1,971
1,211
833
2,349
739
2,443
1,919
1,263
3,182
Percent
73.96%
74.20%
78.62%
67.96%
72.12%
74.95%
73.39%
74.44%
74.21%
74.16%
74.19%
2010
Percent
77.08%
77.57%
79.78%
74.41%
77.92%
77.41%
79.64%
76.90%
76.68%
78.86%
77.55%
2011
Source: HIMSS Analytics® Database 2011
Percent
71.88%
76.96%
78.26%
74.58%
78.10%
76.23%
79.44%
75.90%
76.45%
77.16%
76.73%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
35
▶▶ Health Information Management con tinued
The analysis of this HIM market by bed-size segments from 2010
to 2011 showed dictation with speech recognition had the highest
year-over-year growth across all bed segments. The analysis also
indicated the following (see Tables HIM14–HIM20):
• 0–100 beds: dictation with speech recognition had the highest
growth in this segment at slightly more than five percent. Data
warehouse/mining – clinical and dictation each had growth of
more than three percent (see Table HIM14).
• 101–200 beds: dictation with speech recognition and data
warehousing/mining – clinical each showed growth of more
than seven percent in the past year. Use of in-house transcription
decreased by more than two percent (see Table HIM15).
• 201–300 beds: dictation with speech recognition showed the
highest growth at slightly under 10 percent followed by data
warehouse/mining – clinical at more than eight percent. Chart
tracking/locater and in-house transcription are the only two
applications to report a decrease (see Table HIM16).
Table HIM14
Table HIM17
0–100 Beds
2009
2010
2011
% of 2,181 hospitals
91.33% 2,013 92.30% 2,050 93.99%
65.61% 1,483 68.00% 1,508 69.14%
81.11% 1,814 83.17% 1,875 85.97%
79.00% 1,780 81.61% 1,844 84.55%
0.00% 250 11.46% 295 13.53%
18.57% 502 23.02% 579 26.55%
79.83% 1,784 81.80% 1,859 85.24%
15.86% 429 19.67% 542 24.85%
91.43% 2,018 92.53% 2,045 93.76%
52.09% 1,216 55.75% 1,256 57.59%
71.39% 1,675 76.80% 1,686 77.30%
Abstracting
1,992
Case Mix Management
1,431
Chart Deficiency
1,769
Chart Tracking/Locator
1,723
Computer-Assisted Coding
N/A
Data Warehousing/Mining – Clinical 405
Dictation
1,741
Dictation with Speech Recognition 346
Encoder
1,994
Outcomes and Quality Management 1,136
In-House Transcription
1,557
Table HIM15
2009
815
723
805
793
N/A 256
780
232
818
645
626
99.15%
87.96%
97.93%
96.47%
0.00%
31.14%
94.89%
28.22%
99.51%
78.47%
76.16%
2010
% of 822 hospitals
815 99.15%
736 89.54%
806 98.05%
802 97.57%
124 15.09%
304 36.98%
784 95.38%
327 39.78%
818 99.51%
664 80.78%
625 76.03%
2011
818
743
810
808
140
366
800
390
818
671
605
99.51%
90.39%
98.54%
98.30%
17.03%
44.53%
97.32%
47.45%
99.51%
81.63%
73.60%
Table HIM16
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
2009
325
284
327
325
N/A
130
315
122
327
261
253
99.09%
86.59%
99.70%
99.09%
0.00%
39.63%
96.04%
37.20%
99.70%
79.57%
77.13%
2010
% of 328 hospitals
325 99.09%
288 87.80%
328 100.00%
326 99.39%
66 20.12%
153 46.65%
321 97.87%
175 53.35%
327 99.70%
269 82.01%
255 77.74%
2011
326 99.39%
296 90.24%
328 100.00%
325 99.09%
75 22.87%
176 53.66%
325 99.09%
209 63.72%
327 99.70%
276 84.15%
248 75.61%
401–500 Beds
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
2009
182 100.00%
167 91.76%
182 100.00%
177 97.25%
N/A
0.00%
76 41.76%
178 97.80%
76 41.76%
182 100.00%
145 79.67%
136 74.73%
2010
% of 182 hospitals
182 100.00%
168 92.31%
182 100.00%
177 97.25%
36 19.78%
86 47.25%
179 98.35%
94 51.65%
182 100.00%
148 81.32%
142 78.02%
2011
182 100.00%
169 92.86%
182 100.00%
177 97.25%
42 23.08%
94 51.65%
180 98.90%
115 63.19%
182 100.00%
154 84.62%
137 75.27%
Table HIM19
201–300 Beds
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
301–400 Beds
Table HIM18
101–200 Beds
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
• 301–400 beds: the greatest grown in this segment was for
dictation with speech recognition (more than 10 percent).
Use of both in-house transcription and chart tracking/locator
declined in the past year (see Table HIM17).
• 401–500 beds: at slightly more than 11 percent, dictation with
speech recognition had the greatest growth from 2010 to 2011.
Use of in-house transcription decreased by more than two
percent (see Table HIM18).
• 501–600 beds: dictation with speech recognition showed
growth of more than six percent in the past year. Use of
in-house transcription, outcomes and quality management,
dictation and case mix management all declined in the past
year (see Table HIM19).
• 600+ beds: dictation with speech recognition indicated
the most increase in implementation from 2010 to 2011 at
10 percent; use of case mix management decreased by four
percent (see Table HIM20).
2009
502
456
499
491
N/A
174
480
182
503
412
399
99.60%
90.48%
99.01%
97.42%
0.00%
34.52%
95.24%
36.11%
99.80%
81.75%
79.17%
2010
% of 504 hospitals
503 99.80%
455 90.28%
501 99.40%
497 98.61%
92 18.25%
215 42.66%
486 96.43%
245 48.61%
503 99.80%
416 82.54%
402 79.76%
2011
503
462
501
496
112
258
496
294
503
423
395
99.80%
91.67%
99.40%
98.41%
22.22%
51.19%
98.41%
58.33%
99.80%
83.93%
78.37%
36 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
501–600 Beds
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
2009
121 99.18%
108 88.52%
122 100.00%
118 96.72%
N/A
0.00%
47 38.52%
120 98.36%
58 47.54%
122 100.00%
102 83.61%
97 79.51%
2010
% of 122 hospitals
121 99.18%
109 89.34%
122 100.00%
121 99.18%
24 19.67%
56 45.90%
119 97.54%
76 62.30%
122 100.00%
104 85.25%
104 85.25%
2011
122 100.00%
108 88.52%
122 100.00%
121 99.18%
27 22.13%
60 49.18%
118 96.72%
84 68.85%
122 100.00%
101 82.79%
97 79.51%
▶▶ Health Information Management con tinued
Table HIM20
600+ Beds
Abstracting
Case Mix Management
Chart Deficiency
Chart Tracking/Locator
Computer-Assisted Coding
Data Warehousing/Mining – Clinical
Dictation
Dictation with Speech Recognition
Encoder
Outcomes and Quality Management
In-House Transcription
Table HIM22
2009
150 100.00%
140 93.33%
150 100.00%
147 98.00%
N/A
0.00%
76 50.67%
144 96.00%
80 53.33%
150 100.00%
128 85.33%
114 76.00%
2010
% of 150 hospitals
150 100.00%
149 99.33%
150 100.00%
147 98.00%
33 22.00%
92 61.33%
145 96.67%
96 64.00%
150 100.00%
135 90.00%
123 82.00%
2011
150 100.00%
143 95.33%
150 100.00%
146 97.33%
42 28.00%
100 66.67%
147 98.00%
111 74.00%
150 100.00%
138 92.00%
123 82.00%
Evaluating the contracting activity for HIM applications, the
majority of contracts signed for computer-assisted coding and
dictation with speech recognition occurred between 2005 and 2011,
showing that these applications are beginning to become more
accepted in the market. More than half of the legacy HIM
applications (abstracting, case mix, chart deficiency, chart locator/
tracking, dictation, encoding, outcomes and quality management
and in-house transcription) had the highest contracting activity from
1995 to 2004. It is likely that chart deficiency and chart locator/
tracking will be displaced as more hospitals continue to complete
their EMR system implementations. (Table HIM6 shows there was
a slight decrease in this application in the Academic Medical Center
market.) Encoding upgrade activity will generate significant
contracting activity through the next few years in anticipation of the
transition to ICD-10. The data warehousing/mining – clinical and
dictation with speech recognition applications have had their highest
contracting activity since 2000 (see Tables HIM21–HIM24).
Table HIM21
2011
Abstracting
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Case Mix Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Chart Deficiency
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
147
269
815
809
837
2,877
2,877
2,877
2,877
2,877
2,877
2,877
5.11%
9.35%
28.33%
28.12%
29.09%
100.00%
134
298
613
750
574
2,369
2,369
2,369
2,369
2,369
2,369
2,369
5.66%
12.58%
25.88%
31.66%
24.23%
100.00%
83
246
665
903
846
2,743
2,743
2,743
2,743
2,743
2,743
2,743
3.03%
8.97%
24.24%
32.92%
30.84%
100.00%
2011
Chart Tracking/Locator
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Computer-Assisted Coding
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Data Warehousing/Mining – Clinical
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
88
247
698
870
773
2,676
2,676
2,676
2,676
2,676
2,676
2,676
3.29%
9.23%
26.08%
32.51%
28.89%
100.00%
1
1
5
13
31
51
51
51
51
51
51
51
1.96%
1.96%
9.80%
25.49%
60.78%
100.00%
5
102
55
243
325
730
730
730
730
730
730
730
0.68%
13.97%
7.53%
33.29%
44.52%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
32
85
300
693
752
1,862
1,862
1,862
1,862
1,862
1,862
1,862
1.72%
4.49%
15.86%
36.63%
39.75%
100.00%
0 7
7
122
401
537
537 537
537
537
537
537
0.00%
1.30%
1.30%
22.72%
74.67%
100.00%
239
334
771
580
348
2,272
2,272
2,272
2,272
2,272
2,272
2,272
10.52%
14.70%
33.93%
25.53%
15.32%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
41
164
479
659
458
1,801
1,801
1,801
1,801
1,801
1,801
1,801
2.28%
9.11%
26.60%
36.39%
25.43%
100.00%
39
187
372
526
532
1,656
1,656
1,656
1,656
1,656
1,656
1,656
2.36%
11.29%
22.46%
31.76%
32.13%
100.00%
Table HIM23
2011
Dictation
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Dictation with Speech Recognition
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Encoder
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table HIM24
2011
Outcomes and Quality Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
In-House Transcription
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
37
▶▶ Health Information Management con tinued
Market Drivers/Future Outlook
The HIM Department IT applications market will be significantly
impacted through 2015 by several factors:
• Preparations for conversation to ICD-10 by the later part of 2013.
This includes mapping several applications that rely on encoded
data to the new ICD-10 formats (also significantly affecting
interfaces) by October 1, 2013.
• Negotiating the contractual commitments between hospitals and
vendors for federal, state and other regulatory upgrades relative to
ICD-10 encoding upgrades.
• Increased demands from the government (ARRA) and payers for
reporting quality and outcomes data.
• Increased conversion of the medical record from paper to a
digital format; the mixed format providing some special
challenges for security and operational management, as well as
patient care challenges.
• Increase focus on quality outcomes for participating in outcomesbased reimbursement models (e.g., pay for performance, ACOs).
• Increased adoption of nomenclature coding standards such as
SNOMED and LOINC.
• Consistent with the above, increasingly stringent claims coding
and supporting documentation requirements mandated by federal
regulations and public and private reimbursement requirements.
• The introduction of new software technologies to analyze,
structure and codify transcribed free text.
• The drive to reduce transcription costs by implementing speech
recognition software that will require cooperation of key medical
staff users such as in radiology, pathology and emergence
medicine.
• Continued constraints in capital markets and intense internal
competition for the capital required to acquire or upgrade HIM
applications.
• Continued implementation of EMR applications which may make
obsolete some of these applications (chart tracking in particular
as evidenced by academic medical centers this year).
• The increasing trend towards more highly integrated, enterprisewide architectures to support business and clinical intelligence,
quality and outcomes reporting, and a corresponding de-emphasis
of, and decline in, specialized, department-specific data marts.
▶▶ Document Management/Electronic Forms
The healthcare IT document management and electronic forms
application market in 2011 has seen steady growth since 2009 and
has the potential to continue growing in the next few years (see
Table DMEF1). Both document management and electronic forms
management demonstrated growth of more than four percent from
2010 to 2011. These applications will continue to be an important
component of the EMR environment at hospitals as they move
toward paperless environments. Technologies which can extract
discrete data elements from these document management and
electronic forms management solutions and reformat them in a
manner suitable for analysis, research and reporting will also see
market adoption increases over the next five years as health systems
reach for a higher level of cost and quality analytics.
A majority of hospitals purchasing electronic forms management
applications in 2011 did so for the first time. Conversely,
approximately two thirds of planned purchases for document
management will be among hospitals that are planning to replace
their current solution (see Table DMEF2).
Table DME F1 | Document Management and Electronic Forms
N=4,289
2009
2010
Document Management
61.74%
67.27%
Electronic Forms Management
42.88%
51.06%
Percentage include installed, contracted or installation in process
2011
71.58%
56.05%
An evaluation of hospital market segments for document
management and electronic forms management applications in 2011
shows academic medical centers have the highest adoption rate for
both applications. The data also shows:
• Document management: growth for all market segments was
between three and five percent. Growth was greatest among
critical access hospitals (see Table DMEF3).
• Electronic forms management: critical access hospitals also
demonstrated the largest growth for electronic forms management
at more than six percent. Growth for all remaining market
segments was between four and six percent (see Table DMEF4).
The analysis of the document management and electronic forms
management market in 2011 by bed-size segments provides additional
insight into this application environment (see Tables DMEF5–DMEF11).
The increase in adoption for both technologies grew in every bed-size
category. In our opinion, the adoption of these technologies, particularly
electronic forms management, continues to be heavily influenced by
the increases in EMR adoption seen across all bed-size ranges.
While, historically, the adoption of document management grew
faster among larger hospitals, the rate of adoption has slowed for
larger hospitals, while the rate of adoption for small and mediumsized hospitals is increasing year after year. This may be attributed
to the fact that as the price of these solutions has declined, they have
Table DME F 2 | 2010
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Document Management
49
69.01%
Electronic Forms Management
6
16.67%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
38 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
# of Hospitals Planning
to Purchase Software
for the First Time
22
30
% of Hospitals Planning
to Purchase Software
for the First Time
30.99%
83.33%
N = Total Number of
Hospitals Planning
71
36
▶▶ Document Management/Electronic Forms con tinued
Table DME F 3 | Document Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
157
2,491
1,688
960
467
2,181
421
2,227
1,776
872
2,648
Percent
81.77%
60.80%
67.33%
53.87%
40.43%
69.59%
41.81%
67.85%
68.68%
51.20%
61.74%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
161
2,724
1,839
1,046
540
2,345
483
2,402
1,913
972
2,885
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
129
2,061
1,396
794
444
1,746
378
1,812
1,417
773
2,190
Percent
83.85%
66.49%
73.35%
58.70%
46.75%
74.82%
47.96%
73.19%
73.98%
57.08%
67.27%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
168
2,902
1,950
1,120
598
2,472
532
2,538
2,023
1,047
3,070
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
139
2,265
1,511
893
518
1,886
435
1,969
1,539
865
2,404
Percent
87.50%
70.83%
77.78%
62.85%
51.77%
78.88%
52.83%
77.33%
78.23%
61.48%
71.58%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table DME F4 | Electronic Forms Management
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
120
1,719
1,147
692
366
1,473
309
1,530
1,183
656
1,839
Percent
62.50%
41.96%
45.75%
38.83%
31.69%
47.00%
30.69%
46.62%
45.75%
38.52%
42.88%
2010
become more affordable to smaller institutions. The data shows that
the highest growth rates between 2010 and 2011 were in bed-range
categories fewer than 300 beds.
• 0–100 beds: growth for these applications in this bed segment
was between four and five percent (see Table DMEF5).
• 101–200 beds: document management demonstrated a growth of
more than four percent from 2010 to 2011, while electronic forms
management adoption grew by nearly four percent (see Table DMEF6).
• 201–300 beds: both document management and electronic forms
management application indicated growth of approximately six
percent (see Table DMEF7).
• 301–400 beds: nearly five percent growth was reported for
electronic forms management in this segment from 2010 to 2011,
while document management’s growth was nearly four percent
(see Table DMEF8).
• 401–500 beds: document management adoption has increased by
more than two percent in 2011 and the market is close to
saturation with a market penetration of 89 percent (see Table
DMEF9). Electronic forms management demonstrated an
increase of more than four percent in the past year.
• 501–600 beds: both document management and electronic forms
management indicated an increase in adoption of nearly two
percent 2010 to 2011 (see Table DMEF10).
• Over 600 beds: electronic forms management’s adoption grew
from 2010 to 2011 at approximately five percent, while document
management also indicated growth of six percent (see Table DMEF11).
Percent
67.19%
50.31%
55.68%
44.56%
38.44%
55.71%
37.54%
55.21%
54.80%
45.39%
51.06%
2011
Percent
72.40%
55.28%
60.27%
50.11%
44.85%
60.18%
43.20%
59.99%
59.51%
50.79%
56.05%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table DME F5
0–100 Beds
Document Management
Electronic Forms Management
2009
1,118
772
2010
2011
% of 2,181 hospitals
51.26% 1,246 57.13% 1,336 61.26%
35.40% 919 42.14% 1,036 47.50%
Table DME F6
101–200 Beds
Document Management
Electronic Forms Management
2009
546
387
2010
2011
% of 822 hospitals
66.42% 593 72.14% 630 76.64%
47.08% 463 56.33% 494 60.10%
Table DME F 7
201–300 Beds
Document Management
Electronic Forms Management
2009
356
240
2010
2011
% of 504 hospitals
70.63% 393 77.98% 424 84.13%
47.62% 300 59.52% 332 65.87%
Table DME F 8
301–400 Beds
Document Management
Electronic Forms Management
2009
256
178
2010
2011
% of 328 hospitals
78.05% 264 80.49% 276 84.15%
54.27% 207 63.11% 223 67.99%
Table DME F 9
401–500 Beds
Document Management
Electronic Forms Management
2009
148
109
2010
2011
% of 182 hospitals
81.32% 158 86.81% 162 89.01%
59.89% 123 67.58% 131 71.98%
Table DME F10
501–600 Beds
Document Management
Electronic Forms Management
2009
100
74
2010
2011
% of 122 hospitals
81.97% 102 83.61% 104 85.25%
60.66%
84 68.85%
86 70.49%
Table DME F11
600+ Beds
Document Management
Electronic Forms Management
2009
124
79
2010
2011
% of 150 hospitals
82.67% 129 86.00% 138 92.00%
52.67%
94 62.67% 102 68.00%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
39
▶▶ Document Management/Electronic Forms con tinued
A review of temporal contract signing for document management
applications in 2011 shows that more than half of the contracting
activity took place from 2005 to 2011 (see Table DMEF12). We
believe this can be attributed to the pursuit of these technologies as
an initial step in increasing process efficiencies by improving access
to information by electronic formats, especially with regard to
patient medical record information.
Table DME F12
2011
Document Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Electronic Forms Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
3
37
73
360
732
1,205
1,199
1,199
1,199
1,199
1,199
1,205
0.25%
3.09%
6.09%
30.03%
61.05%
100.00%
1
26
44
282
426
779
779
779
779
779
779
779
0.13%
3.34%
5.65%
36.20%
54.69%
100.00%
Market Drivers/Future Outlook
The document management IT application market has been and
will continue to be impacted through 2015 by:
• Access to capital, which could impact the excellent growth rates
seen for most document management applications over the last
three years.
• Compliance with ARRA meaningful use criteria, which is
expected to drive more rapid adoption of both document
management and electronic forms management to reduce
dependency on paper and enhance the ability to capture more
discrete data for analysis and submission to payers.
• The need to remove paper from the care delivery and operations
processes to improve hospital efficiency.
• The need to eliminate or significantly reduce paper document
storage and filing processes.
• The need to improve access to information that is still captured
on paper documents.
• The need to make medical record information more secure.
▶▶ Nursing Department Environment
The number of nurse IT applications tracked in past annual reports
has grown, as HIMSS Analytics began collecting data for infection
surveillance system, medication reconciliation and nurse call
system. These new applications were added to electronic medication
administration record (EMAR), patient acuity (formerly nurse
acuity), nursing documentation and nurse staffing/scheduling.
Table N A1 | Nursing Department Applications
N=4,289
2009
2010
Electronic Medication Administration
Record (EMAR)
64.44%
72.16%
Infection Surveillance System*
0.00%
23.01%
Medication Reconciliation*
0.00%
36.61%
Nurse Acuity
26.04%
28.91%
Nurse Call System*
0.00%
36.65%
Nurse Staffing/Scheduling
62.35%
64.72%
Nursing Documentation
72.74%
77.50%
Percentage include installed, contracted or installation in process
*Application is tracked for the first time in 2010.
2011
78.90%
29.54%
50.03%
30.59%
46.54%
64.82%
82.37%
The nursing IT application market that demonstrated the highest
growth from 2010 to 2011 was medication reconciliation, at more
than 13 percent. The growth for nurse call system was also high, at
nine percent. All other nursing applications demonstrated growth
ranging from less than one percent (nurse staffing/scheduling) to
seven percent (see Table NA1).
For most of the nursing applications in this report, more than
half of planned purchases will be to replace existing solutions.
EMAR is the exception, as slightly more than half of the planned
purchases are regarded as first-time purchases (see Table NA2).
It is likely that the trend in use of EMAR solutions will continue,
driven by goals of patient safety and reduction of medication errors.
We believe the need towards integrated software solutions is a
driver for this change.
Table N A 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Electronic Medication Administration Record (EMAR)
53
44.54%
Infection Surveillance System
38
66.67%
Medication Reconciliation
46
50.55%
Nurse Acuity
44
86.27%
Nurse Call System
23
82.14%
Nurse Staffing/Scheduling
16
55.17%
Nursing Documentation
54
55.10%
Replacing = Statuses of Live & Operational, Contracted/Not Yet Installed and Installation In Process
First time = Status of Not Automated
40 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
# of Hospitals Planning
to Purchase Software
for the First Time
66
19
45
7
5
13
44
% of Hospitals Planning
to Purchase Software
for the First Time
55.46%
33.33%
49.45%
13.73%
17.86%
44.83%
44.90%
N = Total Number of
Hospitals Planning
119
57
91
51
28
29
98
▶▶ Nursing Department Environment con tinued
An evaluation of hospital-type market segments in 2011 shows the
following trends:
• EMAR: all hospital-type segments continue to demonstrate slight
to strong growth. Double-digit growth is expected among rural
hospitals, critical access hospitals and hospitals that are part of a
single hospital system. Academic medical centers were the
segment with the lowest growth, at slightly under two percent.
This is the only area that is approaching market saturation (see
Table NA3).
• Infection surveillance systems: academic medical centers showed
the highest increase in the use of infection surveillance systems at
more than 14 percent. This is not surprising, as academic medical
centers have always been early adopters of new technology. All
other segments indicated a growth ranging from four to seven
percent (see Table NA4).
• Medication reconciliation: another new addition to this report,
this application indicated a growth of more than 10 percent across
all hospital types. Single hospital systems showed the greatest
increase from 2010 at more than 17 percent (see Table NA5).
• Nurse call system: included for the first time in this report,
this solution’s growth from 2010 was highest for non-academic
hospitals (12 percent), followed by general medical/surgical
facilities at 11 percent. All other segments showed increase
ranging from six percent to ten percent (see Table NA6).
• Nurse staffing/scheduling: overall, the growth from 2010 to
2011 for this application is slight. Single hospital systems had the
greatest growth of slightly less than two percent. Hospitals from
multi-system organizations, critical access hospitals and general
medical/surgical facilities indicated a slight decrease from 2010
(see Table NA7).
• Nursing documentation: rural hospitals and critical access
hospitals indicated an increase of more than eight percent from
2010 to 2011, followed by single hospital systems at seven percent
(see Table NA8).
• Patient acuity: growth for this application ranged from one
to two percent across all market segments. The largest growth
was among critical access hospitals, at nearly three percent.
(see Table NA9).
Table N A 3 | Electronic Medication Administration Record (EMAR)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
161
2,603
1,785
979
494
2,270
399
2,365
1,870
894
2,764
Percent
83.85%
63.53%
71.20%
54.94%
42.77%
72.43%
39.62%
72.06%
72.31%
52.50%
64.44%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
175
2,920
1,950
1,145
618
2,477
540
2,555
2,027
1,068
3,095
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
73
914
700
287
139
848
132
855
716
271
987
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
107
1,463
1,062
508
311
1,259
273
1,297
1,013
557
1,570
Percent
91.15%
71.27%
77.78%
64.25%
53.51%
79.04%
53.62%
77.85%
78.38%
62.71%
72.16%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
178
3,206
2,102
1,282
756
2,628
662
2,722
2,130
1,254
3,384
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
100
1,167
882
385
192
1,075
173
1094
883
384
1,267
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
136
2,010
1,398
748
470
1,676
408
1,738
1,289
857
2,146
Percent
92.71%
78.25%
83.85%
71.94%
65.45%
83.85%
65.74%
82.94%
82.37%
73.63%
78.90%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table N A 4 | Infection Surveillance System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Percent
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
2010
Percent
38.02%
22.31%
27.92%
16.11%
12.03%
27.06%
13.11%
26.05%
27.69%
15.91%
23.01%
2011
Percent
52.08%
28.48%
35.18%
21.60%
16.62%
34.30%
17.18%
33.33%
34.15%
22.55%
29.54%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table N A5 | Medication Reconciliation
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Percent
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
2010
Percent
55.73%
35.71%
42.36%
28.51%
26.93%
40.17%
27.11%
39.52%
39.17%
32.71%
36.61%
2011
Source: HIMSS Analytics® Database 2011
Percent
70.83%
49.06%
55.76%
41.98%
40.69%
53.48%
40.52%
52.96%
49.85%
50.32%
50.03%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
41
▶▶ Nursing Department Environment con tinued
Table N A6 | Nurse Call System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Percent
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
107
1,465
1,032
540
318
1,254
267
1,305
990
582
1,572
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
178
2,598
1,931
845
416
2,360
363
2,413
1,920
856
2,776
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
182
3,142
2,085
1,239
705
2,619
609
2,715
2,133
1,191
0
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
88
1,152
834
406
159
1,081
151
1,089
849
391
1,240
Percent
55.73%
33.76%
41.16%
30.30%
27.53%
40.01%
26.51%
39.76%
38.28%
34.17%
36.65%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
118
1,878
1,313
683
409
1,587
358
1,638
1,270
726
1,996
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
179
2,601
1,930
850
414
2,366
364
2,416
1,895
885
2,780
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
3,350
2,178
1,355
806
2,727
690
2,843
2,217
1,316
0
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
92
1,220
868
444
189
1,123
170
1,142
883
429
1,312
Percent
61.46%
45.84%
52.37%
38.33%
35.41%
50.64%
35.55%
49.91%
49.11%
42.63%
46.54%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table N A7 | Nurse Staffing/Scheduling
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
175
2,499
1,885
789
379
2,295
321
2,353
1,861
813
2,674
Percent
91.15%
61.00%
75.19%
44.28%
32.81%
73.23%
31.88%
71.69%
71.96%
47.74%
62.35%
2010
Percent
92.71%
63.41%
77.02%
47.42%
36.02%
75.30%
36.05%
73.52%
74.25%
50.26%
64.72%
2011
Percent
93.23%
63.49%
76.98%
47.70%
35.84%
75.49%
36.15%
73.61%
73.28%
51.97%
64.82%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table N A 8 | Nursing Documentation
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
173
2,947
1,993
1,127
614
2,506
520
2,600
2039
1,081
0
Percent
90.10%
73.91%
79.50%
63.24%
53.16%
79.96%
51.64%
79.22%
78.85%
63.48%
0.00%
2010
Percent
94.79%
76.69%
83.17%
69.53%
61.04%
83.57%
60.48%
82.72%
82.48%
69.94%
0.00%
2011
Percent
95.31%
81.77%
86.88%
76.04%
69.78%
87.01%
68.52%
86.62%
85.73%
77.28%
0.00%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table N A9 | Patient Acuity
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
74
1,043
763
354
128
989
109
1,008
778
339
1,117
Percent
38.54%
25.46%
30.43%
19.87%
11.08%
31.56%
10.82%
30.71%
30.09%
19.91%
26.04%
2010
42 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
45.83%
28.12%
33.27%
22.78%
13.77%
34.49%
15.00%
33.18%
32.83%
22.96%
28.91%
2011
Percent
47.92%
29.78%
34.62%
24.92%
16.36%
35.83%
16.88%
34.80%
34.15%
25.19%
30.59%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Nursing Department Environment con tinued
The analysis of this market by bed size activity from 2010 to 2011
provided the following observations (see Tables NA10–NA16):
• 0–100 beds: medication reconciliation (13 percent) had the
highest year-over-year growth in this segment, followed by
EMAR and nurse call at nine percent each (see Table NA10).
• 101–200 beds: medication reconciliation (11 percent) had the
highest growth from 2010 to 2011, followed by nurse call system
at slightly under 10 percent. Infection surveillance systems
were the only other area with a growth of more than five percent
(see Table NA11).
• 201–300 beds: three nursing applications indicated a growth
in double digits from 2010 to 2011. These applications are
medication reconciliation (16 percent), nurse call system
(12 percent) and infection surveillance system (12 percent).
Nurse staffing/scheduling showed a slight decline in use in
the past year (see Table NA12).
Table N A10
0–100 Beds
Table N A14
2009
Electronic Medication
Administration Record (EMAR) 1,138
Infection Surveillance System
N/A
Medication Reconciliation
N/A
Nurse Call System
N/A
Nurse Staffing/Scheduling
918
Nursing Documentation
1,333
Patient Acuity
380
52.18%
0.00%
0.00%
0.00%
42.09%
61.12%
17.42%
2010
% of 2,181 hospitals
1,345
334
618
629
986
1,481
426
61.67%
15.31%
28.34%
28.84%
45.21%
67.90%
19.53%
2011
1,549
430
906
823
999
1,630
479
71.02%
19.72%
41.54%
37.73%
45.80%
74.74%
21.96%
Table N A11
101–200 Beds
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
401–500 Beds
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
2009
156
N/A
N/A
N/A
167
160
81
2010
% of 182 hospitals
85.71%
0.00%
0.00%
0.00%
91.76%
87.91%
44.51%
170
72
102
77
166
164
90
93.41%
39.56%
56.04%
42.31%
91.21%
90.11%
49.45%
2011
173
87
128
98
163
170
88
95.05%
47.80%
70.33%
53.85%
89.56%
93.41%
48.35%
Table N A15
2009
572
N/A
N/A
N/A
605
659
260
69.59%
0.00%
0.00%
0.00%
73.60%
80.17%
31.63%
2010
% of 822 hospitals
630
211
328
360
625
677
284
76.64%
25.67%
39.90%
43.80%
76.03%
82.36%
34.55%
2011
661
259
421
442
626
707
290
80.41%
31.51%
51.22%
53.77%
76.16%
86.01%
35.28%
Table N A12
201–300 Beds
• 301–400 beds: medication reconciliation and nurse call systems
had the highest year-over-year growth at 15 percent and 12
percent, respectively. Nurse staffing/scheduling is the only
application to decrease in the same timeframe (see Table NA13).
• 401–500 beds: EMAR is close to reaching full market saturation
at 95 percent in 2011. Medication reconciliation and nurse call
systems experienced double digit growth, at 14 and 12 percent
respectively (see Table NA14).
• 501–600: overall, the nursing IT applications had slight to
moderate increase in this bed segment (two to seven percent)
from 2010 to 2011. EMAR and nurse staffing have achieved
market saturation (95 percent or better) and nurse staffing/
scheduling is close to market saturation (see Table NA15).
• Over 600 beds: the largest growth in this bed segment was
medication reconciliation at nearly 19 percent followed closely
by infection surveillance systems (18 percent). Nurse staffing/
scheduling did not show growth over the past year and nursing
documentation has reached market saturation (see Table NA16).
501–600 Beds
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
2009
108
N/A
N/A
N/A
114
116
48
2010
% of 122 hospitals
88.52%
0.00%
0.00%
0.0%
93.44%
95.08%
39.34%
116
52
75
64
115
119
54
95.08%
42.62%
61.48%
52.46%
94.26%
97.54%
44.26%
2011
118
59
84
73
115
119
56
96.72%
48.36%
68.85%
59.84%
94.26%
97.54%
45.90%
Table N A16
2009
398
N/A
N/A
N/A
435
429
174
78.97%
0.00%
0.00%
0.00%
86.31%
85.12%
34.52%
2010
% of 504 hospitals
426
150
220
231
444
446
194
84.52%
29.76%
43.65%
45.83%
88.10%
88.49%
38.49%
2011
449
210
302
292
438
461
199
89.09%
41.67%
59.92%
57.94%
86.90%
91.47%
39.48%
600+ Beds
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
2009
129
N/A
N/A
N/A
138
133
63
2010
% of 150 hospitals
86.00%
0.00%
0.00%
0.00%
92.00%
88.67%
42.00%
133
59
76
73
140
141
69
88.67%
39.33%
50.67%
48.67%
93.33%
94.00%
46.00%
2011
138
86
104
91
140
143
71
92.00%
57.33%
69.33%
60.67%
93.33%
95.33%
47.33%
Table N A13
301–400 Beds
Electronic Medication
Administration Record (EMAR)
Infection Surveillance System
Medication Reconciliation
Nurse Call System
Nurse Staffing/Scheduling
Nursing Documentation
Patient Acuity
2009
263
N/A
N/A
N/A
297
290
111
80.18%
0.00%
0.00%
0.00%
90.55%
88.41%
33.84%
2010
% of 328 hospitals
275
109
151
138
300
296
123
83.84%
33.23%
46.04%
42.07%
91.46%
90.24%
37.50%
2011
296
136
201
177
299
303
129
90.24%
41.46%
61.28%
53.96%
91.16%
92.38%
39.33%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
43
▶▶ Nursing Department Environment con tinued
An evaluation of the contract purchasing timeframes for these
nursing applications reveals that more than half of the EMAR and
nursing documentation contracts were signed between 2005 and
2011, while most (80 percent or more) of the new applications
(infection surveillance, medication reconciliation and nurse call
system) were signed in that same time period (see Tables NA17 to
NA19).
Table N A17
# for Contract
2011
Range
Electronic Medication Administration Record (EMAR)
Prior to 1990
4
1990 to 1994
85
1995 to 1999
77
2000 to 2004
650
2005 to 2011
1,207
Total
2,023
Infection Surveillance System
Prior to 1990
0
1990 to 1994
3
1995 to 1999
8
2000 to 2004
31
2005 to 2011
219
Total
261
Total
Responding
% of Total
Responding
2,023
2,023
2,023
2,023
2,023
2,023
0.20%
4.20%
3.813%
32.13%
59.66%
100.00%
261
261
261
261
261
261
0.00%
1.15%
3.07%
11.88%
83.91%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
4
5
30
96
583
718
718
718
718
718
718
718
0.56%
0.70%
4.18%
13.37%
81.20%
100.00%
2
2
3
21
121
149
149
149
149
149
149
149
1.34%
1.34%
2.01%
14.09%
81.21%
100.00%
100
101
242
385
740
1,568
1,568
1,568
1,568
1,568
1,568
1,568
6.38%
6.44%
15.43%
24.55%
47.19%
100.00%
Table N A18
2011
Medication Reconciliation
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Nurse Call System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Nurse Staffing/Scheduling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
44 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Table N A19
2011
Nursing Documentation
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Patient Acuity
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
10
127
176
726
1,078
2,117
2,117
2,117
2,117
2,117
2,117
2,117
0.47%
6.00%
8.31%
34.29%
50.92%
100.00%
7
24
56
334
326
747
746
746
746
746
746
746
0.94%
3.22%
7.51%
44.77%
43.70%
100.00%
Market Drivers/Future Outlook
The nursing application IT application market has been and will
continue to be impacted by:
• The need to improve, and be able to report on, quality outcomes
and ARRA measures to meet increasingly detailed claims
documentation requirements and qualify for performance-based
reimbursement bonus payment.
• The need to improve patient safety and eliminate medical errors.
• Intense competition for limited capital for purchasing nursing
IT solutions.
• In this competition, nursing documentation purchases should
fare better, since they include functions which are essential for
hospitals to meet the ARRA meaningful use criteria,
measurements and reporting requirements.
• These systems, especially nursing documentation and EMAR,
have proven to be nurse satisfiers, thus aid in recruiting and
retention.
• The need to create an effective support foundation for CPOE as
most hospitals implement nursing documentation before CPOE.
• The need to effectively and efficiently determine nurse staffing
levels and assignments to meet minimum staffing requirements
and help reduce the impact of the nursing shortage.
• The need to couple EMAR applications with pharmacy
management and dispensing solutions to facilitate the closed
loop medication administration process for improving patient
safety—a requirement that we believe will be an integral part
of Stage 2 meaningful use requirements in some manner.
▶▶ Ancillary Department Environment
All the ancillary department applications showed slight to
moderate growth from 2010 to 2011. For the past several years,
respiratory care information systems indicated the highest growth
of the applications included in the ancillary care report. This
trend continues this year, with an increase of slightly more than
six percent. Laboratory information systems and pharmacy
management systems have achieved market saturation (95 percent
or better), and radiology information systems is very close to
reaching this threshold (see Table AD1).
Table A D1 | Ancillary Departments
N=4,289
2009
2010
Cardiology Information System
41.04%
43.13%
Emergency Department Systems
69.83%
72.88%
Intensive Care
48.08%
50.55%
Laboratory Information System
96.88%
97.55%
Obstetrical Systems (Labor and Delivery)
47.42%
48.45%
Pharmacy Management System
94.03%
94.73%
Radiology Information System
92.77%
93.96%
Respiratory Care Information System
38.80%
43.55%
Percentage include installed, contracted or installation in process
2011
45.51%
77.55%
53.30%
98.34%
50.83%
96.04%
94.85%
49.92%
The majority of purchases across the applications in ancillary
departments will be replacement purchases (see Table AD2).
Hospitals were most likely to indicate that purchases would be
first-time purchases for emergency department (ED) applications;
40 percent of hospitals reporting a purchase in this area would do
so for the first time. The drive for integrated clinical systems,
especially the requirement for a tight data coupling with pharmacy
systems and CPOE systems continues to drive the replacement of
legacy pharmacy systems with the organization’s EMR vendor’s
pharmacy system.
Replacement purchases for laboratory systems are being driven by
the need for laboratories to function as both hospital laboratories
and as reference laboratories for their local and/or regional markets.
As hospitals continue to move forward to achieve meaningful use
requirements, both for Stage One and in preparation for Stage Two,
hospital laboratories will be required to integrate laboratory results
associated with their own external reference labs into the EMRs of
their hospital patients. They will also be required to integrate results
with the EMRs of providers for whom they act as a reference
laboratory. High volumes of molecular biologic testing (e.g., genetic
and proteomic testing) may also induce laboratories to evaluate
replacing their current systems if current vendors do not support
these testing environments. ED systems continue to grow in the
smaller hospital market where installations are overwhelmingly
first-time purchases. The need for continuity of care documentation
including the emergency department is driving this growth into the
smaller hospital market. Intensive care system purchase growth is
being driven by the need for quality and safety improvements, the
desire to directly capture medical device data into the EMR.
An evaluation of hospital-type market segments for each ancillary
department system from 2010 to 2011 shows the highest growth in
the following hospital-type segments:
• Cardiology information systems: single hospital systems and
general medical/surgical hospitals have the greatest growth, at
more than three percent (see Table AD3).
• Emergency department systems: growth among critical access
hospitals and rural hospitals was strongest, at approximately ten
percent for each segment. Growth in all other segments ranged
from one to eight percent (see Table AD4).
• Intensive care: growth was strongest among academic medical
centers. Growth for the remaining segments ranged from one to
four percent (see Table AD5).
• Laboratory information systems: as expected, the growth in this
market is small, as all of the hospital segments have reached
market saturation (95 percent or better). All academic medical
centers utilize a laboratory information system (see Table AD6).
• Obstetrical systems: rural and single hospital systems reported
the greatest increase (more than four percent) in the past year.
Growth in the other segments was between one and three percent
(see Table AD7).
• Pharmacy management systems: critical access hospitals and
rural hospitals demonstrated the highest growth of approximately
three percent. All academic medical centers use pharmacy
management systems (see Table AD8).
• Radiology information systems: very little activity is reported
for radiology information systems since most of the segments
are approaching or have reached market saturation. The greatest
growth is among critical access and rural hospitals, at three
percent each (see Table AD9).
• Respiratory care information systems: the growth for this
application ranged from three to eight percent. Critical access
hospitals and rural hospitals reported the largest growth while
academic medical centers demonstrated the smallest growth at
slightly under four percent (see Table AD10).
Table A D2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Cardiology Information System
33
94.29%
Emergency Department Systems
48
60.00%
Intensive Care
32
80.00%
Laboratory Information System
94
94.00%
Obstetrical Systems (Labor and Delivery)
8
80.00%
Pharmacy Management System
78
86.67%
Radiology Information System
79
87.78%
Respiratory Care Information System
37
75.51%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
2
32
8
6
2
12
11
12
% of Hospitals Planning
to Purchase Software
for the First Time
5.71%
40.00%
20.00%
6.00%
20.00%
13.33%
12.22%
24.49%
Source: HIMSS Analytics® Database 2011
N = Total Number of
Hospitals Planning
35
80
40
100
10
90
90
49
©2012 HIMSS Analytics.
45
▶▶ Ancillary Department Environment con tinued
Table A D3 | Cardiology Information Systems
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
162
1598
1,422
338
90
1,670
68
1,692
1,243
517
1,760
Percent
84.38%
39.00%
56.72%
18.97%
7.79%
53.29%
6.75%
51.55%
48.07%
30.36%
41.04%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
170
1,680
1,507
343
95
1,755
80
1,770
1,290
560
1,850
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
2,943
2,214
912
631
2,495
551
2,575
2,009
1,117
3,126
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
155
2,013
1,568
600
266
1,902
221
1,947
1,468
700
2,168
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,992
2,498
1,686
1,080
3,104
949
3,235
2,545
1,639
4,184
Percent
88.54%
41.01%
60.11%
19.25%
8.23%
56.00%
7.79%
53.93%
49.88%
32.88%
43.13%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
171
1,781
1,585
367
118
1,834
93
1,859
1,332
620
1,952
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
185
3,141
2,295
1,031
744
2,582
656
2,670
2,060
1,266
3,326
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
164
2,122
1,664
622
275
2,011
238
2,048
1,519
767
2,286
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
4,026
2,500
1,718
1,100
3,118
962
3,256
2,565
1,653
4,218
Percent
89.06%
43.47%
63.22%
20.59%
10.22%
58.52%
9.24%
56.64%
51.51%
36.41%
45.51%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D 4 | Emergency Department Systems
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
179
2,816
2,168
827
546
2,449
472
2,523
1,956
1,039
2,995
Percent
93.23%
68.73%
86.48%
46.41%
47.27%
78.14%
46.87%
76.87%
75.64%
61.01%
69.83%
2010
Percent
95.31%
71.83%
88.31%
51.18%
54.63%
79.61%
54.72%
78.46%
77.69%
65.59%
72.88%
2011
Percent
96.35%
76.67%
91.54%
57.86%
64.42%
82.39%
65.14%
81.35%
79.66%
74.34%
77.55%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D5 | Intensive Care
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
147
1,915
1,476
586
258
1,804
222
1,840
1,410
652
2,062
Percent
76.56%
46.74%
58.88%
32.88%
22.34%
57.56%
22.05%
56.06%
54.52%
38.29%
48.08%
2010
Percent
80.73%
49.13%
62.54%
33.67%
23.03%
60.69%
21.95%
59.32%
56.77%
41.10%
50.55%
2011
Percent
85.42%
51.79%
66.37%
34.90%
23.81%
64.17%
23.63%
62.40%
58.74%
45.04%
53.30%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D6 | Laboratory Information System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
3,963
2,493
1,662
1,063
3,092
930
3,225
2,535
1,620
4,155
Percent
100.00%
96.73%
99.44%
93.27%
92.03%
98.66%
92.35%
98.26%
98.03%
95.13%
96.88%
2010
46 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
100.00%
97.44%
99.64%
94.61%
93.51%
99.04%
94.24%
98.57%
98.41%
96.24%
97.55%
2011
Percent
100.00%
98.27%
99.72%
96.41%
95.24%
99.49%
95.53%
99.21%
99.19%
97.06%
98.34%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Ancillary Department Environment con tinued
Table A D7 | Obstetrical Systems (Labor and Delivery)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
144
1,890
1,613
421
231
1,803
197
1,837
1,372
662
2,034
Percent
75.00%
46.13%
64.34%
23.63%
20.00%
57.53%
19.56%
55.97%
53.05%
38.87%
47.42%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
149
1,929
1,667
411
228
1,850
205
1,873
1,366
712
2,078
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,871
2,492
1,571
968
3,095
847
3,216
2,529
1,534
4,063
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,838
2,468
1,562
974
3,056
852
3,178
2,503
1,527
4,030
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
117
1,751
1,282
586
302
1,566
263
1,605
1,199
669
1,868
Percent
77.60%
47.08%
66.49%
23.06%
19.74%
59.03%
20.36%
57.07%
52.82%
41.81%
48.45%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
151
2,029
1,735
445
261
1,919
249
1,931
1,394
786
2,180
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,927
2,497
1,622
1,006
3,113
880
3,239
2,547
1,572
4,119
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
192
3,876
2,476
1,592
1,006
3,062
882
3,186
2,503
1,565
4,068
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
124
2,017
1,446
695
395
1,746
344
1,797
1,343
798
2,141
Percent
78.65%
49.52%
69.21%
24.97%
22.60%
61.23%
24.73%
58.84%
53.91%
46.15%
50.83%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D8 | Pharmacy Management System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
192
3,841
2,490
1,543
940
3,093
822
3,211
2,518
1,515
4,033
Percent
100.00%
93.75%
99.32%
86.59%
81.39%
98.69%
81.63%
97.84%
97.37%
88.96%
94.03%
2010
Percent
100.00%
94.48%
99.40%
88.16%
83.81%
98.76%
84.11%
97.99%
97.80%
90.08%
94.73%
2011
Percent
100.00%
95.85%
99.60%
91.02%
87.10%
99.33%
87.39%
98.69%
98.49%
92.31%
96.04%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D9 | Radiology Information System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
191
3,788
2,459
1,520
936
3,043
815
3,164
2,490
1,489
3,979
Percent
99.48%
92.46%
98.09%
85.30%
81.04%
97.10%
80.93%
96.40%
96.29%
87.43%
92.77%
2010
Percent
100.00%
93.68%
98.44%
87.65%
84.33%
97.51%
84.61%
96.83%
96.79%
89.67%
93.96%
2011
Percent
100.00%
94.61%
98.76%
89.34%
87.10%
97.70%
87.89%
97.07%
96.79%
91.90%
94.85%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table A D10 | Respiratory Care Information System
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
106
1,558
1,144
520
264
1,400
217
1,447
1,075
589
1,664
Percent
55.21%
38.03%
45.63%
29.18%
22.86%
44.67%
21.55%
44.09%
41.57%
34.59%
38.80%
2010
Percent
60.94%
42.74%
51.14%
32.88%
26.15%
49.97%
26.12%
48.90%
46.37%
39.28%
43.55%
2011
Source: HIMSS Analytics® Database 2011
Percent
64.58%
49.23%
57.68%
39.00%
34.20%
55.71%
34.16%
54.75%
51.93%
46.86%
49.92%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
47
▶▶ Ancillary Department Environment con tinued
The analysis of the ancillary market by bed size from 2009–2011
is shown in Tables AD11–AD17. Examining recent activities from
2010 to 2011, the top three highest application growth segments
by bed segment are as follows:
• 0–100 beds: respiratory care information systems and emergency
department systems each demonstrated a growth of more than
seven percent (see Table AD11).
• 101–200 beds: respiratory care reported the highest growth at
more than five percent, followed by intensive care and cardiology
information systems at three percent each (see Table AD12).
• 201–300 beds: the greatest growth was for intensive care and
respiratory care information systems at five and four percent
respectively (see Table AD13).
• 301–400 beds: respiratory care information systems had the
highest year-over-year growth at close to six percent. There
was no growth for laboratory information systems, pharmacy
management systems and radiology information systems, each
of which are universally used (see Table AD14).
• 401–500 beds: respiratory care information systems had the
highest growth at nearly four percent. Despite reaching market
saturation, growth for emergency department systems still topped
two percent (see Table AD15).
• 501–600 beds: respiratory systems, intensive care and cardiology
systems indicated increase from 2010 to 2011. All other
applications remain unchanged from last year. Laboratory
information systems, pharmacy management systems and
radiology information systems have achieved market saturation
(see Table AD16).
• Over 600 beds: respiratory care and intensive care each had
nearly seven percent growth in the past year. A number of
applications have reached market saturation (see Table AD17).
Table A D11
0–100 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
2010
2011
% of 2,181 hospitals
314 14.40%
357 16.37%
1,212 55.57% 1,371 62.86%
719 32.97%
754 34.57%
2,077 95.23% 2,110 96.74%
287
1,095
694
2,049
13.16%
50.21%
31.82%
93.95%
566
1,928
1,894
25.95%
88.40%
86.84%
576
1,957
1,936
26.41%
89.73%
88.77%
631
2,012
1,972
28.93%
92.25%
90.42%
611
28.01%
697
31.96%
862
39.52%
Table A D12
101–200 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
469 57.06%
704 85.64%
487 59.25%
822 100.00%
2010
% of 822 hospitals
497 60.46%
708 86.13%
521 63.38%
821 99.88%
2011
525 63.87%
729 88.69%
549 66.79%
822 100.00%
522
819
805
63.50%
99.64%
97.93%
538
820
810
65.45%
99.76%
98.54%
556
821
813
67.64%
99.88%
98.91%
381
46.35%
422
51.34%
468
56.93%
48 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Table A D13
201–300 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
2010
% of 504 hospitals
371 73.61%
469 93.06%
347 68.85%
504 100.00%
391 77.58%
478 94.84%
374 74.21%
504 100.00%
338 67.06%
504 100.00%
500 99.21%
343 68.06%
504 100.00%
503 99.80%
363 72.02%
504 100.00%
502 99.60%
247
275
296
354
467
329
503
70.24%
92.66%
65.28%
99.80%
49.01%
54.56%
2011
58.73%
Table A D14
301–400 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
254 77.44%
303 92.38%
208 63.41%
328 100.00%
2010
% of 328 hospitals
267 81.40%
305 92.99%
223 67.99%
328 100.00%
270 82.32%
310 94.51%
235 71.65%
328 100.00%
251 76.52%
328 100.00%
326 99.39%
251 76.52%
328 100.00%
327 99.70%
257 78.35%
328 100.00%
327 99.70%
164
179
198
50.00%
54.57%
2011
60.37%
Table A D15
401–500 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
158 86.81%
168 92.31%
129 70.88%
182 100.00%
2010
% of 182 hospitals
157 86.26%
171 93.96%
135 74.18%
182 100.00%
158 86.81%
175 96.15%
137 75.27%
182 100.00%
138 75.82%
182 100.00%
182 100.00%
143 78.57%
182 100.00%
182 100.00%
144 79.12%
182 100.00%
182 100.00%
103
117
124
56.59%
64.29%
2011
68.13%
Table A D16
501–600 Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
103
113
95
121
84.43%
92.62%
77.87%
99.18%
98 80.33%
122 100.00%
122 100.00%
67
54.92%
2010
% of 122 hospitals
105 86.07%
114 93.44%
101 82.79%
122 100.00%
108 88.52%
114 93.44%
105 86.07%
122 100.00%
101 82.79%
122 100.00%
122 100.00%
101 82.79%
122 100.00%
122 100.00%
77
63.11%
2011
82
67.21%
Table A D17
600+ Beds
Cardiology Information System
Emergency Department Systems
Intensive Care
Laboratory Information System
Obstetrical Systems
(Labor and Delivery)
Pharmacy Management System
Radiology Information System
Respiratory Care
Information System
2009
135 90.00%
145 96.67%
120 80.00%
150 100.00%
2010
% of 150 hospitals
139 92.67%
147 98.00%
122 81.33%
150 100.00%
143 95.33%
149 99.33%
132 88.00%
150 100.00%
121 80.67%
150 100.00%
150 100.00%
126 84.00%
150 100.00%
150 100.00%
128 85.33%
150 100.00%
150 100.00%
101
111
91
60.67%
67.33%
2011
74.00%
▶▶ Ancillary Department Environment con tinued
An evaluation of contract purchasing timeframes for ancillary
department applications shows that the majority of applications
was purchased between 2000 and 2011 (see Tables AD18–AD20).
Purchasing for cardiology information systems and ED systems
was particularly strong between 2005 and 2011, when half of all
contracts was signed. Ancillary department systems contracted
before 1995 will have the highest probability for replacement
purchases through 2015.
Table A D18
# for Contract
Range
Total
Responding
% of Total
Responding
4
18
66
291
423
802
802
802
802
802
802
802
0.50%
2.24%
8.23%
36.28%
52.74%
100.00%
13
51
185
714
979
1,942
1,942
1,942
1,942
1,942
1,942
1,942
0.67%
2.63%
9.53%
36.77%
50.41%
100.00%
8
133
167
549
585
1,452
1,452
1,452
1,452
1,452
1,452
1,452
0.55%
9.16%
11.50%
37.82%
40.98%
100.00%
# for Contract
2011
Range
Laboratory Information System
Prior to 1990
141
1990 to 1994
262
1995 to 1999
578
2000 to 2004
788
2005 to 2011
815
Total
2,584
Obstetrical Systems (Labor and Delivery)
Prior to 1990
0
1990 to 1994
33
1995 to 1999
110
2000 to 2004
359
2005 to 2011
391
Total
893
Pharmacy Management System
Prior to 1990
48
1990 to 1994
247
1995 to 1999
399
2000 to 2004
1,001
2005 to 2011
1,074
Total
2,769
Total
Responding
% of Total
Responding
2,584
2,584
2,584
2,584
2,584
2,584
5.46%
10.14%
22.37%
30.50%
31.54%
100.00%
893
893
893
893
893
893
0.00%
3.70%
12.32%
40.28%
43.78%
100.00%
2,769
2,769
2,769
2,769
2,769
2,769
1.73 %
8.92%
14.41%
36.15%
38.79%
100.00%
2011
Cardiology Information Systems
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Emergency Department Systems
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Intensive Care
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table A D19
Table A D20
2011
Radiology Information System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Respiratory Care Information System
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
58
164
379
916
1,137
2,654
2,654
2,654
2,654
2,654
2,654
2,654
2.19%
6.18%
14.28%
34.51%
42.84%
100.00%
11
123
150
404
514
1,202
1,202
1,202
1,202
1,202
1,202
1,202
0.92%
10.23%
12.48%
33.61%
42.76%
100.00%
Market Drivers/Future Outlook
The ancillary department IT application market has been and
will continue to be impacted through 2015 by:
• The need to reduce or eliminate medical and medication errors.
• The continued hospital focus on patient safety.
• The need to capture more clinical data electronically to support
meaningful use, health information exchange (HIE) and personal
health record (PHR) initiatives.
• Increased pressures on hospitals by federal and state authorities
to participate in HIE and public health reporting activities, or
the desire of IDNs to actively participate in private HIEs.
• The continued move toward integrated clinical systems and away
from “best of breed” will drive some replacement purchases of
essentially stand-alone ancillary systems.
• Intense competition for limited capital funds in a period when
government-mandated initiatives will determine the applications
that receive the highest priority.
• The need to create improved data sharing/integration between
clinical and financial systems to support improved claims
processing accuracy and for performance analysis and reporting
under bundled payment contracts.
• The need to reduce turn-around times for producing diagnostic
results that are accessible from the EMR.
• The need to have CPOE systems tightly coupled with pharmacy
systems.
• The need to have pharmacy systems tightly coupled with
electronic medication administration systems.
• The push by the government to improve the capture,
management, and sharing of electronic health information in
summary data formats between all healthcare stakeholders.
• The push by the government for pay-for-performance and the
continued need of hospitals to have discrete data with which to
report against ARRA meaningful use criteria by 2011 and
beyond.
• The need to provide a higher level of integration of order
communications and results reporting with external providers
and reference laboratories.
• Complex molecular and genomics testing in laboratories to
deliver “personalized medicine.”
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
49
▶▶ Laboratory Environment
The laboratory environment is included in the Annual Report for
the first time. This environment focuses on solutions that provide
automation and efficiency in laboratory operations. The five laboratory
applications included in this report are anatomical pathology, blood
bank, laboratory–molecular diagnostics, laboratory–outreach services,
and microbiology. Although laboratory information system solution
is also part of this environment, laboratory information system has
historically appeared in the ancillary section of the annual report.
At least for 2011, laboratory information system will continue to be
included in the ancillary environment section of this report.
In 2011, microbiology showed the highest market penetration at
79 percent, followed by blood bank (68 percent) and anatomical
pathology (60 percent). The lowest rate of adoption is laboratory–
molecular diagnostics at 14 percent. Laboratory–outreach services
demonstrated the largest year-over-year growth from 2010 to 2011
at close to five percent (see Table LAB1).
The majority of purchasing plans in this market will be to replace
existing systems. Laboratory–molecular diagnostics is an exception;
the majority of the handful of hospitals that will purchase this
solution in the future will do so for the first time (see Table LAB2).
Table L A B1 | Laboratory
N=4,289
2009
2010
2011
Anatomical Pathology
57.82%
59.20%
59.59%
Blood Bank
65.89%
67.94%
67.85%
Laboratory–Molecular Diagnostics
6.34%
11.87%
13.92%
Laboratory–Outreach Services
13.71%
21.38%
26.18%
Microbiology
74.61%
77.52%
79.46%
Percentages include installed, contracted or installation in process
NOTE: installed does not necessarily indicate full usage across all patient units or by all
categories of clinician
An evaluation of hospital-type market segment growth from
2010 to 2011 shows the highest growth by application occurred
as follows:
• Anatomical pathology: while there was a very slight decrease in
the use of this technology among academic medical centers, this
market is saturated (95 percent adoption). At nearly two percent,
the greatest growth was demonstrated in the critical access, rural
and single hospital system markets (see Table LAB3).
• Blood bank: the academic medical center segment is saturated,
with 98 percent adoption. Rural hospitals and critical access
hospitals indicated the most growth at slightly under two percent.
The single hospital system reported an increase of one percent.
Most other segments reported a decrease in adoption of less than
one percent in the past year (see Table LAB4).
• Laboratory–molecular diagnostics: the highest growth for this
application occurred in the academic medical center segment
(more than four percent). Growth of one to two percent was
noted in the remaining market segments (see Table LAB5).
• Laboratory–outreach services: the highest increase in adoption
for this application was reported by the academic medical center
segment at six percent. The remaining segments saw growth of
three to five percent (see Table LAB6).
• Microbiology: academic medical center has almost reached
full market penetration (98 percent) followed by general
medical/surgical hospitals (93 percent). All hospital segments
demonstrated growth of one percent to four percent with rural
hospitals demonstrating the largest year-over-year increase
(see Table LAB7).
Table L A B2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Anatomical Pathology
38
95.00%
Blood Bank
38
79.17%
Laboratory–Molecular Diagnostics
1
20.00%
Laboratory–Outreach Services
24
80.00%
Microbiology
43
95.56%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
2
10
4
6
2
% of Hospitals Planning
to Purchase Software
for the First Time
5.00%
20.83%
80.00%
20.00%
4.44%
N = Total Number of
Hospitals Planning
40
48
5
30
45
Table L A B 3 | Anatomical Pathology
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
188
2,292
1,901
579
244
2,236
204
2,276
1,722
758
2,480
Percent
97.92%
55.94%
75.83%
32.49%
21.13%
71.35%
20.26%
69.35%
66.59%
44.51%
57.82%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
50 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Segment
Count
190
2,349
1,927
612
271
2,268
234
2,305
1,740
799
2,539
Percent
98.96%
57.33%
76.86%
34.34%
23.46%
72.37%
23.24%
70.23%
67.29%
46.92%
59.20%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
2,368
1,927
629
294
2,262
251
2,305
1,724
832
2,556
Percent
97.92%
57.80%
76.86%
35.30%
25.45%
72.18%
24.93%
70.23%
66.67%
48.85%
59.59%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Laboratory Environment con tinued
Table L A B 4 | Blood Bank
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
188
2,638
2,132
694
355
2,471
308
2,518
1,974
852
2,826
Percent
97.92%
64.39%
85.04%
38.95%
30.74%
78.84%
30.59%
76.72%
76.33%
50.03%
65.89%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
2,725
2,155
759
404
2,510
350
2,564
1,991
923
2,914
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
79
430
365
144
25
484
24
485
395
114
509
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
85
832
674
243
86
831
65
852
642
275
917
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
187
3,138
2,306
1,019
566
2,759
496
2,829
2,159
1,166
3,325
Percent
98.44%
66.51%
85.96%
42.59%
34.98%
80.09%
34.76%
78.12%
76.99%
54.20%
67.94%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
2,722
2,139
771
424
2,486
368
2,542
1,968
942
2,910
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
88
509
420
177
43
554
36
561
461
136
597
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
97
1,026
808
315
129
994
98
1,025
793
330
1,123
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,219
2,333
1,075
611
2,797
541
2,867
2,190
1,218
3,408
Percent
97.92%
66.44%
85.32%
43.27%
36.71%
79.32%
36.54%
77.45%
76.10%
55.31%
67.85%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table L A B5 | Laboratory–Molecular Diagnostics
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
44
228
195
77
12
260
15
257
194
78
272
Percent
22.92%
5.57%
7.78%
4.32%
1.04%
8.30%
1.49%
7.83%
7.50%
4.58%
6.34%
2010
Percent
41.15%
10.50%
14.56%
8.08%
2.16%
15.44%
2.38%
14.78%
15.27%
6.69%
11.87%
2011
Percent
45.83%
12.42%
16.75%
9.93%
3.72%
17.68%
3.57%
17.09%
17.83%
7.99%
13.92%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table L A B6 | Laboratory–Outreach Services
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
54
534
448
140
56
532
43
545
409
179
588
Percent
28.13%
13.03%
17.87%
7.86%
4.85%
16.98%
4.27%
16.61%
15.82%
10.51%
13.71%
2010
Percent
44.27%
20.31%
26.88%
13.64%
7.45%
26.52%
6.45%
25.96%
24.83%
16.15%
21.38%
2011
Percent
50.52%
25.04%
32.23%
17.68%
11.17%
31.72%
9.73%
31.23%
30.67%
19.38%
26.18%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table L A B7 | Microbiology
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
184
3,016
2,275
925
501
2,699
436
2,764
2,120
1,080
3,200
Percent
95.83%
73.61%
90.75%
51.91%
43.38%
86.12%
43.30%
84.22%
81.98%
63.42%
74.61%
2010
Percent
97.40%
76.59%
91.98%
57.18%
49.00%
88.03%
49.26%
86.20%
83.49%
68.47%
77.52%
2011
Source: HIMSS Analytics® Database 2011
Percent
98.44%
78.57%
93.06%
60.33%
52.90%
89.25%
53.72%
87.36%
84.69%
71.52%
79.46%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
51
▶▶ Laboratory Environment con tinued
The analysis of the laboratory market by bed size in 2011 indicates
the following (see Tables LAB8–LAB14):
• 0–100 beds: laboratory–outreach services demonstrated the highest
growth for this segment (more than four percent), followed by
microbiology at slightly more than three percent (see Table LAB8).
• 101–200 beds: the largest growth in this segment was for
laboratory–outreach services, with growth of nearly four percent.
Use of blood bank and anatomical pathology solutions decreased
in the past year (see Table LAB9).
• 201–300 beds: laboratory–outreach services had a more than five
percent growth in this market; growth for laboratory–molecular
diagnostics was two percent (see Table LAB10).
• 301–400 beds: the greatest growth in this segment was for
laboratory–outreach services and laboratory–molecular diagnostics,
at six and three percent respectively (see Table LAB11).
• 401–500 beds: laboratory–molecular diagnostics and laboratory–
outreach services demonstrated the best growth in this segment,
as four and six percent respectively. Blood bank and microbiology
remained unchanged from last year (see Table LAB12).
• 501–600 beds: this bed segment has almost reached complete market
saturation for anatomical pathology, microbiology and blood bank
(95 percent or better) in 2011 and there was no additional growth
for these applications during the past year. Laboratory–outreach
services and laboratory–molecular diagnostics showed growth of
seven percent and two percent respectively (see Table LAB13).
• 600+ beds: laboratory–outreach services demonstrated the most
growth in this segment at more than eight percent, followed by
laboratory–molecular diagnostics at seven percent. There was minimal
to no growth for the remaining applications (see Table LAB14).
More than half of the contracting for laboratory–molecular
diagnostics and laboratory–outreach services took place during
2005 to 2011 (see Tables LAB15–LAB16). One-third of the contracts
for the remaining applications were signed during the same period.
Market Drivers/Future Outlook
The laboratory environment market has been or will likely be
impacted through 2016 by:
• An increased focus on complying with ARRA meaningful use
process and reporting criteria in order to qualify for EMR
adoption incentives and avoid Medicare reimbursement penalties.
• Increased pressures on hospitals by federal and state authorities
to participate in HIE and public health reporting activities for
disease indexes and syndromic reporting.
• Intense competition for capital funding, and staff resources
between financial (e.g., version 5010 EDI transaction mandate,
ICD-10-PCS coding mandate) and clinical (e.g., ARRA
meaningful use measurements) IT projects.
• Accelerated mergers and acquisitions in the provider market which
will drive some laboratory and pathology service consolidation.
• With increased mergers and the continued growth of IDNs there
will be an increase in demand from the medical staff for leadingedge molecular diagnostics capabilities to develop a personalized
medicine program.
• Tight capital markets may continue to impact the acquisition and
installation of EMR products through 2015, especially for small
community and critical access hospitals, in spite of the
availability of ARRA incentives.
• The increased need to acquire, manage, and analyze clinical data for
business intelligence, outcomes improvement, pay-for-performance
incentive programs and government compliance reporting.
52 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Table L A B8
0–100 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
683
875
42
139
1,189
2010
2011
% of 2,181 hospitals
31.32%
723 33.15%
745 34.16%
40.12%
953 43.70%
977 44.80%
1.93%
6.37%
54.52%
84
235
1,295
3.85%
10.77%
59.38%
123
329
1,373
5.64%
15.08%
62.95%
Table L A B9
101–200 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
614
714
2010
% of 822 hospitals
74.70%
630 76.64%
86.86%
719 87.47%
624
699
75.91%
85.04%
68
143
763
8.27%
17.40%
92.82%
124
239
773
15.09%
29.08%
94.04%
117
205
772
14.23%
24.94%
93.92%
2011
Table L A B10
201–300 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
444
476
2010
% of 504 hospitals
88.10%
448 88.89%
94.44%
480 95.24%
453
478
89.88%
94.84%
40
91
486
7.94%
18.06%
96.43%
94
187
493
18.65%
37.10%
97.82%
83
160
492
16.47%
31.75%
97.62%
2011
Table L A B11
301–400 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
303
321
2010
% of 328 hospitals
92.38%
303 92.38%
97.87%
323 98.48%
301
317
91.77%
96.65%
33
79
320
10.06%
24.09%
97.56%
89
139
323
27.13%
42.38%
98.48%
79
120
321
24.09%
36.59%
97.87%
2011
Table L A B12
401–500 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
171
176
2010
% of 182 hospitals
93.96%
170 93.41%
96.70%
176 96.70%
168
176
92.31%
96.70%
27
55
178
14.84%
30.22%
97.80%
54
84
180
29.67%
46.15%
98.90%
47
73
180
25.82%
40.11%
98.90%
2011
Table L A B13
501–600 Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
119
119
2010
% of 122 hospitals
97.54%
119 97.54%
97.54%
120 98.36%
119
120
97.54%
98.36%
20
38
117
16.39%
31.15%
95.90%
36
58
118
29.51%
47.54%
96.72%
33
50
118
27.05%
40.98%
96.72%
2011
Table L A B14
600+ Beds
Anatomical Pathology
Blood Bank
Laboratory–Molecular
Diagnostics
Laboratory–Outreach Services
Microbiology
2009
146
145
2010
% of 150 hospitals
97.33%
146 97.33%
96.67%
143 95.33%
146
143
97.33%
95.33%
42
43
147
28.00%
28.67%
98.00%
77
87
148
51.33%
58.00%
98.67%
66
74
147
44.00%
49.33%
98.00%
2011
▶▶ Laboratory Environment con tinued
Table L A B15
2011
Anatomical Pathology
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Blood Bank
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Laboratory–Molecular Diagnostics
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table L A B16
# for Contract
Range
Total
Responding
% of Total
Responding
49
138
259
521
450
1,417
1,417
1,417
1,417
1,417
1,417
1,417
3.46%
9.74%
18.28%
36.77%
31.76%
100.00%
74
160
249
436
584
1,503
1,503
1,503
1,503
1,503
1,503
1,503
4.92%
10.65%
16.57%
29.01%
38.86%
100.00%
8
7
21
24
81
141
141
141
141
141
141
141
5.67%
4.96%
14.89%
17.02%
57.45%
100.00%
2011
Laboratory–Outreach Services
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Microbiology
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
6
12
49
58
188
313
313
313
313
313
313
313
1.92%
3.83%
15.65%
18.53%
60.06%
100.00%
89
198
422
606
617
1,932
1,931
1,931
1,931
1,931
1,931
1,932
4.61%
10.25%
21.85%
31.38%
31.95%
100.00%
▶▶ Operating Room (Surgery)
In 2011, more than two thirds of U.S. hospitals have implemented
all of the operating room (OR) suite of applications covered in
this report—OR scheduling systems, peri-operative systems,
pre-operative and post-operative systems (see Table OR1).
The OR IT application market for U.S. hospitals showed growth
of approximately three to four percent across all applications in
this suite.
The majority of hospitals that reported plans to purchase OR
solutions will replace their existing solutions, driven by the
availability of new products and upgraded versions of existing
solutions (see Table OR2).
Table OR1 | Operating Room
N=4,289
2009
2010
Operating Room (Surgery) – Peri-Operative
57.64%
59.73%
Operating Room (Surgery) – Post-Operative
58.14%
60.62%
Operating Room (Surgery) – Pre-Operative
63.04%
64.75%
OR Scheduling
65.54%
67.54%
Percentage include installed, contracted or installation in process
2011
63.56%
64.84%
67.82%
70.44%
An evaluation of hospital-type market segments in 2011 indicates
that the highest growth by application is as follows:
• Peri-operative: the rural hospital segment had the best year-overyear growth in 2011 at close to seven percent followed by critical
access and single hospital systems (more than five percent each).
The academic medical center segment continues to approach
market saturation (more than 94 percent) (see Table OR3).
• Post-operative: rural and critical access hospitals had the highest
year-over-year growth for this segment in 2011; both had growth
of almost seven percent. Single hospital systems closely followed
at nearly six percent (see Table OR4).
• Pre-operative: as with the peri-operative and post-operative
applications, rural hospitals in the pre-operative market demonstrated
the largest year-over-year growth at more than six percent, followed
by critical access and single hospital systems (see Table OR5).
• OR scheduling: rural hospitals, single hospitals and critical access
hospitals showing the highest increases at more than five percent.
Use of this technology is saturated among academic medical
centers (see Table OR6).
Table OR 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Operating Room (Surgery) – Peri-Operative
56
75.68%
Operating Room (Surgery) – Post-Operative
57
77.03%
Operating Room (Surgery) – Pre-Operative
58
79.45%
OR Scheduling
58
82.86%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
18
17
15
12
% of Hospitals Planning
to Purchase Software
for the First Time
24.32%
22.97%
20.55%
17.14%
Source: HIMSS Analytics® Database 2011
N = Total Number of
Hospitals Planning
74
74
73
70
©2012 HIMSS Analytics.
53
▶▶ Operating Room (Surgery) con tinued
Table OR3 | Operating Room (Surgery) – Peri-Operative
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
168
2,304
1,857
615
327
2,145
260
2,212
1,661
811
2,472
Percent
87.05%
56.24%
74.07%
34.51%
28.31%
68.44%
25.82%
67.40%
64.23%
47.62%
57.64%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
177
2,385
1,897
665
373
2,189
301
2,261
1,687
875
2,562
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
175
2,425
1,910
690
399
2,201
328
2,272
1,698
902
2,600
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
2,594
2,032
745
438
2,339
355
2,422
1,802
975
2,777
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
2,708
2,110
787
470
2,427
371
2,526
1,898
999
2,897
Percent
92.19%
58.21%
75.67%
37.32%
32.29%
69.85%
29.89%
68.89%
65.24%
51.38%
59.73%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
182
2,544
1,982
744
441
2,285
369
2,357
1,763
963
2,726
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
180
2,601
2,004
777
475
2,306
398
2,383
1,777
1,004
2,781
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
185
2,724
2,099
810
500
2,409
418
2,491
1,847
1,062
2,909
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
190
2,831
2,178
843
530
2,491
435
2,586
1,930
1,091
3,021
Percent
94.79%
62.09%
79.06%
41.75%
38.18%
72.91%
36.64%
71.82%
68.17%
56.55%
63.56%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table OR4 | Operating Room (Surgery) – Post-Operative
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
165
2,329
1,859
635
349
2,145
279
2,215
1,665
829
2,494
Percent
85.94%
56.85%
74.15%
35.63%
30.22%
68.44%
27.71%
67.49%
64.39%
48.68%
58.15%
2010
Percent
91.15%
59.19%
76.19%
38.72%
34.55%
70.23%
32.57%
69.23%
65.66%
52.97%
60.62%
2011
Percent
93.75%
63.49%
79.94%
43.60%
41.13%
73.58%
39.52%
72.61%
68.72%
58.95%
64.84%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table OR5 | Operating Room (Surgery) – Pre-Operative
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
181
2,523
2,005
699
388
2,316
310
2,394
1,792
912
2,704
Percent
94.27%
61.58%
79.98%
39.23%
33.59%
73.90%
30.78%
72.94%
69.30%
53.55%
63.04%
2010
Percent
95.31%
63.31%
81.05%
41.81%
37.92%
74.63%
35.25%
73.80%
69.68%
57.25%
64.75%
2011
Percent
96.35%
66.49%
83.73%
45.45%
43.29%
76.87%
41.51%
75.90%
71.42%
62.36%
67.82%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table OR6 | OR Scheduling
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
184
2,627
2,065
746
431
2,380
334
2,477
1,874
937
2,811
Percent
95.83%
64.12%
82.37%
41.86%
37.32%
75.94%
33.17%
75.47%
72.47%
55.02%
65.54%
2010
54 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
98.44%
66.10%
84.16%
44.16%
40.69%
77.44%
36.84%
76.97%
73.40%
58.66%
67.54%
2011
Percent
98.96%
69.10%
86.88%
47.31%
45.89%
79.48%
43.20%
78.79%
74.63%
64.06%
70.44%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Operating Room (Surgery) con tinued
The analysis of the OR market by bed size in 2011 suggests growth
in the following areas (see Tables OR7–OR13):
• 0–100 beds: all OR applications showed a growth of four to five
percent in this bed segment, most likely driven by the general
increased number of OR applications implemented in critical
access hospitals (see Table OR7).
• 101–200 beds: all OR applications indicated a growth of two to
nearly four percent in this bed segment. OR scheduling and postoperative demonstrated the largest growth at more than three
percent (see Table OR8).
• 201–300 beds: growth of all OR applications in this bed segment
was less than one percent between 2010 and 2011; the exception
was OR scheduling, where there was no growth (see Table OR9).
• 301–400 beds: the percent of post-operative implementation
increased by four percent from 2010 to 2011. All other OR
applications indicated a growth of one percent to three percent in
the same timeframe (see Table OR10).
Table OR7
0–100 Beds
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
776
799
883
925
35.58%
36.63%
40.49%
42.41%
2010
2011
% of 2,181 Hospitals
834 38.24%
948 43.47%
869 39.84%
995 45.62%
948 43.47% 1,047 48.01%
997 45.71% 1,085 49.75%
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
612
616
654
679
74.45%
74.94%
79.56%
82.60%
2010
% of 822 hospitals
608 73.97%
617 75.06%
651 79.20%
679 82.60%
2011
633
646
673
709
77.01%
78.59%
81.87%
86.25%
2009
403
403
444
463
79.96%
79.96%
88.10%
91.87%
2010
% of 504 hospitals
421 83.53%
424 84.13%
449 89.09%
469 93.06%
2011
425
426
451
469
84.33%
84.52%
89.48%
93.06%
Table OR10
301–400 Beds
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
2009
276
279
297
313
84.15%
85.06%
90.55%
95.43%
2010
% of 328 hospitals
277 84.45%
278 84.76%
297 90.55%
310 94.51%
2011
288
292
305
313
87.80%
89.02%
92.99%
95.43%
Table OR11
401–500 Beds
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
2009
157
152
169
172
86.26%
83.52%
92.86%
94.51%
2010
% of 182 hospitals
167 91.76%
161 88.46%
171 93.96%
175 96.15%
2011
168
163
170
177
92.31%
89.56%
93.41%
97.25%
Table OR12
501–600 Beds
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
600+ Beds
OR (Surgery) – Peri-Operative
OR (Surgery) – Post-Operative
OR (Surgery) – Pre-Operative
OR Scheduling
2009
137
136
141
142
91.33%
90.67%
94.00%
94.67%
2010
% of 150 hospitals
141 94.00%
139 92.67%
144 96.00%
148 98.67%
2011
146
144
146
149
97.33%
96.00%
97.33%
99.33%
Table OR14
2009
Table OR9
201–300 Beds
Evaluating the contract purchasing timeframes that include
2011 data, more than 80 percent of the contracts were signed
between 2000 and 2011 across all OR applications (see Tables
OR14 and OR15).
Table OR13
2009
Table OR8
101–200 Beds
• 401–500 beds: post-operative and OR scheduling applications
indicated the highest year-over-year growth from 2010 to 2011,
at approximately one percent. Pre-operative applications are the
only OR application to indicate a decrease from 2010 (less than
one percent) (see Table OR11).
• 501–600 beds: peri-operative and post-operative applications
indicated a two to three percent growth in this bed segment
with post-operative and OR scheduling remaining unchanged
from the 2010 (see Table OR12).
• Over 600 beds: all OR applications have reached market saturation
(95 percent or better) in 2011. Peri-operative and post-operative
demonstrated the best year-over-year growth in this segment at
more than three percent from 2010 to 2011 (see Table OR13).
2009
111
109
116
117
90.98%
89.34%
95.08%
95.90%
2010
% of 122 hospitals
114 93.44%
112 91.80%
117 95.90%
119 97.54%
2011
118
115
117
119
# for Contract
2011
Range
Operating Room (Surgery) – Peri-Operative
Prior to 1990
13
1990 to 1994
37
1995 to 1999
179
2000 to 2004
651
2005 to 2011
725
Total
1605
Operating Room (Surgery) – Post-Operative
Prior to 1990
7
1990 to 1994
44
1995 to 1999
187
2000 to 2004
654
2005 to 2011
737
Total
1629
Operating Room (Surgery) – Pre-Operative
Prior to 1990
22
1990 to 1994
72
1995 to 1999
253
2000 to 2004
733
2005 to 2011
744
Total
1824
Total
Responding
% of Total
Responding
1604
1604
1604
1604
1604
1605
0.81%
2.31%
11.16%
40.59%
45.20%
100.00%
1629
1629
1629
1629
1629
1629
0.43%
2.70%
11.48%
40.15%
45.24%
100.00%
1824
1824
1824
1824
1824
1824
1.21%
3.95%
13.87%
40.19%
40.79%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
17
56
216
675
808
1772
1770
1770
1770
1770
1770
1772
0.96%
3.16%
12.20%
38.14%
45.65%
100.00%
Table OR15
2010
OR Scheduling
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2010
Total
96.72%
94.26%
95.90%
97.54%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
55
▶▶ Operating Room (Surgery) con tinued
Market Drivers/Future Outlook
The OR IT application market for U.S. hospitals has been and will
continue to be impacted by some countervailing forces through
2015 by:
• An increased need to capture, share, manage, analyze, and report
OR data to improve processes and drive down costs, some of
which will be for ARRA measurement reporting and to prepare
the organization to price appropriately to accept more bundled
pricing risk in an ACO environment.
• An increased need to track and report quality outcomes for
ARRA measurement reporting, which will likely extend into the
OR environment in the later stages of measurement.
• A continuing focus on reducing medical and medication errors at
point of care and during surgery procedures, which is again likely
to be tied to ARRA reporting measures.
• A continued need to improve efficiency and optimize surgeons’
time in the highly competitive surgical environment.
• One of the last bastions of paper in hospitals is interoperative
anesthesia notes. Anesthesiologists are not likely to move to a
paperless environment if the rest of the OR suite is not automated.
• Increasingly stringent claims coding and supporting
documentation requirements mandated by federal regulations
and public and private reimbursement requirements.
• Intense competition for limited capital funds, which are likely to be
allocated to higher priority applications, such as EMR and financial
projects (e.g., version 5010 EDI transactions, and ICD-10-PCS
encoding conversions), may slow this market through at least 2015.
• An increased consumer demand to access and evaluate hospital
service performance indicators related to hospital performance
scorecards.
▶▶ Ambulatory (Hospital Owned/Managed) IT Environment
From 2010 to 2011, the applications tracked in the hospital-owned/
managed ambulatory IT market showed growth of less than one
percent to five percent, with the exception of ambulatory PACS
which decreased by more than two percent (see Table AH1). It is
reasonable to assume that an increase in the use of ambulatory
electronic medical records (AEMRs) can be traced to hospitals and
clinics having better understanding of the meaningful use metrics
released in 2010. Practice management is the only ambulatory IT
application that has achieved market saturation (installation rates
of 95 percent or better).
With respect to purchasing plans, almost all ambulatory EMRs
will be first-time purchases; the majority of practice management
systems and radiology systems purchases will be replacement
purchases (see Table AH2). As only a handful of purchases were
Table A H1 | Ambulatory
N = 18,335
2009
2010
Ambulatory EMR
53.98%
57.50%
Ambulatory Laboratory
15.71%
17.99%
Ambulatory PACS*
52.78%
59.41%
Ambulatory Pharmacy
5.92%
6.40%
Ambulatory Radiology
16.19%
17.63%
Practice Management
96.94%
97.08%
Percentage include installed, contracted or installation in process
*N = 3,354 Based on ambulatory facilities doing imaging on site
2011
62.26%
19.33%
56.54%
6.61%
18.48%
97.46%
identified for laboratory, PACS and pharmacy, it is not possible to
make an assessment of whether these markets are replacement or
first-time purchase markets.
The tempered growth in AEMR purchasing by hospitals in 2010
was the lack of clarity around the ARRA provisions which defined
the eligibility of “hospital-based physicians” for EMR adoption
incentives. Although intended to exclude hospitalists, pathologists,
ED physicians and others who used only the hospital’s inpatient
EMR, many believed that the restrictive language inadvertently
limited the ability of physicians employed in hospital-owned
ambulatory practices to qualify for incentives. It was not until the
release of the Meaningful Use Stage 1 Final Rule in July that the
qualifying criteria were clarified and hospitals were assured that
such physicians would qualify.
The Stage One of the meaningful use definition was finalized in
2010, thus clarifying the need to purchase AEMRs. It is expected
that AEMR purchases will continue to increase over the next
few years.
As with the acute care side, we are concerned about whether the
industry has the number of implementation professionals that will
be required to meet the ARRA meaningful use measurements for
2011, 2014 and 2015. Many vendors are reporting many months’
delay to begin an implementation after contract signing.
Table A H2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Ambulatory EMR
20
8.37%
Ambulatory Laboratory
1
100.00%
Ambulatory PACS
1
50.00%
Ambulatory Pharmacy
1
100.00%
Ambulatory Radiology
10
100.00%
Practice Management
52
83.87%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
56 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
# of Hospitals Planning
to Purchase Software
for the First Time
219
0
1
0
0
10
% of Hospitals Planning
to Purchase Software
for the First Time
91.63%
0.00%
50.00%
0.00%
0.00%
16.13%
N = Total Number of
Hospitals Planning
239
1
2
1
10
62
▶▶ Ambulatory (Hospital Owned/Managed) IT Environment con tinued
An evaluation of market segments provides the following market
insights for 2011. Please note that in this market segment, HIMSS
Analytics tracks data in the following categories: urban vs. rural
and multi- vs. single hospital system ownership/management of the
ambulatory facility:
• Ambulatory EMR: ambulatory facilities owned by single hospital
systems demonstrated year-over-year growth at more than six
percent (see Table AH3). Ambulatory facilities owned/managed
in the rural segment had growth of more than five percent.
• Ambulatory laboratory: growth is minimal (about one percent)
across all segments, except ambulatory facilities owned by single
hospital systems; growth in this market was approximately three
percent (see Table AH4).
• Ambulatory PACS: the adoption of this solution decreased across all
segments by one to four percent. Ambulatory facilities owned by
multi-hospital systems showed the largest decrease (see Table AH5).
• Ambulatory pharmacy: growth among ambulatory facilities
that are owned by single hospital systems was approximately
one percent; almost all of the remaining segments demonstrated
market growth of less than one percent in the past year, except
facilities owned by multi-hospital systems, where a slight
decrease was noted (see Table AH6).
• Ambulatory radiology: all segments indicated growth of two
percent or less, with the largest growth among those facilities
that are part of a single hospital system (see Table AH7).
• Practice management: every segment tracked in this report
has market utilization at 95 percent or greater. Therefore,
growth was minimal, at less than one percent in each segment
(see Table AH8).
Table A H3 | Ambulatory EMR
2009
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
1,170
8,727
6,717
3,180
9,897
Percent
46.89%
55.09%
57.36%
48.00%
53.98%
2010
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
1,361
9,182
6,985
3,558
10,543
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
332
2,966
2,156
1,142
3,298
Total
Count
320
3,134
2,318
1,136
3,454
Segment
Count
136
1,916
1,443
609
2,052
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
85
1,089
858
316
1,174
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
276
2,957
2,150
1,083
3,233
Percent
54.55%
57.97%
59.65%
53.71%
57.50%
2011
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
1,493
9,923
7,446
3,970
11,416
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
368
3,176
2,198
1,346
3,544
Total
Count
320
3,134
2,318
1,136
3,454
Segment
Count
133
1,820
1,355
598
1,953
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
102
1,110
820
392
1,212
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
305
3,084
2,169
1,220
3,389
Percent
59.84%
61.65%
63.59%
59.92%
62.26%
Total
Count
2,495
15,840
11,710
6,625
18,335
Table A H4 | Ambulatory Laboratory
2009
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
269
2,612
1,854
1,027
2,881
Percent
10.78%
16.49%
15.83%
15.50%
15.71%
2010
Percent
13.31%
18.72%
18.41%
17.24%
17.99%
2011
Percent
14.75%
20.05%
18.77%
20.32%
19.33%
Total
Count
2,495
15,840
11,710
6,625
18,335
Table A H5 | Ambulatory PACS
2009
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
* Based on ambulatory facilities doing imaging on site
Segment
Count
115
1,708
1,285
538
1,823
Percent
35.94%
54.50%
55.44%
47.36%
52.78%
2010
Percent
42.50%
61.14%
62.25%
53.61%
59.41%
2011
Percent
41.56%
58.07%
58.46%
52.64%
56.54%
Total
Count
320
3,134
2,318
1,136
3,454
Table A H6 | Ambulatory Pharmacy
2009
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
90
996
820
266
1,086
Percent
3.61%
6.29%
7.00%
4.02%
5.92%
2010
Percent
3.41%
6.88%
7.33%
4.77%
6.40%
2011
Percent
4.09%
7.01%
7.00%
5.92%
6.61%
Total
Count
2,495
15,840
11,710
6,625
18,335
Table A H7 | Ambulatory Radiology
2009
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
239
2,730
1,967
1,002
2,969
Percent
9.58%
17.23%
16.80%
15.12%
16.19%
2010
Percent
11.06%
18.67%
18.36%
16.35%
17.63%
2011
Source: HIMSS Analytics® Database 2011
Percent
12.22%
19.47%
18.52%
18.42%
18.48%
Total
Count
2,495
15,840
11,710
6,625
18,335
©2012 HIMSS Analytics.
57
▶▶ Ambulatory (Hospital Owned/Managed) IT Environment con tinued
Table A H8 | Practice Management
2009
Segment
Count
2,350
15,424
11,442
6,332
17,774
Type
Rural
Urban
Multi-Hospital System
Single Hospital System
All
2010
Percent
94.19%
97.37%
97.71%
95.58%
96.94%
Total
Count
2,495
15,840
11,710
6,625
18,335
Nearly three-quarters of ambulatory EMR contracts were signed
between 2005 and 2011, as were more than half of the ambulatory
PACS contracts. Approximately one third of ambulatory laboratory,
ambulatory pharmacy and practice management contracts were
signed in the 2000 to 2004 timeframe (see Table AH9–AH10).
Applications that were contracted before 2000, such as practice
management, would be entering a stage when the hospitals may
begin to evaluate them for replacement.
Table A H9
# for Contract
Range
Total
Responding
% of Total
Responding
5,815
5,815
5,815
5,815
5,815
5,815
0.64%
0.60%
3.92%
22.89%
71.89%
100.00%
1,145
1,145
1,145
1,145
1,145
1,145
4.37%
6.46%
14.32%
35.20%
39.65%
100.00%
415
415
415
415
415
415
0.00%
0.00%
4.34%
40.24%
56.14%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
2
4
54
118
150
328
328
328
328
328
328
328
0.61%
1.22%
16.46%
35.98%
45.73%
100.00%
4
20
133
642
492
1,291
1,291
1,291
1,291
1,291
1,291
1,291
0.31%
1.55%
10.30%
49.73%
38.11%
100.00%
205
565
1,876
3,078
3,995
9,708
9,708
9,708
9,708
9,708
9,708
9,708
2.11%
5.82%
19.32%
31.71%
41.15%
100.00%
2011
Ambulatory EMR
Prior to 1990
37
1990 to 1994
35
1995 to 1999
228
2000 to 2004
1,331
2005 to 2011
4,184
Total
5,815
Ambulatory Laboratory
Prior to 1990
50
1990 to 1994
74
1995 to 1999
164
2000 to 2004
403
2005 to 2011
454
Total
1,145
Ambulatory PACS*
Prior to 1990
0
1990 to 1994
0
1995 to 1999
18
2000 to 2004
167
2005 to 2011
233
Total
415
* Based on ambulatory facilities doing imaging on site
Table A H10
2011
Ambulatory Pharmacy
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Ambulatory Radiology
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Practice Management
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
58 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Segment
Count
2,374
15,425
11,427
6,372
17,799
Percent
95.15%
97.38%
97.58%
96.18%
97.08%
2011
Total
Count
2,495
15,840
11,710
6,625
18,335
Segment
Count
2,392
15,478
11,471
6,399
17,870
Percent
95.87%
97.71%
97.96%
96.59%
97.46%
Total
Count
2,495
15,840
11,710
6,625
18,335
The impending deadline for conversion to ICD-10 coding will require a
major upgrade to these legacy practice management applications. Since
many practices now will be selecting their first ambulatory EMR, we
foresee that these purchases will be combined for many organizations.
Further, the drive toward integrated systems to support continuity of care
and possibly a shared savings reimbursement environment will drive
many organizations to select an ambulatory EMR, a practice management
system and an acute care clinical system from the same vendor.
Market Drivers/Future Outlook
The hospital-owned/managed ambulatory IT application market
has been and will continue to be impacted through 2015 by:
• The need to comply with ARRA meaningful use criteria to
achieve funding for AEMR implementations or recover AEMR
investments already made.
• The need to facilitate the interoperable flow of information
between the acute care and ambulatory environments, as well
as with external HIE entities, which will be essential to receive
meaningful use incentive payments beyond Stage 1.
• The need to facilitate the interoperable flow of information
between the acute care and ambulatory environments for both
clinical and financial applications to support a shared savings /
bundled payment environment.
• Completion of practice management system upgrades in time for
the ICD-10 implementation deadline.
• Growing efforts of HIE projects, and the ability to create,
manage, and exchange patient summary data from all modalities
of patient care.
• The need to better track episodes of care for quality outcomes
and pay-for-performance reimbursement models, especially for
the ARRA meaningful use criteria, patient-centered medical
home and ACOs.
• Access to capital by hospitals to make application purchases for
their ambulatory environments (this will be easier for ambulatory
facilities owned by hospitals than for stand-alone/independent
clinics, which may drive further market consolidation of clinics
and ambulatory services and hospitals).
• Relaxation of the Stark Laws related to hospital subsidies for
ambulatory practice EMR purchases, which are set to expire in 2013.
• Ongoing activity with respect to standards adoption and
government mandates to ensure interoperability will lead to
frequent version upgrades of installed products.
• Usability of HIT systems that will accommodate a variety of
clinical specialties in addition to primary care clinicians.
• Consumer demands for personal health information and patient
safety derived from the AEMR.
• Increase in consumer demands to have emerging technologies
(i.e., mobile health or mHealth) available to communicate with
clinicians and manage their healthcare.
• Shortages of trained HIT professionals available to assist
ambulatory clinics in meeting the implementation and reporting
meaningful use requirements.
▶▶ Radiology PACS
Growth in the radiology picture archive and communications
system (R-PACS) market continued at a slight to moderate pace in
2011 (see Table RP1). Growth was strongest for the digital
mammography modality, which increased approximately eight
percent over the past year. The lowest growth was for angiography
at approximately one percent. Computed radiography (CR),
computerized tomography (CT), and ultrasound are approaching
market saturation at nearly 90 percent adoption level in 2011.
With the exception of orthopedic, the majority of R-PACS modality
planned purchases continue to be first-time purchases (see Table
RP2). Slightly more than half of planned purchase for orthopedic
solutions will replace existing solutions. While this is a market that
continues to offer good growth opportunities, it would be expected
that replacement purchases for R-PACS will continue to increase
due to the consolidation of the market vendors and products.
Additionally, new technologies which support 3D imagery will
begin to create obsolescence for some of the existing solutions.
Generally speaking, academic/teaching hospitals have the highest
rates of adoption across all modalities and this segment has
achieved market saturation (95 percent of the market or better) for
all modalities except digital mammography and orthopedics.
Medical/surgical hospitals are also approaching market saturation
(90 percent to 95 percent) for computed radiography, magnetic
resonance imaging (MRI) and nuclear medicine; and have achieved
market saturation for computerized tomography and ultrasound.
The top segments that showed the highest growths by modality
from 2010 to 2011 are:
• Angiography: at slightly more than two percent, rural hospitals
demonstrated the highest growth in this market. Other hospital
segments indicated a growth of approximately one percent
(see Table RP3).
• Computed radiography: rural hospitals and critical access
hospitals reported growth of more than six percent from in
the past year. All other segments indicated growth ranging less
than one percent (academic medical centers) to four percent
(see Table RP4).
• Computerized tomography: the highest growth reported for
computerized tomography is among rural hospitals and critical
access hospitals; each demonstrated growth of approximately
six percent. Market saturation has been reached among academic
hospitals and general medical/surgical hospitals (see Table RP5).
• Digital fluoroscopy: rural and critical access hospitals reported
the two highest increases at more than four percent. Growth
among other non-medical/surgical hospitals was slightly more
than three percent (see Table RP6).
• Digital mammography: all segments showed good growth
(more than five percent growth) from 2010 to 2011; nine percent
growth was achieved among general medical/surgical hospitals,
critical access hospitals, rural hospitals, and single hospitals
(see Table RP7).
• Digital radiography: rural hospitals indicated a growth of more
than five percent followed by critical access hospitals at more
than four percent. All other segments indicated growth that
ranged from one percent to three percent (see Table RP8).
• Magnetic resonance imaging: rural hospitals reported the highest
year-over-year increase at six percent followed by critical access
hospitals at five percent. Market saturation has been achieved
among academic/teaching hospitals (see Table RP9).
• Nuclear medicine: rural and critical access hospitals
demonstrated the largest increase at more than five percent,
each. Academic/teaching hospitals have achieved market
saturation and there was no growth in this segment in the past
year (see Table RP10).
• Orthopedic: with the exception of academic/teaching hospitals,
growth for this modality was between four and six percent.
Growth in the academic/teaching hospital segment had increased
by slightly more than two percent (see Table RP11).
• Ultrasound: rural hospitals and critical access hospitals
indicated moderate growth (six to seven percent) while the
other segments indicated growth from one percent to five
percent (see Table RP12).
Table RP1 | R-PACS
N=4,289
2009
2010
Angiography
63.16%
64.16%
Computed Radiography (CR)
79.90%
82.98%
Computerized Tomography (CT)
81.02%
84.61%
Digital Fluoroscopy (DF)
69.50%
71.79%
Digital Mammography
41.80%
50.52%
Digital Radiography (DR)
71.65%
74.68%
Magnetic Resonance Imaging (MRI)
76.08%
79.25%
Nuclear Medicine
71.21%
73.91%
Orthopedic
37.09%
42.46%
Ultrasound (US)
79.20%
82.96%
Percentage include installed, contracted or installation in process
2011
65.45%
86.20%
87.04%
74.33%
58.48%
77.36%
81.60%
75.99%
47.35%
86.17%
Table rp 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Angiography
4
26.67%
Computed Radiography (CR)
4
33.33%
Computerized Tomography (CT)
5
27.78%
Digital Fluoroscopy (DF)
4
30.77%
Digital Mammography
2
12.50%
Digital Radiography (DR)
4
28.57%
Magnetic Resonance Imaging (MRI)
3
21.43%
Nuclear Medicine
3
20.00%
Orthopedic
8
57.14%
Ultrasound (US)
3
23.08%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
11
8
13
9
14
10
11
12
6
10
% of Hospitals Planning
to Purchase Software
for the First Time
73.33%
66.67%
72.22%
69.23%
87.50%
71.43%
78.57%
80.00%
42.86%
76.92%
Source: HIMSS Analytics® Database 2011
N = Total Number of
Hospitals Planning
15
12
18
13
16
14
14
15
14
13
©2012 HIMSS Analytics.
59
▶▶ Radiology PACS con tinued
Table RP 3 | Angiography
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
185
2,524
2,003
706
383
2,326
333
2,376
1,833
876
2,709
Percent
96.35%
61.61%
79.90%
39.62%
33.16%
74.22%
33.07%
72.39%
70.88%
51.44%
63.16%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
185
2,567
2,033
719
396
2,356
340
2,412
1,851
901
2,752
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
3,371
2,284
1,275
830
2,729
703
2,356
2,165
1,394
3,559
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,438
2,356
1,273
902
2,727
763
2,866
2,154
1,475
3,629
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
184
2,895
2,177
902
554
2,525
470
2,609
1,973
1,106
3,079
Percent
96.35%
62.66%
81.09%
40.35%
34.29%
75.18%
33.76%
73.49%
71.58%
52.91%
64.16%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
186
2,621
2,078
729
418
2,389
365
2,442
1,894
913
2,807
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
2,508
2,339
1,358
903
2,794
772
2,925
2,247
1,450
3,697
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,542
2,407
1,326
970
2,763
828
2,905
2,209
1,524
3,733
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
185
3,003
2,231
957
603
2,585
513
2,675
2,037
1,151
3,188
Percent
96.88%
63.97%
82.89%
40.91%
36.19%
76.23%
36.25%
74.41%
73.24%
53.61%
65.45%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP4 | Computed Radiography (CR)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
188
3,239
2,224
1,203
760
2,667
654
2,773
2,114
1,313
3,427
Percent
97.92%
79.06%
88.71%
67.51%
65.80%
85.10%
64.95%
84.49%
81.75%
77.10%
79.90%
2010
Percent
97.92%
82.28%
91.10%
71.55%
71.86%
87.08%
69.81%
87.02%
83.72%
81.86%
82.98%
2011
Percent
98.44%
85.62%
93.30%
76.21%
78.18%
89.15%
76.66%
89.12%
86.89%
85.14%
86.20%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP5 | Computerized Tomography (CT)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
190
3,285
2,286
1,189
824
2,651
708
2,767
2,092
1,385
3,475
Percent
98.96%
80.18%
91.18%
66.72%
71.34%
84.59%
70.31%
84.31%
80.82%
81.33%
81.02%
2010
Percent
99.48%
83.92%
93.98%
71.44%
78.10%
87.01%
75.77%
87.32%
83.29%
86.61%
84.61%
2011
Percent
99.48%
86.45%
96.01%
74.41%
83.98%
88.16%
82.22%
88.51%
85.42%
89.49%
87.04%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP 6 | Digital Fluoroscopy (DF)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
183
2,798
2,112
869
522
2,459
452
2,529
1,923
1,058
2,981
Percent
95.31%
68.29%
84.24%
48.77%
45.19%
78.46%
44.89%
77.06%
74.36%
62.13%
69.50%
2010
60 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
95.83%
70.66%
86.84%
50.62%
47.97%
80.57%
46.67%
79.49%
76.30%
64.94%
71.79%
2011
Percent
96.35%
73.30%
88.99%
53.70%
52.21%
82.48%
50.94%
81.51%
78.77%
67.59%
74.33%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Radiology PACS con tinued
Table RP7 | Digital Mammography
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
129
1,664
1,302
491
304
1,489
242
1,551
1,166
627
1,793
Percent
67.19%
40.62%
51.93%
27.55%
26.32%
47.51%
24.03%
47.26%
45.09%
36.82%
41.80%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
138
2,029
1,556
611
414
1,753
327
1,840
1,375
792
2,167
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
186
3,017
2,179
1,024
608
2,595
519
2,684
2,046
1,157
3,203
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
3,211
2,294
1,105
762
2,637
640
2,759
2,071
1,328
3,399
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
2,987
2,255
915
588
2,582
509
2,661
1,993
1,177
3,170
Percent
71.88%
49.52%
62.07%
34.29%
35.84%
55.93%
32.47%
56.06%
53.17%
46.51%
50.52%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
149
2,359
1,785
723
526
1,982
426
2,082
1,561
947
2,508
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
187
3,131
2,237
1,081
661
2,657
571
2,747
2,105
1,213
3,318
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,311
2,350
1,150
820
2,680
703
2,797
2,130
1,370
3,500
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
183
3,076
2,301
958
647
2,612
563
2,696
2,041
1,218
3,259
Percent
77.60%
57.58%
71.20%
40.57%
45.54%
63.24%
42.30%
63.44%
60.36%
55.61%
58.48%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP 8 | Digital Radiography (DR)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
185
2,888
2,105
968
552
2,521
479
2,594
1,983
1,090
3,073
Percent
96.35%
70.49%
83.96%
54.32%
47.79%
80.44%
47.57%
79.04%
76.68%
64.00%
71.65%
2010
Percent
96.88%
73.64%
86.92%
57.46%
52.64%
82.80%
51.54%
81.78%
79.12%
67.94%
74.68%
2011
Percent
97.40%
76.42%
89.23%
60.66%
57.23%
84.78%
56.70%
83.70%
81.40%
71.23%
77.36%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP 9 | Magnetic Resonance Imaging (MRI)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
187
3,076
2,234
1,029
693
2,570
594
2,669
2,014
1,249
3,263
Percent
97.40%
75.08%
89.11%
57.74%
60.00%
82.00%
58.99%
81.32%
77.88%
73.34%
76.08%
2010
Percent
97.92%
78.37%
91.50%
62.01%
65.97%
84.14%
63.56%
84.06%
80.09%
77.98%
79.25%
2011
Percent
98.44%
80.82%
93.74%
64.53%
71.00%
85.51%
69.81%
85.22%
82.37%
80.45%
81.60%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP10 | Nuclear Medicine
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
182
2,872
2,195
859
535
2,519
476
2,578
1,944
1,110
3,054
Percent
94.79%
70.10%
87.55%
48.20%
46.32%
80.38%
47.27%
78.55%
75.17%
65.18%
71.21%
2010
Percent
95.31%
72.91%
89.95%
51.35%
50.91%
82.39%
50.55%
81.08%
77.07%
69.11%
73.91%
2011
Source: HIMSS Analytics® Database 2011
Percent
95.31%
75.08%
91.78%
53.76%
56.02%
83.34%
55.91%
82.15%
78.92%
71.52%
75.99%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
61
▶▶ Radiology PACS con tinued
Table RP11 | Orthopedic
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
123
1,468
1,115
476
256
1,335
204
1,387
1,025
566
1,591
Percent
64.06%
35.83%
44.48%
26.71%
22.16%
42.60%
20.26%
42.26%
39.64%
33.24%
37.09%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
134
1,687
1,276
545
304
1,517
237
1,584
1,156
665
1,821
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
189
3,369
2,336
1,222
861
2,697
726
2,832
2,124
1,434
3,558
Percent
69.79%
41.18%
50.90%
30.58%
26.32%
48.40%
23.54%
48.26%
44.70%
39.05%
42.46%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
139
1,892
1,416
615
364
1,667
293
1,738
1,268
763
2,031
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
190
3,506
2,390
1,306
938
2,758
799
2,897
2,209
1,487
3,696
Percent
72.40%
46.18%
56.48%
34.51%
31.52%
53.19%
29.10%
52.96%
49.03%
44.80%
47.35%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table RP12 | Ultrasound (US)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
188
3,209
2,270
1,127
771
2,626
662
2,735
2,054
1,343
3,397
Percent
97.92%
78.33%
90.55%
63.24%
66.75%
83.79%
65.74%
83.33%
79.43%
78.86%
79.20%
2010
When looking at bed-size growth in the R-PACS market, growth
will be greater among smaller hospitals; a higher percent of
hospitals with 100 beds or fewer adopted technology in the past
year, compared to larger hospitals. It is likely that the higher level of
adoption in this bed segment is being driven primarily by adoption
of this technology among rural and critical access hospitals. The
following list represents the modalities with the greatest
implementation growth by bed segment:
• 0–100 beds: digital mammography reported the highest year-overyear increase (nine percent). Growth for the remaining modalities
is between three and five percent, with the exception being
angiography, at one percent (see Table RP13).
• 101–200 beds: the largest growth was among the digital
mammography and orthopedic modalities (almost ten and six
percent respectively) in the past year (see Table RP14).
• 201–300 beds: digital mammography and orthopedics are the
only modalities to indicate a substantial increase (more than five
percent), while the adoption of other modalities was less than
two percent (see Table RP15).
62 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
98.44%
82.23%
93.18%
68.57%
74.55%
86.06%
72.10%
86.29%
82.13%
84.20%
82.96%
2011
Percent
98.96%
85.57%
95.33%
73.29%
81.21%
88.00%
79.34%
88.27%
85.42%
87.32%
86.17%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
• 301–400 beds: digital mammography indicated an increase
of nearly six percent, followed orthopedics at three percent.
Computerized tomography, MRI, nuclear medicine and
ultrasound did not show any growth in this segment in the
past year (see Table RP16).
• 401–500 beds: digital mammography and orthopedics each
showed a growth of approximately four percent. Use of
angiography, computed radiography and digital fluoroscopy
declined in this segment in the past year (see Table RP17).
• 501–600 beds: digital mammography and orthopedic are the
only modalities that showed significant increases in this segment
in the past year (see Table RP18).
• Over 600 beds: orthopedic and digital mammography each
reported the highest year-over-year growth at approximately
seven percent. Growth among the remaining modalities was
negligible (see Table RP19).
▶▶ Radiology PACS con tinued
Table RP13
0–100 Beds
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
Table RP18
2009
882
1,482
1,516
1,120
593
1,199
1,330
1,136
525
1,445
40.44%
67.95%
69.51%
51.35%
27.19%
54.97%
60.98%
52.09%
24.07%
66.25%
2010
2011
% of 2,181 hospitals
904 41.45%
931 42.69%
1,577 72.31% 1,693 77.62%
1,622 74.37% 1,711 78.45%
1,176 53.92% 1,254 57.50%
778 35.67%
966 44.29%
1,282 58.78% 1,371 62.86%
1,426 65.38% 1,504 68.96%
1,210 55.48% 1,283 58.83%
616 28.24%
716 32.83%
1,562 71.62% 1,682 77.12%
Table RP14
101–200 Beds
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
649
729
727
681
409
684
712
707
380
720
78.95%
88.69%
88.44%
82.85%
49.76%
83.21%
86.62%
86.01%
46.23%
87.59%
2010
% of 822 hospitals
653 79.44%
750 91.24%
753 91.61%
701 85.28%
493 59.98%
715 86.98%
733 89.17%
731 88.93%
424 51.58%
745 90.63%
2011
669
767
765
722
571
733
752
745
472
760
81.39%
93.31%
93.07%
87.83%
69.46%
89.17%
91.48%
90.63%
57.42%
92.46%
2009
443
460
468
447
282
451
466
461
237
472
87.90%
91.27%
92.86%
88.69%
55.95%
89.48%
92.46%
91.47%
47.02%
93.65%
2010
% of 504 hospitals
450 89.29%
469 93.06%
483 95.83%
457 90.67%
324 64.29%
457 90.67%
476 94.44%
473 93.85%
278 55.16%
482 95.63%
2011
458
474
486
464
353
460
479
475
305
485
90.87%
94.05%
96.43%
92.06%
70.04%
91.27%
95.04%
94.25%
60.52%
96.23%
Table RP16
301–400 Beds
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
2009
297
310
315
300
202
303
313
309
173
312
90.55%
94.51%
96.04%
91.46%
61.59%
92.38%
95.43%
94.21%
52.74%
95.12%
2010
% of 328 hospitals
303 92.38%
317 96.65%
321 97.87%
309 94.21%
233 71.04%
308 93.90%
318 96.95%
315 96.04%
194 59.15%
319 97.26%
2011
306
318
321
312
252
312
318
315
205
319
93.29%
96.95%
97.87%
95.12%
76.83%
95.12%
96.95%
96.04%
62.50%
97.26%
Table RP17
401–500 Beds
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
2009
119
121
121
117
81
120
121
119
72
120
97.54%
99.18%
99.18%
95.90%
66.39%
98.36%
99.18%
97.54%
59.02%
98.36%
2010
% of 122 hospitals
119 97.54%
121 99.18%
121 99.18%
118 96.72%
92 75.41%
120 98.36%
121 99.18%
119 97.54%
77 63.11%
121 99.18%
2011
119
121
121
119
101
120
121
119
83
121
97.54%
99.18%
99.18%
97.54%
82.79%
98.36%
99.18%
97.54%
68.03%
99.18%
Table RP19
2009
Table RP15
201–300 Beds
501–600 Beds
2009
175
177
178
174
124
172
175
176
113
178
96.15%
97.25%
97.80%
95.60%
68.13%
94.51%
96.15%
96.70%
62.09%
97.80%
2010
% of 182 hospitals
176 96.70%
177 97.25%
179 98.35%
175 96.15%
132 72.53%
174 95.60%
177 97.25%
176 96.70%
124 68.13%
179 98.35%
2011
175
176
179
172
140
175
177
176
131
179
600+ Beds
Angiography
Computed Radiography (CR)
Computerized Tomography (CT)
Digital Fluoroscopy (DF)
Digital Mammography
Digital Radiography (DR)
Magnetic Resonance Imaging (MRI)
Nuclear Medicine
Orthopedic
Ultrasound (US)
2009
144 96.00%
148 98.67%
150 100.00%
142 94.67%
102 68.00%
144 96.00%
146 97.33%
146 97.33%
91 60.67%
150 100.00%
2010
% of 150 hospitals
147 98.00%
148 98.67%
150 100.00%
143 95.33%
115 76.67%
147 98.00%
148 98.67%
146 97.33%
108 72.00%
150 100.00%
2011
149 99.33%
148 98.67%
150 100.00%
145 96.67%
125 83.33%
147 98.00%
149 99.33%
146 97.33%
119 79.33%
150 100.00%
For most hospitals, R-PACS adoption is a recent phenomenon.
More than 90 percent of all R-PACS modalities were purchased
since 2000, with more than half of purchases occurring between
2005 and 2011 (see Tables RP20–RP23). No contract activity
occurred prior to 1995.
Table RP 20
2011
Angiography
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Computed Radiography (CR)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Computerized Tomography (CT)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
67
836
933
1,836
1,836
1,836
1,836
1,836
1,836
1,836
0.00%
0.00%
3.65%
45.53%
50.82%
100.00%
0
0
69
963
1,306
2,338
2,338
2,338
2,338
2,338
2,338
2,338
0.00%
0.00%
2.95%
41.19%
55.86%
100.00%
0
0
71
989
1,304
2,364
2,364
2,364
2,364
2,364
2,364
2,364
0.00%
0.00%
3.00%
41.84%
55.16%
100.00%
96.15%
96.70%
98.35%
94.51%
76.92%
96.15%
97.25%
96.70%
71.98%
98.35%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
63
▶▶ Radiology PACS con tinued
Table RP 21
2011
Digital Fluoroscopy (DF)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Digital Mammography
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Digital Radiography (DR)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
66
897
1,100
2,063
2,063
2,063
2,063
2,063
2,063
2,063
0.00%
0.00%
3.20%
43.48%
53.32%
100.00%
0
0
22
325
803
1,150
1,150
1,150
1,150
1,150
1,150
1,150
0.00%
0.00%
1.91%
28.26%
69.83%
100.00%
0
0
61
883
1,114
2,058
2,058
2,058
2,058
2,058
2,058
2,058
0.00%
0.00%
2.96%
42.91%
54.13%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
70
956
1,189
2,215
2,215
2,215
2,215
2,215
2,215
2,215
0.00%
0.00%
3.16%
43.16%
53.68%
100.00%
0
0
68
913
1,133
2,114
2,114
2,114
2,114
2,114
2,114
2,114
0.00%
0.00%
3.22%
43.19%
53.60%
100.00%
0
0
25
387
591
1,003
1,003
1,003
1,003
1,003
1,003
1,003
0.00%
0.00%
2.49%
38.58%
58.92%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
69
983
1,279
2,331
2,331
2,331
2,331
2,331
2,331
2,331
0.00%
0.00%
2.96%
42.17%
54.87%
100.00%
Table RP 22
2011
Magnetic Resonance Imaging (MRI)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Nuclear Medicine
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Orthopedic
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Table RP 23
2011
Ultrasound (US)
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
64 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Market Drivers/Future Outlook
The R-PACS IT application market will likely continue to
experience growth, albeit slow, driven by continued first-time
purchases among smaller hospitals and the early stages of
replacement purchases by the larger hospitals, including academic
medical centers and other early adopters. This market segment has
been, and will continue to be, impacted through 2015 by:
• Tough capital markets through at least 2013 that may slow
the growth of R-PACS modalities in hospitals where budget
competition between clinical and financial IT projects will
be increasingly competitive.
• However, this will be offset by increased demand to share
medical images between care providers in HIEs, a need that
will be driven by ARRA Stage 2 and Stage 3 meaningful use
requirements and bundled payment arrangements.
• Increased pressures on hospitals by federal and state authorities
to participate in HIE and public health reporting activities, or
the desire of IDNs to actively participate in private HIEs.
• As EMR adoption grows among owned, affiliated and other
ambulatory practices for which the hospital provides diagnostic
imaging services, demand for the electronic transmittal and
integration of images and reports from these practices will also
increase, thus driving some purchases to DICOM-compliant
products
• The increasing adoption of care delivery models that emphasize
care coordination, and reward participants for producing
improved clinical outcomes, reducing redundant testing, and
sharing results electronically.
• Ongoing demand to drive down radiology service and storage
costs and eliminate film costs for those hospitals that have a
minority of digital sourced modalities.
• The increasing demand for orthopedic pre-surgical templating
to improve quality related to implant surgery for a growing
elderly population.
• Ongoing market consolidation that will impact vendors and
products.
• Increasing consumer demands to have access to their medical
information and images.
▶▶ Cardiology PACS
Growth for the cardiology picture archive and communications
system (C-PACS) modalities tracked in this report was between
one to three percent in the past year (see Table CP1). While this
market continues to grow at a slower pace than the radiology
ACS (R-PACS) market, it has grown consistently over the past
several years.
With the exception of computerized tomography and intravascular
ultrasound, the majority of C-PACS modality purchases will be
among hospitals that are purchasing the technology for the first
time. Computerized tomography and intravascular ultrasound
purchase plans in 2011 are evenly split between first-time and
replacement purchases (see Table CP2).
Most of the C-PACS modalities exhibited slight to moderate growth
from 2010 to 2011 across all hospital types, but no segment had
Table CP1 | C-PACS
N=4,289
2009
2010
Cardiology – Cath Lab
27.07%
31.15%
Cardiology – CT (Computerized Tomography)
16.51%
19.93%
Cardiology – Echocardiology
26.21%
30.80%
Cardiology – Intravascular Ultrasound
15.64%
18.93%
Cardiology – Nuclear Cardiology
14.62%
18.16%
Percentage include installed, contracted or installation in process
2011
32.43%
22.24%
33.71%
21.38%
21.29%
more than five percent growth in the past year. The hospital
segments that showed the high growth by C-PACS modality were:
• Cath lab: medical/surgical hospitals showed the greatest growth
in the past year, at two percent. Declines in installation occurred
among academic/teaching hospitals and critical access hospitals
(see Table CP3).
• Computerized tomography: general medical/surgical hospitals
demonstrated the highest year-over-year increase at approximately
three percent. The other hospital segments indicated an increase
of one percent to two percent (see Table CP4).
• Echocardiology: general medical/surgical hospitals had the
most growth in the past year, at nearly four percent. The
remaining segments showed growth of one to three percent
(see Table CP5).
• Intravascular ultrasound: general medical/surgical and noncritical access segments are the only two hospitals segments that
showed a growth of more than three percent. All other segments
reported a growth of less than three percent (see Table CP6).
• Nuclear cardiology: the general medical/surgical segment
demonstrated the highest growth rate between 2010 and 2011, at
nearly five percent. After an increase of 10 percent from 2009 to
2010, the academic medical center segment reported a growth of
only one percent during this timeframe (see Table CP7).
Table CP 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Cardiology – Cath Lab
4
40.00%
Cardiology – CT (Computerized Tomography)
2
50.00%
Cardiology – Echocardiology
2
14.29%
Cardiology – Intravascular Ultrasound
1
50.00%
Cardiology – Nuclear Cardiology
3
37.50%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
First time = Status of not automated
# of Hospitals Planning
to Purchase Software
for the First Time
6
2
12
1
5
% of Hospitals Planning
to Purchase Software
for the First Time
60.00%
50.00%
85.71%
50.00%
62.50%
N = Total Number of
Hospitals Planning
10
4
14
2
8
Table CP 3 | Cardiology – Cath Lab
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
133
1,028
955
206
17
1,144
12
1,149
851
310
1,161
Percent
69.27%
25.09%
38.09%
11.56%
1.47%
36.50%
1.19%
35.01%
32.91%
18.20%
27.07%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
151
1,185
1,110
226
20
1,316
19
1,317
969
367
1,336
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
98
757
686
169
41
814
23
832
614
241
855
Percent
78.65%
28.92%
44.28%
12.68%
1.73%
41.99%
1.89%
40.13%
37.47%
21.55%
31.15%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
150
1,241
1,165
226
19
1,372
19
1,372
992
399
1,391
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
103
851
772
182
47
907
29
925
683
271
954
Percent
78.13%
30.29%
46.47%
12.68%
1.65%
43.78%
1.89%
41.80%
38.36%
23.43%
32.43%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table CP4 | Cardiology – CT (Computerized Tomography)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
87
621
558
150
33
675
18
690
516
192
708
Percent
45.31%
15.16%
22.26%
8.42%
2.86%
21.54%
1.79%
21.02%
19.95%
11.27%
16.51%
2010
Percent
51.04%
18.48%
27.36%
9.48%
3.55%
25.97%
2.28%
25.35%
23.74%
14.15%
19.93%
2011
Source: HIMSS Analytics® Database 2011
Percent
53.65%
20.77%
30.79%
10.21%
4.07%
28.94%
2.88%
28.18%
26.41%
15.91%
22.24%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
©2012 HIMSS Analytics.
65
▶▶ Cardiology PACS con tinued
Table CP5 | Cardiology – Echocardiology
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
125
999
889
235
53
1,071
29
1,095
789
335
1,124
Percent
65.10%
24.38%
35.46%
13.19%
4.59%
34.17%
2.88%
33.36%
30.51%
19.67%
26.21%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
144
1,177
1,053
268
69
1,252
46
1,275
913
408
1,321
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
102
710
656
156
26
786
20
792
567
245
812
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
99
680
616
163
35
744
26
753
532
247
779
Percent
75.00%
28.73%
42.00%
15.04%
5.97%
39.95%
4.57%
38.85%
35.31%
23.96%
30.80%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
145
1,301
1,151
295
89
1,357
64
1,382
983
463
1,446
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
106
811
745
172
33
884
28
889
638
279
917
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
101
812
735
178
46
867
39
874
616
297
913
Percent
75.52%
31.75%
45.91%
16.55%
7.71%
43.30%
6.36%
42.11%
38.01%
27.19%
33.71%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table CP 6 | Cardiology – Intravascular Ultrasound
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
86
585
532
139
24
647
12
659
471
200
671
Percent
44.79%
14.28%
21.22%
7.80%
2.08%
20.64%
1.19%
20.08%
18.21%
11.74%
15.64%
2010
Percent
53.13%
17.33%
26.17%
8.75%
2.25%
25.08%
1.99%
24.13%
21.93%
14.39%
18.93%
2011
Percent
55.21%
19.79%
29.72%
9.65%
2.86%
28.21%
2.78%
27.09%
24.67%
16.38%
21.38%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table CP7 | Cardiology – Nuclear Cardiology
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
79
548
492
135
26
601
13
614
441
186
627
Percent
41.15%
13.38%
19.63%
7.58%
2.25%
19.18%
1.29%
18.71%
17.05%
10.92%
14.62%
2010
The evaluation of the C-PACS market by bed-size segments
for 2011 shows that the C-PACS modalities with the highest
year-over-year growth for each bed segment are outlined below
(see Tables CP8–CP14):
• 0–100 beds: there was very little growth among these hospitals;
echocardiology indicated the highest year-over-year growth at
almost two percent (see Table CP8).
• 101–200 beds: echocardiology and nuclear cardiology
indicated growth at more than three percent from 2010 to
2011 (see Table CP9).
• 201–300 beds: all C-PACS modalities in this bed category
indicated a moderate increase (five to seven percent) in the
past year (see Table CP10).
• 301–400 beds: growth for the modalities in this bed-size category
was between three and four percent; the greatest growth was for
the echocardiology modality (see Table CP11).
• 401–500 beds: intravascular ultrasound and nuclear cardiology
each had growth of nearly five percent; the remaining modalities
grew at a rate of less than four percent (see Table CP12).
66 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
51.56%
16.60%
24.57%
9.15%
3.03%
23.74%
2.58%
22.94%
20.57%
14.50%
18.16%
2011
Percent
52.60%
19.82%
29.32%
9.99%
3.98%
27.66%
3.87%
26.63%
23.82%
17.44%
21.29%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
• 501–600 beds: growth for all modalities in this bed segment
was between three and four percent, with the exception of
cath lab, which demonstrated growth of less than one percent
(see Table CP13).
• Over 600 beds: the largest year-over-year growth in this bed
segment was demonstrated by the nuclear cardiology and
computerized tomography modalities, each at more than
six percent (see Table CP14).
Two-thirds of the C-PACS growth took place between 2005 and
2011, suggesting that this market has entered the rapid adoption
stage of purchasing activity (see Tables CP15–CP16). Digital
imaging modalities of all types will continue to multiply over the
next several years as the industry embraces various forms of health
information exchange. The highly competitive market of cardiology
and cardiac surgery along with an aging population with heart
disease will continue to drive this market for the foreseeable future.
In addition, as EMR deployments continue the current growth in
all market segments, the need to have all images accessible to the
EMR will continue to drive the market for C-PACS.
▶▶ Cardiology PACS con tinued
Table CP 8
0–100 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
Table CP15
2009
96
2010
2011
% of 2,181 Hospitals
4.40%
126
5.78%
129
5.91%
90
150
4.13%
6.88%
106
192
4.86%
8.80%
125
234
5.73%
10.73%
73
77
3.35%
3.53%
89
100
4.08%
4.59%
111
137
5.09%
6.28%
Table CP 9
101–200 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
279
2010
% of 822 hospitals
33.94%
328 39.90%
2011
338
41.12%
164
262
19.95%
31.87%
215
321
26.16%
39.05%
239
348
29.08%
42.34%
155
138
18.86%
16.79%
190
185
23.11%
22.51%
210
215
25.55%
26.16%
Table CP10
201–300 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
242
2010
% of 504 hospitals
48.02%
284 56.35%
2011
311
61.71%
134
207
26.59%
41.07%
167
252
33.13%
50.00%
194
280
38.49%
55.56%
127
113
25.20%
22.42%
158
144
31.35%
28.57%
190
179
37.70%
35.52%
Table CP11
301–400 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
203
2010
% of 328 hospitals
61.89%
225 68.60%
2011
234
71.34%
110
189
33.54%
57.62%
133
210
40.55%
64.02%
143
224
43.60%
68.29%
111
111
33.84%
33.84%
139
132
42.38%
40.24%
149
141
45.43%
42.99%
Table CP12
401–500 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
134
2010
% of 182 hospitals
73.63%
144 79.12%
2011
147
80.77%
82
124
45.05%
68.13%
90
131
49.45%
71.98%
96
138
52.75%
75.82%
78
71
42.86%
39.01%
89
79
48.90%
43.41%
98
87
53.85%
47.80%
Table CP13
501–600 Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
94
2010
% of 122 hospitals
77.05%
105 86.07%
58
89
47.54%
72.95%
65
96
57
56
46.72%
45.90%
64
66
2011
106
86.89%
53.28%
78.69%
69
99
56.56%
81.15%
52.46%
54.10%
68
71
55.74%
58.20%
Table CP14
600+ Beds
Cardiology – Cath Lab
Cardiology – CT (Computerized
Tomography)
Cardiology – Echocardiology
Cardiology – Intravascular
Ultrasound
Cardiology – Nuclear Cardiology
2009
113
2010
% of 150 hospitals
75.33%
124 82.67%
2011
126
84.00%
70
103
46.67%
68.67%
79
119
52.67%
79.33%
88
123
58.67%
82.00%
70
61
46.67%
40.67%
83
73
55.33%
48.67%
91
83
60.67%
55.33%
# for Contract
2011
Range
Cardiology – Cath Lab
Prior to 1990
0
1990 to 1994
1
1995 to 1999
12
2000 to 2004
163
2005 to 2011
345
Total
521
Cardiology – CT (Computerized Tomography)
Prior to 1990
0
1990 to 1994
0
1995 to 1999
8
2000 to 2004
93
2005 to 2011
205
Total
306
Cardiology – Echocardiology
Prior to 1990
0
1990 to 1994
1
1995 to 1999
11
2000 to 2004
143
2005 to 2011
364
Total
519
Total
Responding
% of Total
Responding
521
521
521
521
521
521
0.00%
0.19%
2.30%
31.29%
66.22%
100.00%
306
306
306
306
306
306
0.00%
0.00%
2.61%
30.39%
66.99%
100.00%
519
519
519
519
519
519
0.00%
0.19%
2.12%
27.55%
70.13%
100.00%
# for Contract
Range
Total
Responding
% of Total
Responding
0
0
8
95
219
322
322
322
321
321
321
322
0.00%
0.00%
2.48%
29.50%
68.01%
100.00%
0
0
7
95
213
315
315
315
315
315
315
315
0.00%
0.00%
2.22%
30.16%
67.62%
100.00%
Table CP16
2011
Cardiology – Intravascular Ultrasound
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Cardiology – Nuclear Cardiology
Prior to 1990
1990 to 1994
1995 to 1999
2000 to 2004
2005 to 2011
Total
Market Drivers/Future Outlook
Despite the near-term mixed outlook for capital budgets, which will
tend to moderate demand, the prospects for long-term growth in this
market segment are very positive. The C-PACS IT application
market has been and will continue to be impacted in the future by:
• The demand to increase medical image sharing among providers
in an EMR environment.
• The demand to share medical images within emerging healthcare
information exchanges.
• The highly competitive landscape for cardiology and cardiac
surgery and the ability to recruit recent residency graduates who
have been users of C-PACS.
• The demand to decrease costs for medical imaging services.
• The increased acceptance and adoption of standards that will
facilitate the capture, rendering, and transmission of medical
images across digital imaging modalities and between vendor
PACS solutions.
• Continued favorable cost trends for on-line and archival storage,
including the impact of storage virtualization technologies.
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
67
▶▶ Bar Code Technology
In the past year, all of the bar code technologies tracked in this
report showed at least some growth. In 2011, the adoption of bar
coding technologies in laboratory was highest at 84 percent,
followed by pharmacy administration (67 percent) and radiology
(50 percent). The increase in adoption of bar coding technology
was greatest for medication administration and pharmacy
administration. Each of these areas experienced five percent
growths in the past year (see Table BC1). At less than one percent,
growth was smallest for the use of technology for radiology.
Patient registration applications will continue to grow as bar
coding at patient registration is essential for, and directly related
to, growth in the use of bar coding to support point-of-care
medication administration.
Future adoption of bar coding technologies is projected to be
greatest for the use of medication administration (see Table BC2).
Use of these bar coding technologies will continue to be
implemented for the purpose of the “five rights” of medication
administration (right patient, right dose, right drug, right time and
right route) in order to improve patient safety. The closed loop
Table BC1 | Bar Coding (Current)
N=4,289
Fixed Assets/Equipment
Tracking
Laboratory
Materials Management
Medication Administration
Patient Registration
Pharmacy Administration
Radiology
2009
Count Percent
Count
2010
Percent
Count
2011
Percent
109
3387
1867
1725
289
2343
2002
163
3514
2020
1897
394
2642
2124
3.80%
81.93%
47.10%
44.23%
9.19%
61.60%
49.52%
210
3591
2144
2133
503
2874
2154
4.90%
83.73%
49.99%
49.73%
11.73%
67.01%
50.22%
2009
Count Percent
Count
2010
Percent
Count
2011
Percent
41
209
298
1464
78
1017
129
62
194
326
1580
93
928
139
1.45%
4.52%
7.60%
36.84%
2.17%
21.64%
3.24%
96
209
353
1490
122
866
145
2.24%
4.87%
8.23%
34.74%
2.84%
20.19%
3.38%
2.54%
78.97%
43.53%
40.22%
6.74%
54.63%
46.68%
Table BC 2 | Bar Coding (Planned)
N=4,289
Fixed Assets/Equipment
Tracking
Laboratory
Materials Management
Medication Administration
Patient Registration
Pharmacy Administration
Radiology
0.96%
4.87%
6.95%
34.13%
1.82%
23.71%
3.01%
68 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
medication administration process is included in Stage 5 of the
HIMSS Analytics EMR Adoption ModelSM. This is the most
complex and demanding level of hospital IT transformation as
it requires the tight coupling of data between CPOE systems,
pharmacy, and nursing documentation applications, along with
integrated bar code processing of medication transactions at the
point of care. We believe some attributes associated with
automated medication administration can be expected to appear
in the Stage 2 meaningful use requirements, as the ARRA law
calls for “advanced clinical processes.”
Market Drivers/Future Outlook
The bar code technology market has been and will continue to
be impacted through 2015 by:
• The drive for hospitals to implement the “five rights” of
medication administration and to improve patient safety through
information technology.
• The drive for hospitals to implement the “five rights” of
medication administration and to improve nurse satisfaction and
patient and family confidence.
• Anticipated Stage 2 ARRA meaningful use requirements which
are expected to require some aspects of closed loop medication
administration processes.
• The need to more effectively manage patient tracking and patient
flows.
• The desire to improve supply chain management functions
throughout the hospital to reduce inventory and management
costs.
• Though a nascent market now, asset tracking and real-time
location tracking with also drive some bar code technology
adoption.
• The lack of consistent standards for the technology of materials
packaging and medication packaging.
• The integration overhead of integrating bar code technology
with healthcare IT applications if the technology is purchased
separately from the underlying application it supports.
• However, the adoption of RFID technologies in patient tracking
and material management may begin to reduce some growth
of bar code technologies in these applications over the next
several years.
▶▶ Electronic Medical Record Environment
The electronic medical record environment includes six
applications. These applications have the ability to significantly
impact clinical outcomes, cost and patient safety for hospitals if
implemented as part of a comprehensive change management
process and used directly by all clinicians, including physicians.
While nursing applications are also part of the EMR suite, we
have broken them out for separate analysis (please refer to the
Nursing IT section for additional information).
In 2011, order entry and clinical data repository are approaching
market saturation (between 90 percent and 95 percent). The order
entry application may become obsolete as hospitals continue to
replace legacy order entry applications with new generation CPOE
applications that can accommodate patient orders from all clinicians
supported by clinical decision support. In support of this, all of
the EMR applications showed growth, with the highest increases
for CPOE (11 percent for the second year in a row), physician
documentation (eight percent) and physician portal (nearly eight
percent). The remaining three applications indicated growth
ranging from one percent to three percent (see Table EMR1).
The EMR environment is a mix of first-time and replacement
purchases; the majority of purchasing plans for clinical decision
support, clinical data repository and order entry will replace
existing solutions. Future purchases of CPOE, physician
documentation and physician portal will largely be done by
hospitals that are purchasing the applications for the first time
(see Table EMR2).
An evaluation of hospital-type market segment growth from 2010 to
2011 shows the highest growth by application occurred as follows:
• Clinical data repository: the greatest growth in this application
from 2010 to 2011 was among the rural hospitals and critical
access hospitals that are adopting this technology for the first
time, mostly; each segment saw approximately six percent
growth in the past year (see Table EMR3). All other segments,
except academic medical centers, reported low to moderate
growth, ranging from one percent to more than five percent. The
academic medical centers’ adoption rate remained unchanged
over the past year.
• Clinical decision support: the critical access and rural segments
each demonstrated an increase of more than six percent from
•
•
•
•
2010 to 2011 (see Table EMR4). There was a slight decrease in
the use of this technology among academic medical centers;
however, this decrease was not statistically relevant.
CPOE: over the past year, the implementation of CPOE increased
by approximately 10 percent in all segments with the exception of
academic medical centers and hospitals from multi-hospital
systems (see Table EMR5). Hospitals from single hospital systems
reported the most growth at nearly 17 percent.
Order entry: order entry is a saturated market in nearly all of the
segments tracked in this report (see Table EMR6). The highest growth
in the past year was among critical access hospitals, at slightly more
than four percent. With the exception of academic medical centers
in which no growth was demonstrated, growth among the other
market segments was between one and three percent.
Physician documentation: all hospital segments demonstrated
moderate to healthy growth with more than 10 percent growth
for critical access hospitals, single hospital systems, and rural
hospitals (see Table EMR7). The segment that demonstrated the
least growth was academic medical centers, at four percent.
Physician portal: academic medical center segment is the only
hospital segment that indicated growth less than seven percent
(see Table EMR8). All other segments indicated moderate growth
with rural hospitals demonstrating the largest year-over-year
growth at slightly less than 10 percent.
In 2011, hospitals that are generally smaller and located in rural
areas are adopting physician-focused applications (e.g., CPOE,
physician documentation, physician portal) at a higher rate. Most of
this is due to the ARRA meaningful use and the access to the
incentives by meeting the meaningful criteria, allowing for these
segments to “catch up” to the higher market penetration rates in
academic medical centers and multi-hospital systems.
Table E MR1 | Electronic Medical Record
N=4,289
2009
2010
Clinical Data Repository
87.06%
88.32%
Clinical Decision Support
80.74%
85.80%
Computerized Practitioner Order Entry (CPOE)
45.63%
56.45%
Order Entry (includes Order Communication)
90.81%
91.68%
Physician Documentation
43.04%
52.88%
Physician Portal
28.40%
42.78%
Percentages include installed, contracted or installation in process
2011
91.09%
88.62%
67.59%
93.61%
61.25%
50.55%
Table E MR 2 | 2011
# of Hospitals
% of Hospitals
with Installed
with Installed
Software–Replacing
Software–Replacing
Clinical Data Repository
65
67.01%
Clinical Decision Support
70
67.96%
Computerized Practitioner Order Entry (CPOE)
51
30.00%
Order Entry (includes Order Communications)
67
70.53%
Physician Documentation
50
33.33%
Physician Portal
8
25.81%
Replacing = Statuses of live & operational, contracted/not yet installed and installation in process
# of Hospitals Planning
to Purchase Software
for the First Time
32
33
119
28
100
23
% of Hospitals Planning
to Purchase Software
for the First Time
32.99%
32.04%
70.00%
29.47%
66.67%
74.19%
Source: HIMSS Analytics® Database 2011
N = Total Number of
Hospitals Planning
97
103
170
95
150
31
©2012 HIMSS Analytics.
69
▶▶ Electronic Medical Record Environment con tinued
Table emr3 | Clinical Data Repository
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
190
3,544
2,372
1,362
777
2,957
677
3,057
2,418
1,316
3,734
Percent
98.96%
86.50%
94.62%
76.43%
67.27%
94.35%
67.23%
93.14%
93.50%
77.28%
87.06%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,597
2,385
1,403
815
2,973
722
3,066
2,426
1,362
3,788
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
188
3,492
2,349
1,331
814
2,866
727
2,953
2,339
1,341
3,680
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
172
2,249
1,465
956
452
1,969
382
2,039
1,635
786
2,421
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,741
2,423
1,509
910
3,022
817
3,115
2,469
1,463
3,932
Percent
99.48%
87.80%
95.13%
78.73%
70.56%
94.86%
71.70%
93.42%
93.81%
79.98%
88.32%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,716
2,413
1,494
891
3,016
790
3,117
2,457
1,450
3,907
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
187
3,614
2,394
1,407
885
2,916
788
3,013
2,376
1,425
3,801
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
177
2,722
1,748
1,151
629
2,270
523
2,376
1,826
1,073
2,899
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
191
3,824
2,449
1,566
959
3,056
851
3,164
2,503
1,512
4,015
Percent
99.48%
90.70%
96.25%
83.84%
77.14%
96.23%
78.45%
94.97%
95.01%
85.14%
91.09%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table emr4 | Clinical Decision Support
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
184
3,279
2,250
1,213
715
2,748
630
2,833
2,250
1,213
3,463
Percent
95.83%
80.03%
89.75%
68.07%
61.90%
87.68%
62.56%
86.32%
87.01%
71.23%
80.74%
2010
Percent
97.92%
85.23%
93.70%
74.69%
70.48%
91.45%
72.19%
89.98%
90.45%
78.74%
85.80%
2011
Percent
97.40%
88.21%
95.49%
78.96%
76.62%
93.04%
78.25%
91.80%
91.88%
83.68%
88.62%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table emr5 | Computerized Practitioner Order Entry (CPOE)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
160
1,797
1,262
695
319
1,638
248
1,709
1,378
579
1,957
Percent
83.33%
43.86%
50.34%
39.00%
27.62%
52.27%
24.63%
52.07%
53.29%
34.00%
45.63%
2010
Percent
89.58%
54.89%
58.44%
53.65%
39.13%
62.83%
37.93%
62.13%
63.23%
46.15%
56.45%
2011
Percent
92.19%
66.44%
68.72%
64.59%
54.46%
72.43%
51.94%
72.39%
70.61%
63.01%
67.59%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Table emr6 | Order Entry (Includes Order Communication)
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
191
3,704
2,432
1,463
867
3,028
775
3,120
2,466
1,429
3,895
Percent
99.48%
90.41%
97.01%
82.10%
75.06%
96.62%
76.96%
95.06%
95.36%
83.91%
90.81%
2010
70 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Percent
99.48%
91.31%
96.65%
84.68%
78.79%
96.43%
81.13%
94.91%
95.48%
85.91%
91.68%
2011
Percent
99.48%
93.34%
97.69%
87.88%
83.03%
97.51%
84.51%
96.40%
96.79%
88.78%
93.61%
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
▶▶ Electronic Medical Record Environment con tinued
Table emr7 | Physician Documentation
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
133
1,713
1,220
626
302
1,544
245
1,601
1,284
562
1,846
Percent
69.27%
41.81%
48.66%
35.13%
26.15%
49.27%
24.33%
48.78%
49.65%
33.00%
43.04%
2010
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
157
2,111
1,405
863
391
1,877
337
1,931
1,557
711
2,268
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
127
1,708
1,313
522
281
1,554
250
1,585
1,260
575
1,835
Percent
81.77%
51.53%
56.04%
48.43%
33.85%
59.89%
33.47%
58.84%
60.21%
41.75%
52.88%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
165
2,462
1,639
988
512
2,115
441
2,186
1,731
896
2,627
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Segment
Count
136
2,032
1,509
659
382
1,786
349
1,819
1,456
712
2,168
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
85.94%
60.09%
65.38%
55.44%
44.33%
67.49%
43.79%
66.61%
66.94%
52.61%
61.25%
Table emr8 | Physician Portal
2009
Type
Academic/Teaching
Non-Academic
Med/Surg
Other
Critical Access
Non-Critical Access
Rural
Urban
Multi-Hospital System
Single Hospital System
All
Segment
Count
81
1,137
884
334
171
1,047
131
1,087
862
356
1,218
Percent
42.19%
27.75%
35.26%
18.74%
14.81%
33.41%
13.01%
33.12%
33.33%
20.90%
28.40%
2010
The analysis of the EMR market by bed size in 2011 indicates the
following (see Tables EMR9–EMR15):
• 0–100 beds: at nearly 13 percent, CPOE demonstrated the highest
growth for this segment, followed by physician documentation and
physician portal, both at more than eight percent (see Table EMR9).
• 101–200 beds: this segment reported growth across all EMR
applications, with CPOE indicating the highest year-over-year
increase at more than 10 percent followed by physician
documentation at slightly under 10 percent (see Table EMR10).
• 201–300 beds: CPOE, physician portal, and physician
documentation demonstrated the strongest growth in the past
year; each demonstrated growth of more than seven percent.
All other EMR applications showed growth under one percent
(see Table EMR11).
• 301–400 beds: more than 11 percent growth was reported for
CPOE in this bed segment. Growth for physician portal and
physician documentation was also strong, at six and seven percent
respectively (see Table EMR12).
• 401–500 beds: physician documentation had the highest growth
at seven percent while clinical data repository, clinical decision
support, and order entry remained unchanged from last year.
Physician portal and CPOE reported changes from five to seven
percent (see Table EMR13).
• 501–600 beds: CPOE had a growth of more than five percent in
this segment, followed by physician documentation (four percent)
and physician portal (three percent) (see Table EMR 14).
• 600+ beds: physician portal demonstrated the most growth in this
segment at nearly nine percent, followed by physician documentation
(seven percent) and CPOE at nearly five percent. All other
applications remained unchanged from 2010 (see Table EMR15).
Percent
66.15%
41.69%
52.37%
29.29%
24.33%
49.59%
24.83%
48.29%
48.72%
33.76%
42.78%
2011
Total
Count
192
4,097
2,507
1,782
1,155
3,134
1,007
3,282
2,586
1,703
4,289
Percent
70.83%
49.60%
60.19%
36.98%
33.07%
56.99%
34.66%
55.42%
56.30%
41.81%
50.55%
Table E MR9
0–100 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
2009
1680
1,521
2010
2011
% of 2,181 Hospitals
77.03% 1,731 79.37% 1,842 84.46%
69.74% 1,672 76.66% 1,774 81.34%
729
33.43%
1,024
46.95%
1,299
59.56%
1,821
694
390
83.49%
31.82%
17.88%
1,868
934
633
85.65%
42.82%
29.02%
1,941
1,120
817
89.00%
51.35%
37.46%
Table E MR10
101–200 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
2009
780
738
2010
% of 822 hospitals
94.89%
779 94.77%
89.78%
761 92.58%
2011
786
772
95.62%
93.92%
384
46.72%
456
55.47%
546
66.42%
797
389
278
96.96%
47.32%
33.82%
790
455
404
96.11%
55.35%
49.15%
797
535
466
96.96%
65.09%
56.69%
Table E MR11
201–300 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
2009
493
466
2010
% of 504 hospitals
97.82%
496 98.41%
92.46%
487 96.63%
497
497
98.61%
97.62%
297
58.93%
345
68.45%
393
77.98%
498
301
185
98.81%
59.72%
36.71%
495
341
279
98.21%
67.66%
55.36%
498
380
321
98.81%
75.40%
63.69%
Source: HIMSS Analytics® Database 2011
2011
©2012 HIMSS Analytics.
71
▶▶ Electronic Medical Record Environment con tinued
Table E MR12
301–400 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
Table E MR16
2009
327
301
2010
% of 328 hospitals
99.70%
328 100.00%
91.77%
314 95.73%
2011
328 100.00%
317 96.65%
206
62.80%
231
70.43%
270
82.32%
326
174
145
99.39%
53.05%
44.21%
327
202
206
99.70%
61.59%
62.80%
326
227
225
99.39%
69.21%
68.80%
Table E MR13
401–500 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
2009
2010
% of 182 hospitals
182 100.00%
182 100.00%
179 98.35%
179 98.35%
2011
182 100.00%
179 98.35%
123
67.58%
138
75.82%
150
82.42%
181
105
94
99.45%
57.69%
51.65%
180
118
130
98.90%
64.84%
71.43%
181
131
139
99.45%
71.98%
76.37%
Table E MR14
501–600 Beds
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
2009
2010
% of 122 hospitals
122 100.00%
122 100.00%
114 93.44%
121 99.18%
96
78.69%
122 100.00%
81 66.39%
59 48.36%
99
81.15%
122 100.00%
96 78.69%
85 69.67%
Clinical Data Repository
Clinical Decision Support
Computerized Practitioner
Order Entry (CPOE)
Order Entry (includes Order
Communications)
Physician Documentation
Physician Portal
106
86.89%
122 100.00%
101 82.79%
89 72.95%
2010
% of 150 hospitals
150 100.00%
150 100.00%
144 96.00%
146 97.33%
150 100.00%
146 97.33%
122
135
150 100.00%
102 68.00%
67 44.67%
128
85.33%
150 100.00%
122 81.33%
98 65.33%
% of Total
Responding
2,637
2,637
2,637
2,637
2,637
2,637
0.83%
6.48%
17.56%
34.17%
40.96%
100.00%
2,328
2,328
2,328
2,328
2,328
2,328
0.86%
6.66%
16.37%
30.93%
45.19%
100.00%
1,808
1,808
1,808
1,808
1,808
1,808
0.11%
4.81%
3.37%
28.48%
63.22%
100.00%
Total
Responding
% of Total
Responding
2,932
2,932
2,932
2,932
2,932
2,932
1.84%
11.05%
18.45%
32.30%
36.36%
100.00%
1,651
1,651
1,651
1,651
1,651
1,651
0.30%
8.84%
3.45%
26.89%
60.51%
100.00%
598
598
598
598
598
598
0.00%
0.84%
3.51%
17.39%
78.26%
100.00%
Table E MR17
122 100.00%
121 99.18%
2009
81.33%
Total
Responding
2011
Table E MR15
600+ Beds
# for Contract
2011
Range
Clinical Data Repository
Prior to 1990
22
1990 to 1994
171
1995 to 1999
463
2000 to 2004
901
2005 to 2011
1,080
Total
2,637
Clinical Decision Support
Prior to 1990
20
1990 to 1994
155
1995 to 1999
381
2000 to 2004
720
2005 to 2011
1,052
Total
2,328
Computerized Practitioner Order Entry (CPOE)
Prior to 1990
2
1990 to 1994
87
1995 to 1999
61
2000 to 2004
515
2005 to 2011
1,143
Total
1,808
2011
90.00%
150 100.00%
133 88.67%
111 74.00%
More than two thirds of the contracting for all applications in this
suite took place in 2000 or later (see Tables EMR16–EMR17).
However, the majority of CPOE, physician documentation and
physician portals (60 percent or more) took place in 2005 or later.
The availability of meaningful use incentives will continue to drive
higher rates of adoption for applications in this suite over the next
several years, as hospitals strive to meet meaningful use Stage 1
and Stage 2 criteria.
Market Drivers/Future Outlook
The EMR environment market has been or will likely be impacted
through 2015 by:
• An increased focus on complying with ARRA meaningful use
Stage 1 and Stage 2 requirements and reporting criteria in order
to qualify for EMR adoption incentives and avoid Medicare
reimbursement penalties.
• The increased need to acquire, manage, and analyze clinical data for
business intelligence, outcomes improvement, pay for performance
incentive programs and government compliance reporting.
• Increased hiring of hospitalists who are expected to use CPOE and
physician documentation applications as a condition of employment.
72 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
# for Contract
2011
Range
Order Entry (includes Order Communications)
Prior to 1990
54
1990 to 1994
324
1995 to 1999
541
2000 to 2004
947
2005 to 2011
1,066
Total
2,932
Physician Documentation
Prior to 1990
5
1990 to 1994
146
1995 to 1999
57
2000 to 2004
444
2005 to 2011
999
Total
1,651
Physician Portal
Prior to 1990
0
1990 to 1994
5
1995 to 1999
21
2000 to 2004
104
2005 to 2011
468
Total
598
• Increased purchasing of physician practices who are expected
to use CPOE and physician documentation applications as a
condition of purchase and employment.
• Increased pressures on hospitals by federal and state authorities
to participate in HIE and public health reporting activities, or the
desire of IDNs to actively participate in private HIEs.
• Intense competition for capital funding, and staff resources
between financial (e.g., version 5010 EDI transaction mandate,
ICD-10-PCS coding mandate) and clinical (e.g., ARRA
meaningful use measurements) IT projects.
• Tight capital markets may continue to impact the acquisition and
installation of EMR products through 2015, especially for small
community and critical access hospitals, in spite of the
availability of ARRA incentives.
• The continued resistance of attending physicians in a competitive
community hospital environment to the adoption and use of
CPOE and physician documentation applications.
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation
The terms electronic medical record (EMR) and electronic health
record (EHR) are frequently used interchangeably. Despite the
government’s preferred use of the term EHR, these terms, while
similar, are not synonymous. It is our opinion that these terms
describe completely different concepts, both of which are crucial
to the success of local, regional, and national goals to improve
patient safety, improve the quality and efficiency of patient care,
and reduce healthcare delivery costs. This will continue to be of
utmost importance through 2015, the timeframe during which the
HITECH provisions in the American Recovery and Reinvestment
Act (ARRA) will be available to subsidize EMR implementations
across many different care settings.
The International Organization for Standardization Technical
Committee 215 (ISO/TC 215) has created an EHR classification
document that uses three terms to differentiate these environments
in order to bring some clarity to the use of this terminology in the
industry. These three terms are the Local EHR, the Shared EHR
and the Integrated Care EHR. The Local EHR is defined as the
EMR within a hospital or clinic that is the legal medical record for
that entity (LEHR). The Shared EHR is an EMR that supports both
inpatient and outpatient environments (SEHR). The Integrated Care
EHR refers to the ability to share summary patient information
between and across all healthcare modalities (ICEHR). ICEHRs
rely on the presence of LEHRs and SEHRs to create and share
patient information in order to be able to support emerging health
information exchange (HIE) environments. Because of the rapid
evolution and deployment of these applications, it is critically
important to understand the differences, and to reduce confusion
in the market.
ISO defines an EHR as “a healthcare record in computer
processable format.” The LEHR is the legal record created in
hospitals or ambulatory environments and the SEHR is an
enterprise EMR that supports both inpatient and outpatient
environments for multiple provider settings under one enterprise
umbrella. In various combinations, both LEHRs and SEHRs can be
the source of data for ICEHRs. An ICEHR provides the ability to
readily share summary medical information among stakeholders
from multiple provider enterprises and to have a patient’s
information precede and follow him or her through the various
modalities of care providing care to that individual.
as the lack of a standard CMV to define the data within the CCD.
If history is any indicator, the government will need to continue to
drive adoption and use of CCD and a CMV through a combination
of federal mandates, regulatory penalties and incentives, and the
underwriting of demonstration and pilot projects. Provisions to
encourage the exchange of patient information across the healthcare
delivery ecosystem and funding to create and propagate the standards
to facilitate that exchange are well-defined in the HITECH sections
of ARRA. The impending standard, due in early 2012, for the
Nationwide Health Information Exchanges (NwHIN) is a step in
the right direction. The beginnings of such initiatives are already a
part of Stage 1 meaningful use and are expected to become an even
stronger focus of the Stage 2 and Stage 3 of meaningful use criteria.
Such initiatives have also been evident in the grant awards made
by the Office of the National Coordinator for Health Information
Technology (ONC), the National Institute of Standards and
Technology (NIST) and other, similar federal agencies in 2010 and
in 2011. We believe this type of activity will increase over the next
one to five years to facilitate the ultimate goal of clinical results
information exchange to reduce consumption.
Before we can start sharing encounter summary information
among providers and consumers, care delivery organizations
must implement complete EMR solutions so that they possess the
discrete electronic data required to create patient summaries to
share with the other stakeholders which conform to standards of
interoperability. At this point, HIMSS Analytics data shows that
there is increasing momentum in the upper levels of the EMRAM,
Stages 5 and 6, so that hospitals will have EMR solutions that
can share information with other stakeholders in the manner
envisioned, and articulated, by the government.
The EMR Adoption ModelSM (EMRAM) was developed by
HIMSS Analytics to assess the status of clinical system/EMR
implementations in care delivery organizations (CDOs), specifically
hospitals. This model, which uses an algorithm to score more than
5,300 hospitals in the U.S., demonstrates consistent upward
momentum among U.S. hospitals (see Figure EMRAM1).
Figure EMRAM1: US EMR Adoption Model
SM
Stage
Cumulative Capabilities
2010
Final
2011
Q3
HIEs will serve as the conduit for sharing summary records of
care between all modalities of patient care. Stakeholders are
composed of patients/consumers, healthcare providers, employers,
and/or payers/insurers/quality reviewers, including the government.
A key enabler for the sharing of secure patient information among
stakeholders is the ability of the industry to adopt the continuum
of care document (CCD) transaction standard in a way that also
uses a controlled medical vocabulary (CMV) so that discrete data
in the CCD transaction can be instantly recognized by any
receiving LEHR.
Stage 7
Complete EMR; CCD transactions to share data; Data
warehousing; Data continuity with ED, ambulatory, OP
1.0%
1.1%
Stage 6
Physician documentation (structured templates),
full CDSS (variance & compliance), full R-PACS
3.2%
4.4%
Stage 5
Closed loop medication administration
4.5%
7.1%
Stage 4
CPOE, Clinical Decision Support (clinical protocols)
10.5%
13.2%
Stage 3
Nursing/clinical documentation (flow sheets), CDSS
(error checking), PACS available outside Radiology
49.0%
46.1%
Stage 2
CDR, Controlled Medical Vocabulary, CDS, may have
Document Imaging; HIE capable
14.6%
12.6%
We appear to be three to five years away from these capabilities,
not because of the technologies, but because of the industry’s rate of
adoption of both EMRs and the CCD transaction standard, as well
Stage 1
Ancillaries - Lab, Rad, Pharmacy - All Installed
7.1%
5.9%
Stage 0
All Three Ancillaries Not Installed
10.1%
9.6%
N = 5,281
N = 5,299
Data from HIMSS Analytics® Database ©2011
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
73
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation con tinued
EMR Adoption ModelSM: An EMR Market Transformation Assessment Tool
The stages of the model are as follows:
Stage 0: Some clinical automation may be present, but all three of
the major ancillary department systems for laboratory, pharmacy,
and radiology are not implemented.
Stage 1: All three of the major ancillary clinical systems (pharmacy,
laboratory, radiology) are installed.
Stage 2: Major ancillary clinical systems feed orders and results
data to a clinical data repository (CDR) that provides physician
access for retrieving and reviewing results. The CDR contains a
controlled medical vocabulary (CMV), and the clinical decision
support/rules engine (CDSS) for rudimentary conflict checking
such as duplicate orders. Information from document imaging
systems may be linked to the CDR at this stage.
Stage 3: Nursing/clinical documentation (e.g., vital signs, flow
sheets, nursing notes, eMAR) is required and is implemented and
integrated with the CDR for at least one inpatient service in the
hospital; care plan charting is scored with extra points. The
electronic medication administration record application (EMAR)
is implemented. The first level of clinical decision support is
implemented to conduct error checking with order entry (i.e., drug/
drug, drug/ food, drug/lab conflict checking normally found in the
pharmacy information system). Medical image access from picture
archive and communication systems (PACS) is available for access
by physicians outside the radiology department via the
organization’s intranet.
Stage 4: Computerized practitioner/physician order entry
(CPOE) for use by any clinician is added to the nursing and CDR
environment along with the second level of clinical decision support
capabilities related to evidence-based medicine protocols and order
sets. An organization is given credit for having achieved this stage
if one patient service area (excluding the emergency department)
has implemented CPOE and completed the previous stages.
Stage 5: The closed-loop medication administration environment
is fully implemented in at least one patient care service area. The
EMAR and bar coding or other auto identification technology,
such as radio frequency identification (RFID), are implemented
and integrated with CPOE and pharmacy to support the five rights
of medication administration (right patient, right drug, right dose,
right route, right time), thereby maximizing point-of-care patient
safety processes.
Stage 6: Full physician documentation/charting (using structured
templates) is implemented for at least one patient care service area
supported by CDSS. Level three of clinical decision support is
implemented, which provides guidance for all clinician activities
related to protocols and outcomes in the form of variance and
compliance alerts. A full complement of radiology PACS systems
provides medical images to physicians via an intranet and displaces
all film-based images.
Stage 7: The hospital has a paperless EMR environment to support
patient care delivery. Patient data/information is easily exchanged
between the inpatient, out-patient, and emergency department
domains. All radiology images are digital and easily accessed by all
authorized clinicians. Clinical information can be readily analyzed
and reported on for quality and patient safety initiatives, and shared
via standardized electronic transactions with all entities within a
74 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
health information exchange (i.e., other hospitals, ambulatory clinics,
sub-acute environments, employers, payers and patients). This stage
allows the healthcare organization to support the true sharing and
use of health and wellness information by consumers and providers
alike using CCD, CCR, or state required transaction formats.
Scoring Format
An EMR score is represented by the following format – S.nnnn,
where “S” equals the current stage achieved for the model, and
the “.nnnn” represents the weighted score representing the
implementation of higher stage clinical applications that have
been implemented before the higher stage has been fully achieved.
In this model all applications in previous stages and the current
stage must be achieved before the current stage score is achieved.
For example, if a hospital has installed CPOE (Stage 4), but has
not yet implemented all of the components required for clinical
documentation used by nursing (Stage 3), then the hospital would
be scored as a Stage 2 hospital and the four digits after the stage
designation would identify the weighted points that had been
achieved for implementing CPOE (2.nnnn).
An overall evaluation of the U.S. hospital market for the EMR
Adoption Model scores by individual stage for the third quarter
of 2011 as compared to 2010 final numbers is shown in Figure
EMRAM1. Hospitals in Stages 4–6 increased from end of year 2010
to the Q3 of 2011, while the percentage of hospitals in Stages 0 to 3
have decreased in the same timeframe, continuing the trend that
was reported last year. The increase in the percentage of hospitals
in Stages 4 to 6 can largely be attributed directly to the ARRA
incentive and meeting the meaningful use criteria. The percentage
of Stage 5 hospitals has almost doubled since the end of 2010,
providing a significant increase in medication safety. There was
minor increase in the percent of U.S. hospitals that have reached
Stage 7. A little less than half of U.S. hospitals are in Stage 3, a
proportion which has decreased by almost three percent, due to
hospitals moving up the scale. Stage 3 provides the foundation for
advancing to more advanced stages of clinical information system
capabilities (e.g., CPOE, closed-loop medication administration,
and physician documentation).
An evaluation of U.S. hospitals by type, bed size, and region
(see Table EMR1) with 2011 data shows that:
• Academic/teaching hospitals had the highest mean and median
EMRAM scores, among all hospital types; they are also the only
group that has both a median and mean score of four. This is
followed by general medical/surgical and urban hospitals. This is
unchanged from previous annual reports.
• There is a positive correlation between larger bed hospitals
and high EMRAM average and median scores. Hospitals in the
600 or more bed segment had the highest mean score and median
score across all bed size categories; hospitals with fewer than
100 beds have the lowest mean and median scores.
• As in previous annual reports, the New England region had the
highest mean and median score by region. Hospitals in the
Mountain and West South Central regions have the lowest
average and median scores.
An evaluation of the EMRAM scores by individual U.S. state shows
that Rhode Island, Maine and Connecticut all have median scores
above 4.0000. Montana is the only state to have a mean and median
score under 2.0000 and is ranked 50th of all the U.S. states and
District of Columbia (see Tables EMR2 and EMR3).
▶▶ The EMR Adoption ModelSM: Measuring Clinical IT Transformation con tinued
Table E MR A M1
Table E MR A M3
Segment
Hospital Type Segment
Academic/Teaching
Non-Academic
General Medical/Surgical
Others
Rural
Urban
IDS
Independent Hospital
Critical Access
Bed Segment
0–100 beds
101–200 beds
201–300 beds
301–400 beds
401–500 beds
501–600 beds
600+ Beds
Regions (U.S. Census Defined)
East North Central
East South Central
Middle Atlantic
Mountain
New England
Pacific
South Atlantic
West North Central
West South Central
All Hospitals
Total
Mean
Min
Max
Median
Number
4.2111
3.0901
3.4286
2.7056
2.3608
3.3767
3.3029
2.8615
2.3872
1.2860
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
7.0710
7.0710
7.0710
7.0710
7.0390
7.0710
7.0710
7.0630
6.0550
4.2470
3.2600
3.3310
3.1350
3.0400
3.3200
3.3030
3.1990
3.0720
221
5,078
3,161
2,138
1,251
4,048
3,306
1,993
1,323
2.6328
3.3981
3.7498
3.8064
3.8185
4.0942
4.2120
0.0000
0.0000
0.0100
0.1900
2.0150
2.1700
2.1020
7.0630
7.0710
7.0710
7.0710
7.0390
7.0710
7.0710
3.1200
3.3150
3.4080
3.4150
3.4410
3.5090
4.2235
2,759
973
610
405
215
149
188
3.3991
2.8580
3.4383
2.7394
3.8923
3.3311
3.3794
2.9378
2.6678
0.0000
0.0000
0.0050
0.0000
0.1110
0.0000
0.0000
0.0000
0.0000
7.0710
6.0710
7.0390
7.0630
7.0630
7.0710
7.0710
7.0630
7.0390
3.3160
3.2000
3.3150
3.1560
3.4595
3.2710
3.3350
3.2350
3.1390
839
442
486
419
200
584
787
708
834
3.1369
0.0000
7.0710
3.2750
5,299
Region Key for States:
New England . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MA, ME, VT, RI, CT, NH
Middle Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NY, NJ, PA
South Atlantic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MD, DE, DC, WV, VA, NC, SC, GA, FL
East North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MI, OH, IN, IL, WI
East South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . KY, TN, MS, AL
West North Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MN, IA, MO, KS, ND, SD, NE
West South Central . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TX, LA, AR, OK
Mountain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ID, CO, WY, MT, NV, UT, AZ, NM
Pacific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WA, CA, OR, AK, HI
Table E MR A M2
Segment
Rhode Island
Maine
Connecticut
Delaware
Vermont
Massachusetts
Virginia
Maryland
Missouri
South Carolina
Utah
Iowa
Illinois
Washington
Indiana
Georgia
Oregon
Pennsylvania
Florida
Wisconsin
North Carolina
New Jersey
Ohio
Minnesota
New York
Mean
4.3605
3.9510
3.9343
4.1829
4.0035
4.0049
3.9711
3.8939
3.4470
3.4575
3.2554
3.4053
3.5352
3.3992
3.4674
3.1888
3.3854
3.4214
3.2695
3.5267
3.3421
3.4309
3.2535
3.4272
3.4579
Min
1.3230
2.0950
1.0790
2.4580
1.0710
0.1250
0.0790
1.0710
0.0050
0.1300
0.0000
0.0050
0.0450
0.0050
0.0050
0.0000
0.0420
0.0050
0.0000
0.0000
0.0100
0.0550
0.0000
0.0000
0.0050
Max
6.0710
6.0480
6.0710
7.0470
6.0710
7.0630
7.0710
6.0630
7.0310
6.0710
6.0710
6.0710
7.0710
6.0710
6.0710
6.0710
7.0230
7.0390
6.0710
7.0710
6.0710
6.0710
6.0710
7.0630
6.0710
Median
4.2610
4.1550
4.0960
3.6050
3.5250
3.4870
3.4190
3.4155
3.4000
3.3910
3.3750
3.3680
3.3600
3.3590
3.3390
3.3350
3.3350
3.3350
3.3320
3.3250
3.3220
3.3150
3.3120
3.2980
3.2870
Number
11
35
34
9
14
81
84
48
133
71
49
121
199
93
137
155
61
198
239
136
122
85
207
133
203
Segment
Alaska
Tennessee
Arizona
New Hampshire
Alabama
Colorado
Kentucky
California
Michigan
West Virginia
Texas
Idaho
Nevada
Wyoming
South Dakota
Louisiana
Nebraska
New Mexico
District of Columbia
Arkansas
Kansas
Oklahoma
Mississippi
Hawaii
North Dakota
Montana
Mean
3.3329
3.0614
3.1642
3.1196
2.9664
2.7713
3.0084
3.3571
3.2511
3.0150
2.7711
2.7576
2.4048
2.8278
2.5621
2.5083
2.5447
2.8459
2.4858
2.6313
2.2425
2.4634
2.3038
2.5397
2.0412
1.7363
Min
0.0050
0.0000
0.0250
0.1110
0.0000
0.0150
0.0580
0.0000
0.0050
0.0100
0.0000
0.0000
0.0000
0.0150
0.0000
0.0050
0.0000
0.0000
0.0050
0.0050
0.0000
0.0000
0.0050
0.0050
0.0000
0.0000
Max
6.0710
6.0710
7.0630
6.0470
5.1190
6.0470
6.0710
7.0710
6.0710
6.0470
7.0390
6.0150
4.2670
6.0310
6.0470
6.0710
6.0550
6.0310
4.2770
6.0710
6.0480
6.0710
6.0710
6.0480
5.1350
6.0240
Median
3.2750
3.2720
3.2615
3.2600
3.2520
3.2495
3.2350
3.2305
3.2195
3.2000
3.1870
3.1840
3.1550
3.1470
3.1435
3.1395
3.1240
3.1240
3.0970
3.0750
3.0750
3.0750
2.1620
2.1510
2.1470
1.7300
Number
17
140
82
25
99
84
104
388
160
49
486
43
41
27
52
144
87
37
10
86
137
118
99
25
45
56
For additional information about EMRAM, go to the link
shown below:
http://www.himssanalytics.org/hc_providers/emr_adoption.asp
2011 marked the beginning of the period of payout for ARRA’s
EMR adoption incentives, and measures of activity during the
latter half of 2010 suggest that the rate of EMR acquisition and
implementation is escalating. We anticipate this trend will further
accelerate in 2011. However, while the rate of progress is
commendable and vital to the long term “health” of healthcare,
much more work remains to be accomplished if the government’s
goal of 70 percent of the U.S. healthcare providers are to achieve
meaningful criteria by the end of 2015.
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
75
▶▶ Appendix
▶▶
0–100 Beds
Applications
101–200 Beds
201–300 Beds
2010
2011
2010
2011
2010
2011
% of 2,181 Hospitals
% of 2,181 Hospitals
% of 822 hospitals
% of 822 hospitals
% of 504 hospitals
% of 504 hospitals
Abstracting
2,013
92.30%
2,050
93.99%
815
99.15%
818
99.51%
503
99.80%
503
99.80%
Accounts Payable
2,175
99.72%
2,179
99.91%
822
100.00%
822
100.00%
504
100.00%
504
100.00%
ADT/Registration
2,166
99.31%
2,170
99.50%
821
99.88%
821
99.88%
504
100.00%
504
100.00%
Anatomical Pathology
723
33.15%
745
34.16%
630
76.64%
624
75.91%
448
88.89%
453
89.88%
Bed Management
412
18.89%
506
23.20%
300
36.50%
328
39.90%
239
47.42%
263
52.18%
1,752
80.33%
1,781
81.66%
795
96.72%
800
97.32%
494
98.02%
497
98.61%
953
43.70%
977
44.80%
719
87.47%
699
85.04%
480
95.24%
478
94.84%
1,585
72.67%
1,615
74.05%
736
89.54%
738
89.78%
458
90.87%
461
91.47%
Business Intelligence
619
28.38%
688
31.55%
376
45.74%
416
50.61%
240
47.62%
268
53.17%
Cardiology – Cath Lab
126
5.78%
129
5.91%
328
39.90%
338
41.12%
284
56.35%
311
61.71%
Cardiology – CT (Computerized Tomography)
106
4.86%
125
5.73%
215
26.16%
239
29.08%
167
33.13%
194
38.49%
Cardiology – Echocardiology
192
8.80%
234
10.73%
321
39.05%
348
42.34%
252
50.00%
280
55.56%
89
4.08%
111
5.09%
190
23.11%
210
25.55%
158
31.35%
190
37.70%
Cardiology – Nuclear Cardiology
100
4.59%
137
6.28%
185
22.51%
215
26.16%
144
28.57%
179
35.52%
Cardiology Information System
314
14.40%
357
16.37%
497
60.46%
525
63.87%
371
73.61%
391
77.58%
Case Mix Management
1,483
68.00%
1,508
69.14%
736
89.54%
743
90.39%
455
90.28%
462
91.67%
Chart Deficiency
1,814
83.17%
1,875
85.97%
806
98.05%
810
98.54%
501
99.40%
501
99.40%
Chart Tracking/Locator
1,780
81.61%
1,844
84.55%
802
97.57%
808
98.30%
497
98.61%
496
98.41%
Clinical Data Repository
1,731
79.37%
1,842
84.46%
779
94.77%
786
95.62%
496
98.41%
497
98.61%
Clinical Decision Support
1,672
76.66%
1,774
81.34%
761
92.58%
772
93.92%
487
96.63%
497
98.61%
Computer Assisted Coding
250
11.46%
295
13.53%
124
15.09%
140
17.03%
92
18.25%
112
22.22%
Computerized Practitioner
Order Entry (CPOE)
1,024
46.95%
1,299
59.56%
456
55.47%
546
66.42%
345
68.45%
393
77.98%
638
29.25%
802
36.77%
416
50.61%
502
61.07%
261
51.79%
314
62.30%
Contract Management
1,159
53.14%
1,198
54.93%
627
76.28%
635
77.25%
399
79.17%
407
80.75%
Cost Accounting
1,215
55.71%
1,242
56.95%
627
76.28%
628
76.40%
426
84.52%
426
84.52%
Credit/Collections
1,879
86.15%
1,901
87.16%
793
96.47%
795
96.72%
480
95.24%
482
95.63%
Data Warehousing/Mining – Financial
699
32.05%
753
34.53%
402
48.91%
443
53.89%
256
50.79%
295
58.53%
Data Warehousing/Mining – Clinical
502
23.02%
579
26.55%
304
36.98%
366
44.53%
215
42.66%
258
51.19%
DBMS
1,138
52.18%
1,162
53.28%
616
74.94%
627
76.28%
384
76.19%
392
77.78%
Dictation
1,784
81.80%
1,859
85.24%
784
95.38%
800
97.32%
486
96.43%
496
98.41%
Dictation with Speech Recognition
429
19.67%
542
24.85%
327
39.78%
390
47.45%
245
48.61%
294
58.33%
Disaster Recovery
633
29.02%
726
33.29%
304
36.98%
363
44.16%
193
38.29%
227
45.04%
Document Management
1,246
57.13%
1,336
61.26%
593
72.14%
630
76.64%
393
77.98%
424
84.13%
EDI – Clearinghouse Vendor
1,686
77.30%
1,775
81.38%
675
82.12%
711
86.50%
407
80.75%
435
86.31%
919
42.14%
1,036
47.50%
463
56.33%
494
60.10%
300
59.52%
332
65.87%
Electronic Medication
Administration Record (EMAR)
1,345
61.67%
1,549
71.02%
630
76.64%
661
80.41%
426
84.52%
449
89.09%
Emergency Department Systems
1,212
55.57%
1,371
62.86%
708
86.13%
729
88.69%
469
93.06%
478
94.84%
Encoder
2,018
92.53%
2,045
93.76%
818
99.51%
818
99.51%
503
99.80%
503
99.80%
915
41.95%
999
45.80%
482
58.64%
536
65.21%
312
61.90%
346
68.65%
Benefits Administration
Blood Bank
Budgeting
Cardiology – Intravascular Ultrasound
Consumer Portal
Electronic Forms Management
Encryption
76 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
301–400 Beds
401–500 Beds
501–600 Beds
600+ Beds
2010
2011
2010
2011
2010
2011
2010
2011
% of 328 hospitals
% of 328 hospitals
% of 182 hospitals
% of 182 hospitals
% of 122 hospitals
% of 122 hospitals
% of 150 hospitals
% of 150 hospitals
325
99.09%
326
99.39%
182
100.00%
182
100.00%
121
99.18%
122
100.00%
150
100.00%
150
100.00%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
121
99.18%
150
100.00%
150
100.00%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
303
92.38%
301
91.77%
170
93.41%
168
92.31%
119
97.54%
119
97.54%
146
97.33%
146
97.33%
183
55.79%
205
62.50%
112
61.54%
119
65.38%
78
63.93%
83
68.03%
111
74.00%
124
82.67%
321
97.87%
323
98.48%
180
98.90%
180
98.90%
120
98.36%
120
98.36%
145
96.67%
145
96.67%
323
98.48%
317
96.65%
176
96.70%
176
96.70%
120
98.36%
120
98.36%
143
95.33%
143
95.33%
307
93.60%
307
93.60%
174
95.60%
173
95.05%
118
96.72%
117
95.90%
141
94.00%
141
94.00%
172
52.44%
193
58.84%
95
52.20%
106
58.24%
72
59.02%
77
63.11%
85
56.67%
97
64.67%
225
68.60%
234
71.34%
144
79.12%
147
80.77%
105
86.07%
106
86.89%
124
82.67%
126
84.00%
133
40.55%
143
43.60%
90
49.45%
96
52.75%
65
53.28%
69
56.56%
79
52.67%
88
58.67%
210
64.02%
224
68.29%
131
71.98%
138
75.82%
96
78.69%
99
81.15%
119
79.33%
123
82.00%
139
42.38%
149
45.43%
89
48.90%
98
53.85%
64
52.46%
68
55.74%
83
55.33%
91
60.67%
132
40.24%
141
42.99%
79
43.41%
87
47.80%
66
54.10%
71
58.20%
73
48.67%
83
55.33%
267
81.40%
270
82.32%
157
86.26%
158
86.81%
105
86.07%
108
88.52%
139
92.67%
143
95.33%
288
87.80%
296
90.24%
168
92.31%
169
92.86%
109
89.34%
108
88.52%
149
99.33%
143
95.33%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
326
99.39%
325
99.09%
177
97.25%
177
97.25%
121
99.18%
121
99.18%
147
98.00%
146
97.33%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
314
95.73%
317
96.65%
179
98.35%
179
98.35%
121
99.18%
121
99.18%
146
97.33%
146
97.33%
66
20.12%
75
22.87%
36
19.78%
42
23.08%
24
19.67%
27
22.13%
33
22.00%
42
28.00%
231
70.43%
270
82.32%
138
75.82%
150
82.42%
99
81.15%
106
86.89%
128
85.33%
135
90.00%
177
53.96%
208
63.41%
107
58.79%
123
67.58%
74
60.66%
84
68.85%
99
66.00%
107
71.33%
272
82.93%
274
83.54%
156
85.71%
157
86.26%
103
84.43%
103
84.43%
125
83.33%
129
86.00%
289
88.11%
288
87.80%
163
89.56%
166
91.21%
116
95.08%
115
94.26%
139
92.67%
139
92.67%
312
95.12%
316
96.34%
175
96.15%
176
96.70%
117
95.90%
117
95.90%
144
96.00%
145
96.67%
195
59.45%
212
64.63%
114
62.64%
118
64.84%
67
54.92%
72
59.02%
106
70.67%
114
76.00%
153
46.65%
176
53.66%
86
47.25%
94
51.65%
56
45.90%
60
49.18%
92
61.33%
100
66.67%
267
81.40%
269
82.01%
150
82.42%
152
83.52%
103
84.43%
104
85.25%
128
85.33%
131
87.33%
321
97.87%
325
99.09%
179
98.35%
180
98.90%
119
97.54%
118
96.72%
145
96.67%
147
98.00%
175
53.35%
209
63.72%
94
51.65%
115
63.19%
76
62.30%
84
68.85%
96
64.00%
111
74.00%
128
39.02%
146
44.51%
70
38.46%
78
42.86%
58
47.54%
60
49.18%
73
48.67%
83
55.33%
264
80.49%
276
84.15%
158
86.81%
162
89.01%
102
83.61%
104
85.25%
129
86.00%
138
92.00%
278
84.76%
295
89.94%
147
80.77%
153
84.07%
107
87.70%
111
90.98%
132
88.00%
138
92.00%
207
63.11%
223
67.99%
123
67.58%
131
71.98%
84
68.85%
86
70.49%
94
62.67%
102
68.00%
275
83.84%
296
90.24%
170
93.41%
173
95.05%
116
95.08%
118
96.72%
133
88.67%
138
92.00%
305
92.99%
310
94.51%
171
93.96%
175
96.15%
114
93.44%
114
93.44%
147
98.00%
149
99.33%
327
99.70%
327
99.70%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
205
62.50%
224
68.29%
115
63.19%
124
68.13%
76
62.30%
84
68.85%
93
62.00%
104
69.33%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
77
▶▶ Appendix con tinued
0–100 Beds
Applications
101–200 Beds
201–300 Beds
2010
2011
2010
2011
2010
2011
% of 2,181 Hospitals
% of 2,181 Hospitals
% of 822 hospitals
% of 822 hospitals
% of 504 hospitals
% of 504 hospitals
Enterprise Master Person Index (EMPI)
829
38.01%
901
41.31%
453
55.11%
492
59.85%
288
57.14%
310
61.51%
Enterprise Resource Planning
312
14.31%
338
15.50%
189
22.99%
199
24.21%
155
30.75%
162
32.14%
1,190
54.56%
1,231
56.44%
555
67.52%
579
70.44%
353
70.04%
360
71.43%
534
24.48%
577
26.46%
312
37.96%
329
40.02%
216
42.86%
225
44.64%
Firewall
1,243
56.99%
1,350
61.90%
564
68.61%
625
76.03%
353
70.04%
397
78.77%
General Ledger
2,175
99.72%
2,178
99.86%
822
100.00%
822
100.00%
504
100.00%
504
100.00%
334
15.31%
430
19.72%
211
25.67%
259
31.51%
150
29.76%
210
41.67%
1,216
55.75%
1,256
57.59%
664
80.78%
671
81.63%
416
82.54%
423
83.93%
Intensive Care
719
32.97%
754
34.57%
521
63.38%
549
66.79%
347
68.85%
374
74.21%
Interface Engines
913
41.86%
972
44.57%
541
65.82%
560
68.13%
359
71.23%
378
75.00%
84
3.85%
123
5.64%
117
14.23%
124
15.09%
83
16.47%
94
18.65%
Laboratory – Outreach Services
235
10.77%
329
15.08%
205
24.94%
239
29.08%
160
31.75%
187
37.10%
Laboratory Information System
2,077
95.23%
2,110
96.74%
821
99.88%
822
100.00%
504
100.00%
504
100.00%
Materials Management
2,059
94.41%
2,074
95.09%
817
99.39%
819
99.64%
504
100.00%
504
100.00%
Medical Necessity Checking Content
977
44.80%
1,067
48.92%
512
62.29%
547
66.55%
285
56.55%
328
65.08%
Medication Reconciliation
618
28.34%
906
41.54%
328
39.90%
421
51.22%
220
43.65%
302
59.92%
1,295
59.38%
1,373
62.95%
772
93.92%
773
94.04%
492
97.62%
493
97.82%
Nurse Call System
629
28.84%
823
37.73%
360
43.80%
442
53.77%
231
45.83%
292
57.94%
Nurse Staffing/Scheduling
986
45.21%
999
45.80%
625
76.03%
626
76.16%
444
88.10%
438
86.90%
1,481
67.90%
1,630
74.74%
677
82.36%
707
86.01%
446
88.49%
461
91.47%
Obstetrical Systems (Labor and Delivery)
576
26.41%
631
28.93%
538
65.45%
556
67.64%
343
68.06%
363
72.02%
Operating Room (Surgery) – Peri-Operative
834
38.24%
948
43.47%
608
73.97%
633
77.01%
421
83.53%
425
84.33%
Operating Room (Surgery) – Post-Operative
869
39.84%
995
45.62%
617
75.06%
646
78.59%
424
84.13%
426
84.52%
Operating Room (Surgery) – Pre-Operative
948
43.47%
1,047
48.01%
651
79.20%
673
81.87%
449
89.09%
451
89.48%
OR Scheduling
997
45.71%
1,085
49.75%
679
82.60%
709
86.25%
469
93.06%
469
93.06%
Order Entry (includes Order Communications)
1,868
85.65%
1,941
89.00%
790
96.11%
797
96.96%
495
98.21%
498
98.81%
Outcomes and Quality Management
1,675
76.80%
1,686
77.30%
625
76.03%
605
73.60%
402
79.76%
395
78.37%
426
19.53%
479
21.96%
284
34.55%
290
35.28%
194
38.49%
199
39.48%
Patient Billing
2,154
98.76%
2,177
99.82%
821
99.88%
822
100.00%
504
100.00%
503
99.80%
Patient Scheduling
2,025
92.85%
2,059
94.41%
813
98.91%
813
98.91%
500
99.21%
501
99.40%
Payroll
2,136
97.94%
2,143
98.26%
819
99.64%
820
99.76%
503
99.80%
503
99.80%
Personnel Management
1,731
79.37%
1,774
81.34%
801
97.45%
804
97.81%
496
98.41%
497
98.61%
Pharmacy Management System
1,957
89.73%
2,012
92.25%
820
99.76%
821
99.88%
504
100.00%
504
100.00%
Physician Documentation
934
42.82%
1,120
51.35%
455
55.35%
535
65.09%
341
67.66%
380
75.40%
Physician Portal
633
29.02%
817
37.46%
404
49.15%
466
56.69%
279
55.36%
321
63.69%
Radiology – Angiography
904
41.45%
931
42.69%
653
79.44%
669
81.39%
450
89.29%
458
90.87%
Radiology – Computerized Tomography (CT)
1,622
74.37%
1,711
78.45%
753
91.61%
765
93.07%
483
95.83%
486
96.43%
Radiology – Computed Radiography (CR)
1,577
72.31%
1,693
77.62%
750
91.24%
767
93.31%
469
93.06%
474
94.05%
Radiology – Digital Fluoroscopy (DF)
1,176
53.92%
1,254
57.50%
701
85.28%
722
87.83%
457
90.67%
464
92.06%
778
35.67%
966
44.29%
493
59.98%
571
69.46%
324
64.29%
353
70.04%
Executive Information Systems
Financial Modeling
Infection Surveillance System
In-House Transcription
Laboratory – Molecular Diagnostics
Microbiology
Nursing Documentation
Patient Acuity (formerly Nurse Acuity)
Radiology – Digital Mammography
78 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
301–400 Beds
401–500 Beds
501–600 Beds
600+ Beds
2010
2011
2010
2011
2010
2011
2010
2011
% of 328 hospitals
% of 328 hospitals
% of 182 hospitals
% of 182 hospitals
% of 122 hospitals
% of 122 hospitals
% of 150 hospitals
% of 150 hospitals
202
61.59%
211
64.33%
116
63.74%
117
64.29%
75
61.48%
80
65.57%
113
75.33%
117
78.00%
121
36.89%
130
39.63%
72
39.56%
73
40.11%
55
45.08%
57
46.72%
69
46.00%
75
50.00%
231
70.43%
239
72.87%
133
73.08%
136
74.73%
85
69.67%
87
71.31%
117
78.00%
117
78.00%
162
49.39%
167
50.91%
96
52.75%
100
54.95%
71
58.20%
76
62.30%
78
52.00%
80
53.33%
236
71.95%
254
77.44%
139
76.37%
145
79.67%
86
70.49%
93
76.23%
108
72.00%
118
78.67%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
121
99.18%
150
100.00%
150
100.00%
109
33.23%
136
41.46%
72
39.56%
87
47.80%
52
42.62%
59
48.36%
59
39.33%
86
57.33%
269
82.01%
276
84.15%
148
81.32%
154
84.62%
104
85.25%
101
82.79%
135
90.00%
138
92.00%
223
67.99%
235
71.65%
135
74.18%
137
75.27%
101
82.79%
105
86.07%
122
81.33%
132
88.00%
255
77.74%
262
79.88%
154
84.62%
154
84.62%
105
86.07%
108
88.52%
129
86.00%
135
90.00%
79
24.09%
89
27.13%
47
25.82%
54
29.67%
33
27.05%
36
29.51%
66
44.00%
77
51.33%
120
36.59%
139
42.38%
73
40.11%
84
46.15%
50
40.98%
58
47.54%
74
49.33%
87
58.00%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
326
99.39%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
201
61.28%
218
66.46%
115
63.19%
126
69.23%
80
65.57%
83
68.03%
86
57.33%
99
66.00%
151
46.04%
201
61.28%
102
56.04%
128
70.33%
75
61.48%
84
68.85%
76
50.67%
104
69.33%
321
97.87%
323
98.48%
180
98.90%
180
98.90%
118
96.72%
118
96.72%
147
98.00%
148
98.67%
138
42.07%
177
53.96%
77
42.31%
98
53.85%
64
52.46%
73
59.84%
73
48.67%
91
60.67%
300
91.46%
299
91.16%
166
91.21%
163
89.56%
115
94.26%
115
94.26%
140
93.33%
140
93.33%
296
90.24%
303
92.38%
164
90.11%
170
93.41%
119
97.54%
119
97.54%
141
94.00%
143
95.33%
251
76.52%
257
78.35%
143
78.57%
144
79.12%
101
82.79%
101
82.79%
126
84.00%
128
85.33%
277
84.45%
288
87.80%
167
91.76%
168
92.31%
114
93.44%
118
96.72%
141
94.00%
146
97.33%
278
84.76%
292
89.02%
161
88.46%
163
89.56%
112
91.80%
115
94.26%
139
92.67%
144
96.00%
297
90.55%
305
92.99%
171
93.96%
170
93.41%
117
95.90%
117
95.90%
144
96.00%
146
97.33%
310
94.51%
313
95.43%
175
96.15%
177
97.25%
119
97.54%
119
97.54%
148
98.67%
149
99.33%
327
99.70%
326
99.39%
180
98.90%
181
99.45%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
255
77.74%
248
75.61%
142
78.02%
137
75.27%
104
85.25%
97
79.51%
123
82.00%
123
82.00%
123
37.50%
129
39.33%
90
49.45%
88
48.35%
54
44.26%
56
45.90%
69
46.00%
71
47.33%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
327
99.70%
327
99.70%
182
100.00%
182
100.00%
121
99.18%
122
100.00%
150
100.00%
150
100.00%
326
99.39%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
325
99.09%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
328
100.00%
328
100.00%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
202
61.59%
227
69.21%
118
64.84%
131
71.98%
96
78.69%
101
82.79%
122
81.33%
133
88.67%
206
62.80%
225
68.60%
130
71.43%
139
76.37%
85
69.67%
89
72.95%
98
65.33%
111
74.00%
303
92.38%
306
93.29%
176
96.70%
175
96.15%
119
97.54%
119
97.54%
147
98.00%
149
99.33%
321
97.87%
321
97.87%
179
98.35%
179
98.35%
121
99.18%
121
99.18%
150
100.00%
150
100.00%
317
96.65%
318
96.95%
177
97.25%
176
96.70%
121
99.18%
121
99.18%
148
98.67%
148
98.67%
309
94.21%
312
95.12%
175
96.15%
172
94.51%
118
96.72%
119
97.54%
143
95.33%
145
96.67%
233
71.04%
252
76.83%
132
72.53%
140
76.92%
92
75.41%
101
82.79%
115
76.67%
125
83.33%
Source: HIMSS Analytics® Database 2011
©2012 HIMSS Analytics.
79
▶▶ Appendix con tinued
0–100 Beds
Applications
101–200 Beds
201–300 Beds
2010
2011
2010
2011
2010
2011
% of 2,181 Hospitals
% of 2,181 Hospitals
% of 822 hospitals
% of 822 hospitals
% of 504 hospitals
% of 504 hospitals
Radiology – Digital Radiography (DR)
1,282
58.78%
1,371
62.86%
715
86.98%
733
89.17%
457
90.67%
460
91.27%
Radiology – Magnetic Resonance
Imaging (MRI)
1,426
65.38%
1,504
68.96%
733
89.17%
752
91.48%
476
94.44%
479
95.04%
Radiology – Nuclear Medicine
1,210
55.48%
1,283
58.83%
731
88.93%
745
90.63%
473
93.85%
475
94.25%
616
28.24%
716
32.83%
424
51.58%
472
57.42%
278
55.16%
305
60.52%
Radiology – Ultrasound (US)
1,562
71.62%
1,682
77.12%
745
90.63%
760
92.46%
482
95.63%
485
96.23%
Radiology Information System
1,936
88.77%
1,972
90.42%
810
98.54%
813
98.91%
503
99.80%
502
99.60%
Respiratory Care Information System
697
31.96%
862
39.52%
422
51.34%
468
56.93%
275
54.56%
296
58.73%
Single Sign-On
445
20.40%
506
23.20%
312
37.96%
359
43.67%
218
43.25%
252
50.00%
Spam Filter/ Spyware
N/A
0.00%
1,247
57.18%
N/A
0.00%
586
71.29%
N/A
0.00%
379
75.20%
Staff Scheduling
633
29.02%
666
30.54%
436
53.04%
451
54.87%
308
61.11%
321
63.69%
Telemedicine
478
21.92%
581
26.64%
162
19.71%
212
25.79%
92
18.25%
133
26.39%
1,934
88.67%
1,970
90.33%
797
96.96%
804
97.81%
492
97.62%
494
98.02%
518
23.75%
674
30.90%
276
33.58%
353
42.94%
189
37.50%
255
50.60%
Radiology – Orthopedic
Time & Attendance
Virtualization Software
0–100 Beds
Next Generation RCM
101–200 Beds
201–300 Beds
2010
2011
2010
2011
2010
2011
% of 2,181 Hospitals
% of 2,181 Hospitals
% of 822 hospitals
% of 822 hospitals
% of 504 hospitals
% of 504 hospitals
Biller’s Dash Board
473
21.69%
529
24.25%
159
19.34%
188
22.87%
117
23.21%
136
26.98%
Claims Attachment Rules
499
22.88%
540
24.76%
217
26.40%
241
29.32%
137
27.18%
166
32.94%
Claims Remittance Updates AR
322
14.76%
333
15.27%
107
13.02%
125
15.21%
83
16.47%
94
18.65%
Denial Rules
517
23.70%
580
26.59%
227
27.62%
261
31.75%
138
27.38%
164
32.54%
Direct Payer Claims
235
10.77%
249
11.42%
88
10.71%
94
11.44%
62
12.30%
72
14.29%
EFT Transaction
503
23.06%
540
24.76%
187
22.75%
203
24.70%
124
24.60%
135
26.79%
Eligibility Transaction with Payer
338
15.50%
368
16.87%
113
13.75%
124
15.09%
77
15.28%
86
17.06%
EMR Documentation for Claims
60
2.75%
42
1.93%
36
4.38%
24
2.92%
25
4.96%
19
3.77%
Necessity Alert @ Registration
683
31.32%
723
33.15%
329
40.02%
350
42.58%
187
37.10%
205
40.67%
Necessity Alert @ Scheduling
337
15.45%
353
16.19%
219
26.64%
244
29.68%
137
27.18%
147
29.17%
Web PreRegister
231
10.59%
269
12.33%
179
21.78%
219
26.64%
106
21.03%
132
26.19%
Web Schedule
64
2.93%
68
3.12%
71
8.64%
72
8.76%
59
11.71%
60
11.90%
Web Self Pay
430
19.72%
542
24.85%
284
34.55%
347
42.21%
156
30.95%
187
37.10%
A mbulat ory
A mbulat ory
2010
% of 18,335 Ambulatory
Facilities
Ambulatory EMR
10,543
57.50%
2011
% of 18,335 Ambulatory
Facilities
11,416
62.26%
Ambulatory Laboratory
3,298
17.99%
3,544
19.33%
Ambulatory Pharmacy
1,174
6.40%
1,212
6.61%
Ambulatory Radiology
3,233
17.63%
3,389
18.48%
Practice Management
17,799
97.08%
17,870
97.46%
80 Source: HIMSS Analytics® Database 2011 ©2012 HIMSS Analytics.
Ambulatory PACS*
2010
% of 3,454
Ambulatory Facilities
2011
% of 3,354
Ambulatory Facilities
2,052
1,953
59.41%
*Only includes ambulatory facilities doing imaging on site
56.54%
301–400 Beds
401–500 Beds
501–600 Beds
600+ Beds
2010
2011
2010
2011
2010
2011
2010
2011
% of 328 hospitals
% of 328 hospitals
% of 182 hospitals
% of 182 hospitals
% of 122 hospitals
% of 122 hospitals
% of 150 hospitals
% of 150 hospitals
308
93.90%
312
95.12%
174
95.60%
175
96.15%
120
98.36%
120
98.36%
147
98.00%
147
98.00%
318
96.95%
318
96.95%
177
97.25%
177
97.25%
121
99.18%
121
99.18%
148
98.67%
149
99.33%
315
96.04%
315
96.04%
176
96.70%
176
96.70%
119
97.54%
119
97.54%
146
97.33%
146
97.33%
194
59.15%
205
62.50%
124
68.13%
131
71.98%
77
63.11%
83
68.03%
108
72.00%
119
79.33%
319
97.26%
319
97.26%
179
98.35%
179
98.35%
121
99.18%
121
99.18%
150
100.00%
150
100.00%
327
99.70%
327
99.70%
182
100.00%
182
100.00%
122
100.00%
122
100.00%
150
100.00%
150
100.00%
179
54.57%
198
60.37%
117
64.29%
124
68.13%
77
63.11%
82
67.21%
101
67.33%
111
74.00%
144
43.90%
159
48.48%
75
41.21%
81
44.51%
61
50.00%
66
54.10%
83
55.33%
90
60.00%
N/A
0.00%
249
75.91%
N/A
0.00%
138
75.82%
N/A
0.00%
91
74.59%
N/A
0.00%
118
78.67%
222
67.68%
228
69.51%
124
68.13%
125
68.68%
86
70.49%
88
72.13%
114
76.00%
116
77.33%
83
25.30%
100
30.49%
55
30.22%
58
31.87%
38
31.15%
49
40.16%
48
32.00%
64
42.67%
319
97.26%
322
98.17%
180
98.90%
180
98.90%
120
98.36%
119
97.54%
148
98.67%
149
99.33%
136
41.46%
167
50.91%
85
46.70%
100
54.95%
52
42.62%
64
52.46%
74
49.33%
88
58.67%
301–400 Beds
401–500 Beds
501–600 Beds
600+ Beds
2010
2011
2010
2011
2010
2011
2010
2011
% of 328 hospitals
% of 328 hospitals
% of 182 hospitals
% of 182 hospitals
% of 122 hospitals
% of 122 hospitals
% of 150 hospitals
% of 150 hospitals
84
25.61%
91
27.74%
56
30.77%
62
34.07%
34
27.87%
38
31.15%
41
27.33%
48
32.00%
104
31.71%
109
33.23%
68
37.36%
71
39.01%
37
30.33%
42
34.43%
51
34.00%
55
36.67%
53
16.16%
62
18.90%
43
23.63%
47
25.82%
23
18.85%
28
22.95%
31
20.67%
37
24.67%
100
30.49%
109
33.23%
67
36.81%
71
39.01%
40
32.79%
44
36.07%
55
36.67%
63
42.00%
52
15.85%
56
17.07%
42
23.08%
37
20.33%
23
18.85%
24
19.67%
29
19.33%
30
20.00%
87
26.52%
93
28.35%
61
33.52%
62
34.07%
30
24.59%
32
26.23%
46
30.67%
50
33.33%
50
15.24%
51
15.55%
40
21.98%
41
22.53%
22
18.03%
25
20.49%
27
18.00%
33
22.00%
18
5.49%
17
5.18%
15
8.24%
9
4.95%
6
4.92%
5
4.10%
15
10.00%
11
7.33%
145
44.21%
148
45.12%
82
45.05%
88
48.35%
50
40.98%
51
41.80%
51
34.00%
62
41.33%
96
29.27%
100
30.49%
53
29.12%
59
32.42%
33
27.05%
34
27.87%
39
26.00%
47
31.33%
85
25.91%
83
25.30%
48
26.37%
44
24.18%
38
31.15%
38
31.15%
35
23.33%
39
26.00%
40
12.20%
47
14.33%
17
9.34%
17
9.34%
14
11.48%
12
9.84%
27
18.00%
22
14.67%
114
34.76%
130
39.63%
61
33.52%
74
40.66%
49
40.16%
54
44.26%
54
36.00%
56
37.33%
Home Health
2010
% of 1,821
Home Health Facilities
2011
% of 1,821
Home Health Facilities
Home Health Administrative
1,747
95.94%
1,761
96.71%
Home Health Clinical
1,595
87.59%
1,659
91.10%
About HIMSS
HIMSS is a cause-based, not-for-profit organization exclusively focused on providing global leadership for the optimal use of
information technology (IT) and management systems for the betterment of healthcare. Founded 50 years ago, HIMSS and its
related organizations are headquartered in Chicago with additional offices in the United States, Europe and Asia. HIMSS
represents more than 38,000 individual members, of which more than two thirds work in healthcare provider, governmental and
not-for-profit organizations. HIMSS also includes over 540 corporate members and more than 120 not-for-profit organizations
that share our mission of transforming healthcare through the effective use of information technology and management systems.
HIMSS frames and leads healthcare practices and public policy through its content expertise, professional development, research
initiatives, and media vehicles designed to promote information and management systems’ contributions to improving the quality,
safety, access, and cost-effectiveness of patient care. To learn more about HIMSS and to find out how to join us and our members
in advancing our cause, please visit our website at www.himss.org.
About HIMSS Analytics
HIMSS Analytics supports improved decision-making for healthcare organizations, healthcare IT companies and consulting firms by
delivering high quality data and analytical expertise. The company collects and analyzes healthcare organization data relating to IT
processes and environments, products, IS department composition and costs, IS department management metrics, healthcare
delivery trends and purchasing-related decisions. HIMSS Analytics is a wholly-owned, not for profit subsidiary of HIMSS.
HIMSS Analytics
33 W. Monroe St., Suite 1700
Chicago, IL 60603-5616
www.himssanalytics.org
HIMSS
33 W. Monroe St., Suite 1700
Chicago, IL 60603-5616
312-915-9295
www.himss.org
ISBN: 978-1-938904-23-3
ISSN: 1949-0526
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