Health Information Technology
Call for Papers
Clinical Health IT in Hopsitals & Ambulatory Settings
(Including E-Prescribing)
Chair: Christine Elnitsky, Department of Veterans Affairs
Monday, June 26 • 10:30 am – 12:00 pm
●The Promise of Clinical IT Systems? Implications for
Practice from Qualitative Research
Nance Goldstein, Ph.D., MSc, MPhil, BA
Presented By: Nance Goldstein, Ph.D., MSc, MPhil, BA,
Professor / Resident Scholar, Economics Department / WSRC,
University of Southern Maine/ Brandeis University, 14 ½
Fayette St, Cambridge, MA 02139;
Email: nance@brandeis.edu
Research Objective: To capture the experience of clinicians in
adapting to new IT systems that aimed to improve the quality
of patient data, the consistency of care practices and the use
of scarce resources. The study begins to identify possible
effects of IT-mediated documentation on patient care and
workforce attitudes.
Study Design: Observational case study in cardiac/pulmonary
department of urban rehabilitation hospital before and after
implementation of information technology clinical
documentation system in 2002 and 2003. Includes pre- and
post-implementation interviews with 25 clinicians/users. Also
senior hospital and corporate healthcare network executives,
IT managers and planners and professional practice
managers, using a semi-structured protocol.
Population Studied: Observations and interviews of patient
care clinicians and IT system users included nurses, case
managers, physical/occupational/respiratory/ speech
therapists, nurses’ aides and multiple levels of professionals
involved in IT planning and implementation.
Principal Findings: - Clinical users felt they suffered from
design errors, IT shortcuts and the additional required tasks
without acknowledgement or compensation. Clinicians
individually faced the dilemma – sacrifice time with the patient
or stay late to complete IT requirements. - Users noticed the
benefits gained by higher status clinicians (e.g., the
opportunity to work remotely in quiet offices). Also the
implementation excluded key classes of clinicians (for differing
reasons) which increased the workload for system users.
- Resource decisions for IT implementation may ignore or
underestimate the need for supporting time for clinical users
both to enable their contributions to design and
implementation planning and to compensate the extra time
required for successful use of IT as part of patient care work
practices. - While improving the quality and access of up-todate patient data, IT systems also associate data capture with
individual clinicians, threatening to isolate individuals as the
source of medical errors. - One month after the IT
implementation, one-fifth of clinician respondents reported a
decrease in their satisfaction with their job and their
performance. Thirty-five percent disagreed with the statement
that the system’s implementation had increased the quality of
care. The IT department had a backlog of 12 website pages of
changes requested from clinical users.
Conclusions: Clinical IT systems dramatically disrupt patient
care. The new systems represent complex adaptive changes
and important two-way flows as practitioners alter the system
and the IT tools influence work practices, workplace dynamics
and organizational culture. This suggests the need for detailed
studies specific to healthcare contexts – their work practices,
interdependencies and cultural norms.
Implications for Policy, Delivery, or Practice: The study
suggests that researchers, IT professionals and healthcare
administrators consider in much more detail the context for
healthcare IT systems. A wider socio-technical framework for
planning and implementation may optimize the intended
strategic organizational and patient care benefits.
Primary Funding Source: No Funding
●Physicians’ Use of E-prescribing Systems in Today’s
Market
Joy Grossman, Ph.D., Anneliese Gerland, Cheryl Fahlman,
Marie Reed
Presented By: Joy Grossman, Ph.D., Senior Health
Researcher, , Center for Studying Health System Change, 600
Maryland Ave, SW, #550, Washington, DC 20024; Tel: (202)
484-3298; Fax: (202) 484-9258;
Email: jgrossman@hschange.org
Research Objective: In what ways are physician practices
using electronic prescribing? What are the major barriers and
facilitators to electronic prescribing adoption and use?
Study Design: Qualitative analysis of discussions with 12
physician practices with e-prescribing and vantage
organizations such as health plans conducted between
November 2005 and January 2006. The practices were
selected from among the 12 Community Tracking Study (CTS)
sites to provide a mix of practice size and ownership;
physician specialties and geographic location. Respondents
included administrators, physicians and other clinical and
administrative staff who provided perspectives on how the
system is used in the practice; the barriers and facilitators to
adoption and use; and the impact on practice operations,
physician prescribing patterns and patient satisfaction.
Population Studied: Physician practices using e-prescribing
located in the 12 CTS sites.
Principal Findings: Respondents see significant benefits to
using e-prescribing and few would go back to paper.
However, they also identified substantial challenges to
implementing and using these systems. Respondents value
the basic documentation features of e-prescribing systems
most highly. They are more mixed in their assessment of the
value of safety alerts, with many physicians finding them
disruptive and having little impact on prescribing choices.
Pharmacy callbacks for clarifications due to illegibility have
declined dramatically. However, most practices still get
formulary callbacks, because physicians either do not have
access to formulary data or find that it is not complete or
accurate. Similarly, most practices have faced hurdles with
local pharmacies and mail order companies in implementing
electronic faxing. Few have true “end-to-end” electronic
transmissions with pharmacies because of a variety of
factors—the feature is not offered, state regulatory constraints
and/or the lack of readiness of local pharmacies. Respondents
also identified organizational challenges to implementation;
the most substantial being overcoming physician resistance
and changing practice workflow.
Conclusions: There is a substantial gap between the vision of
e-prescribing based on a completely electronic system with
advanced clinical support tools and the reality of how it is
used in physician practices today. While much attention has
focused on physicians’ reluctance to adopt e-prescribing, our
findings suggest that there are substantial challenges to
successful implementation that are due to external factors
outside of the physician practice.
Implications for Policy, Delivery, or Practice: Our findings
suggest policy makers should continue to support efforts
focused on improving the value proposition to physicians of
adopting commercial e-prescribing products. For example,
certification efforts could help ensure the availability of
products that have the most important features to improve
efficiency and quality. Promoting the availability of complete
formulary information would be very valuable, especially with
the introduction of so many Medicare Part D plans. Similarly,
efforts to resolve state regulatory issues and assist pharmacies
in becoming adept at handling electronic transmissions are
critical.
Primary Funding Source: AHRQ
●Case Statement for Implementation of CPOE in all
Massachusetts Hospitals
Doug Johnston, MA, Erica Drazen, Sc.D., Mitchell Adams,
M.B.A., Wendy Everett, Sc.D., Keith MacDonald
Presented By: Doug Johnston, MA, Director of Research,
Research, New England Healthcare Institute, One Broadway,
Twelfth Floor, Cambridge, MA 02142; Tel: (617) 225-0857; Fax:
(617) 225-9025; Email: djohnston@nehi.net
Research Objective: Computerized physician ordered entry
(CPOE) systems have been shown to reduce medical errors,
improve patient safety, and reduce costs in inpatient settings.
However, CPOE adoption rates in Massachusetts hospitals
remain low; only 10 percent of the state’s acute care hospitals
are currently equipped with CPOE, and only 20 percent have
begun installing these systems. One barrier to CPOE
adoption is a compelling analysis of financial value to payers,
providers, and patients. The objective of this study was to
analyze the costs and savings associated with implementing
CPOE in Massachusetts hospitals that do not already have
these systems.
Study Design: A team of researchers from the New England
Healthcare Institute (NEHI), the Massachusetts Technology
Collaborative and First Consulting Group developed a costbenefit model that projected the net savings from inpatient
CPOE adoption in Massachusetts. Cost estimates were
derived using data from hospitals that had previously
implemented vendor-supplied CPOE systems. NEHI projected
savings using data from peer-reviewed literature on reduced
inpatient adverse drug events (ADEs) and improved utilization
of inpatient and emergency department (ED) resources from
CPOE. This model predicted to whom and in what
proportions any potential savings would accrue. Based on
discussions with managed care and hospital reimbursement
experts, the team defined the predominant payment
mechanisms in Massachusetts and calculated the inpatient
and ED benefits following CPOE implementation under each
mechanism. NEHI identified which stakeholder—hospitals,
payers/employers, and patients—would most likely accrue the
benefit in each category. These proportions were then applied
to the calculated total to yield the potential savings accrued to
each stakeholder.
Population Studied: NEHI limited the analysis to benefits
that could be generalized across all Massachusetts hospitals,
payers, and the entire inpatient population.
Principal Findings: NEHI found that the projected costs for
CPOE installation in Massachusetts hospitals amounted to
approximately $210 million over three years, with ongoing
operating costs of $25 million annually. The total estimated
annual benefit for inpatient CPOE in the entire Massachusetts
health care system was $1.48 billion. Reflecting only those
hospitals that have not yet begun CPOE implementation, the
total projected savings was $803.4 million. Adjusting for fixed
hospital costs, and assuming that only 75 percent of the
$803.4 million would be realized, NEHI predicted that CPOE
would save the Massachusetts health care system a total of
$299.4 million. Of this total, $202.1 million, $89.6 million,
and $7.8 million would accrue to hospitals, payers/employers,
and patients respectively. Spreading one-time
implementation costs evenly over three years, annual net
savings from these hospitals would be approximately $275
million.
Conclusions: In addition to patient safety and quality
improvements, NEHI concluded there is a compelling
financial case for the installation of CPOE in all Massachusetts
hospitals.
Implications for Policy, Delivery, or Practice: Achieving
projected cost savings from inpatient CPOE in Massachusetts
requires a coordinated, collaborative initiative between
providers, payers, and vendors of these systems. Such an
initiative should specify system performance and functional
standards, negotiate with key vendors, develop a funding and
incentive program, and establish time frames for achieving
universal inpatient CPOE adoption in Massachusetts.
Primary Funding Source: New England Healthcare Institute
and Massachusetts Technology Collaborative
●Physician Organizations’ Use of Clinical Decision
Support for Order Entry
Jodi Simon, MS, Thomas G. Rundall, Ph.D.
Presented By: Jodi Simon, MS, School of Public Health,
University of California at Berkeley, 9 Longview Court, San
Francisco, CA 94131; Tel: 415-285-2810; Fax: 415-648-5524;
Email: jodi_sacks@yahoo.com
Research Objective: to understand what organizational
structure and market characteristics of physician
organizations are associated with the use of order entry with
decision support for the care of patients with diabetes, asthma
and congestive heart failure.
Study Design: a quantitative nationwide survey of all
physician organizations in the United States with 20 or more
physicians. The data were collected by trained interviewers at
the National Opinion Research Center at the University of
Chicago in 60-minute structured interviews with the CEOs,
presidents, or medical directors of the physician
organizations.
Population Studied: data were collected on 1104 physician
organizations, representing a 70% response rate.
Respondents and non-respondents did not differ by size or
state where they were located. Of the 1104 organizations
responding, 738 were medical groups and 366 were
independent practice associations.
Principal Findings: the use of order entry with decision
support for chronic disease care is not common in physician
organizations; 73% of the organizations did not use order
entry with decision support for any of the three chronic
conditions. The presence of external incentives for quality was
significantly associated with the use of these tools. We found
no statistically significant net relationship between adoption of
these tools and organization size, organization age, hospital
or HMO ownership, level of HMO penetration in the county,
or urban versus rural setting.
Conclusions: the use of order entry with decision support is
not being greatly utilized in physician organizations to help
manage patients with chronic disease. Those organizations
that are leveraging these tools are more likely to be those
experiencing compelling external incentives to improve
quality.
Implications for Policy, Delivery, or Practice: the strong
relationship between external incentives for quality and the
use of order entry with decision support suggests that
environmental factors play an important role in physician
organizations’ decisions to adopt this type of technology.
Policies requiring reporting of chronic care measurements and
rewarding improvement as well are financial incentives for the
use of specific clinical information technology tools are likely
to accelerate adoption in physician organizations.
Primary Funding Source: RWJF
●Adoption of Electronic Prescribing in Community-based
Medical Practices
Christine Vogeli, Ph.D., Michael A. Fischer, M.D., MS, Rainu
Kaushal, M.D., M.P.H., Timothy G. Ferris, M.D., M.P.H.,
Daniel Z. Sands, M.D., M.P.H., Joel Weissman, Ph.D.
Presented By: Christine Vogeli, Ph.D., Instructor of Medicine,
Institute for Health Policy, Massachusetts General Hospital,
50 Staniford Street, 9th floor, Boston, MA 02114; Tel: 617 7240984; Fax: 617 724 4738; Email: cvogeli@partners.org
Research Objective: Emerging data suggests that electronic
prescribing is an important tool for improving both the safety
and efficiency of prescribing. Despite this evidence, adoption
of electronic prescribing systems remains limited, particularly
in the ambulatory setting. This study sought to understand
how quickly physicians adopt electronic prescribing systems
when available, and the patterns of use after adoption.
Study Design: In October 2003, two major health insurers,
their PBMs, and a large e-prescribing company collaboratively
launched a voluntary e-prescribing program in Massachusetts
in which prescribers were provided with eRx software and free
handheld PDAs. The e-prescribing system allows
prescriptions to be written either with a handheld PDA device
or on a personal computer linked to the internet.
Prescriptions are immediately transmitted to pharmacies
electronically or by fax. In order to study adoption rates, we
identified physicians who had been enrolled as users of the
electronic prescribing system and tabulated the frequency with
which they wrote electronic prescriptions between April 2004
and March 2005, the first year the system was in use.
Population Studied: Physicians practicing in a large sample
of community practices in Massachusetts in 2004-2005.
Principal Findings: The number of physicians using the
electronic prescribing system increased steadily, from 131
prescribers in April 2004 to 1,024 in March 2005. The
number of prescriptions per month increased rapidly, from
4,000 in April 2004 to over 55,000 in March 2005. Over time,
electronic prescribers became more active users of the
system, growing from 30 prescriptions per month to 54
prescriptions per month during the study period, an 80%
increase. In the first six months of the study period, only 6%
of enrolled physicians were writing more than 100 electronic
prescriptions per month. By the final month studied this
proportion had more than doubled, with over 15% of enrolled
physicians writing more than 100 electronic prescriptions per
month.
Conclusions: Physician use of electronic prescribing
increased almost ten fold with the provision of an insurance
company subsidized electronic prescribing system. Among
adopters, actual use of electronic prescribing systems by
individual physicians in community settings increased rapidly
An increasing proportion of physicians in our sample became
high-frequency electronic prescribers. Once electronic
prescribing is implemented, actual use can accelerate rapidly.
Implications for Policy, Delivery, or Practice: Electronic
prescribing has been recognized as an important tool for
reducing medication errors and has the potential to allow for
more cost-effective prescribing in inpatient settings. Adoption
of e-prescribing tools in the community setting has the
potential to extend these benefits.
Primary Funding Source: AHRQ
Call for Papers
Making Electronic Health Exchange Real for Providers and
Consumers: Internet, Portal, EMR & Business Case
Chair: Patricia MacTaggart, EDS
Tuesday, June 27 • 8:45 am – 10:15 am
●Developing a Business Case Model for Integrated Child
Health Information Systems
Tim Dall, Kristin Saarlas, MPH, Alan Hinman, MD, MPH
Presented By: Tim Dall, Vice President, The Lewin Group,
3130 Fairview Park Dr., Suite 800, Falls Church, VA 22042; Tel:
703-269-5743; Fax: 703-269-5503; Email: tim.dall@lewin.com
Research Objective: To improve state public health agencies’
capacity to assess the costs and benefits of integrating various
child health information systems (e.g. newborn screening,
early hearing detection and intervention, immunization
registries, WIC, lead screening and birth defects) by
developing a business case modeling tool.
Study Design: The business case model for integrated child
health information systems (ICHIS) was developed with
expert input by a workgroup representing state public health
agencies, physicians, health plans and family advocates.
Assumptions on the marginal costs and benefits of integration
were developed using published literature and unpublished
estimates by the experts in the field. The model, and its
underlying assumptions on effectiveness and efficiencies of
integration, was pilot tested in five states in January 2006.
Population Studied: Costs and benefits associated with state
public health programs related to child health.
Principal Findings: The conceptual framework and underlying
assumptions for the model have been agreed upon by the
workgroup members and represent best available data.
Findings from five states that pilot tested the business case
model in Jan 2006 will be presented, including the feasibility
of using the modeling tool, the validity of the data, and
preliminary cost/benefit results based on different state
information system models. Several areas of the model,
especially those associated with costs of integration, are
lacking and require additional efforts.
Conclusions: Public health agencies need tools to assess the
benefits and costs (i.e., return on investment) of integrating
separate health information systems in order to justify the
additional costs of integration to various stakeholders. The
business case model for ICHIS allows for states to develop a
customized business case to fit their current integration
model as well as estimate a future scenario. Flexible models
such as this tool can provide states with information to decide
which systems should be integrated and provide results from
a societal perspective as well as specific to government,
providers and families/payers. Additional support to states to
collect data and interpret the results of their business cases
are required to maximize the benefit of this tool.
Implications for Policy, Delivery, or Practice: The business
case model for ICHIS can be used to inform policy makers,
public health leaders and providers on the costs and benefits
of health information systems and the impact of such systems
on the delivery and coordination care for children.
Primary Funding Source: HRSA, RWJF
●Time to Reap: Improving Quality by Harvesting Data
from the EMR
Marie Eidem, B.S., Aaron Kurtzhals, B.S., James Naessens,
M.P.H.
Presented By: Marie Eidem, B.S., Lead Analyst/Programmer,
Health Care Policy & Research, Mayo Clinic, 200 First Street
SW, Rochester, MN 55905; Tel: (507)284-5723; Fax: (507)2841731; Email: eidem.marie@mayo.edu
Research Objective: To assess the accuracy and reliability of
immunization data extracted from an electronic medical
record for publicly-reported quality measures.
Study Design: Pneumococcal vaccination data was queried
from our electronic medical record. A computer algorithm
was applied to determine whether this vaccination was
received according to reporting guidelines for ORYX Core
Measures. The algorithm was verified against a small sample
before being fully assessed. These results were compared, at
the patient level, with responses previously collected based on
manual record review by registered nurses. Discrepancies
between the computer-calculated result (EMR) and nurseabstracted result (RN) were reviewed by another nurse, who
determined the “true” (T) immunization status.
Population Studied: Primary and secondary pneumococcal
vaccination data from electronic medical records of 523
patients hospitalized with community acquired pneumonia
(CAP) from 7/1/2004-3/31/2005. Because 289 patients did not
meet pneumococcal vaccination age requirements under
ORYX Core Measures, RN results were not available for them
and they were excluded from analysis. Our current EMR does
not differentiate between refusals and contraindications;
therefore, an additional 7 records without EMR results were
excluded. Also excluded were 3 patients not granting research
authorization, leaving 224 patient records studied.
Principal Findings: Initial discrepancies between EMR and
RN results pointed out minor logic errors in the computer
algorithm. After this was corrected, EMR and RN
assessments matched in 164(73.2%) records: 23 agreed that
vaccination was given during this hospitalization; 119 agreed it
was given prior to hospitalization; and 22 agreed that no
documentation was found. Of the 60 records with
discrepancies, 51 had an RN but no EMR result. Four of those
records plus the remaining 9 with discrepancies were
reviewed by another RN. The EMR result was correct in
12(92.3%) of these cases. Overall, a positive indication from
the EMR was correct in 151 of 151 records(100% positive
predictive value). A negative result from the EMR was correct
in 25 of 73 records(34.2%), due to vaccination documentation
occurring outside of the EMR immunization module.
Evaluation of the discrepancies also brought to light two
potential areas of clinical practice improvement: vaccinations
given multiple times(6) and vaccinations not given until after
dismissal from hospital(3).
Conclusions: The ability to compare manually abstracted and
electronically captured data at the patient level was key in
identifying errors in the computer algorithm. Moving to a
more automated method, where RNs focus abstraction efforts
on cases with no immunization data found in the EMR will
improve accuracy and save valuable staff time. Review and
categorization of discrepancies may identify areas for both
documentation and clinical practice improvement.
Implications for Policy, Delivery, or Practice: Manual
abstraction of quality care measures is a resource-intensive
process that is also subject to human error and bias. With
pay-for-performance initiatives on the horizon, the magnitude
of this problem will certainly grow. Reporting of quality care
measures can no longer rely on manual abstraction by even
the best trained clinical personnel, but must take advantage of
the increasing capabilities of the electronic medical record.
Primary Funding Source: No Funding
●How Older Adults use the Internet to Look for Health
Information
Kathryn Flynn, Ph.D., Maureen A. Smith, M.D., Ph.D., M.P.H.,
Jeremy Freese, Ph.D.
Presented By: Kathryn Flynn, Ph.D., Postdoctoral Fellow,
Center for Clinical and Genetic Economics, Duke University,
PO Box 17969, Durham, NC 27715; Tel: (919) 668-4617; Fax:
(919) 668-7124; Email: kathryn.flynn@duke.edu
Research Objective: Many patients report that they want
more information than their physicians have time to provide.
Health care decision aids may be more successful if we better
understand how patients use non-physician sources of health
information, such as the Internet, to seek health information.
Preparing for an upcoming doctor visit by seeking information
online before a visit may help patients participate in decision
making during a visit. Conversely, seeking information after a
visit may suggest that patients need more information or
support than they received during the visit. Seeking
information online instead of visiting a doctor could be
problematic given the variable quality of information available.
Our objective was to determine how older adults use the
Internet to seek health information, especially with regard to
timing in relation to doctor visits.
Study Design: The Wisconsin Longitudinal Study Graduate
Survey follows a one-third random sample of graduates from
Wisconsin high schools in 1957 using telephone and mail
surveys. Two dependent variables were use of the Internet to
search for health information and timing of use. Explanatory
variables included self-reported effort to stay healthy,
preferences for information and decision making during
health care visits, personality traits, and length of relationship
with a usual provider of care. Multinomial logistic regression
adjusted for gender, marital status, number of children,
rural/farm origin, cognitive ability in high school, educational
attainment, health insurance, SF-12 physical and mental
component summary scores, number of common conditions,
and number of regularly taken prescription medications.
Population Studied: All 5919 respondents, most aged 63 to
66 years, who completed the 2004 telephone and mail
surveys.
Principal Findings: One-third of respondents had searched
the Internet for information about their own health or health
care. Half of these had searched for health information
unrelated to their last doctor visit, while one-third searched
after a visit and one-sixth searched before a visit. Educational
attainment, cognitive ability in high school, and greater
openness-to-experience were positively associated with
searching the Internet for health information irrespective of
timing. Compared to those who had never sought health
information online, sicker individuals (especially those with
cancer) were more likely to seek information online either after
or unrelated to a doctor visit. A preference for being given
many treatment choices rather than letting a doctor make
decisions, greater neuroticism, and greater efforts to stay
healthy were related to seeking health information online
either before or unrelated to a visit.
Conclusions: A significantly smaller percentage of older
adults seek health information on the Internet than some
previous estimates have suggested. Although the majority of
respondents seek health information online unrelated to a
doctor visit, there are important differences in timing. Our
findings provide new insight into how sociodemographic
characteristics, health, cognitive factors, and personality relate
to seeking health information outside of doctor visits.
Implications for Policy, Delivery, or Practice:
Understanding how patients use alternative sources of health
information is important to facilitating shared decision
making. An important next step will be to examine outcomes
associated with seeking health information online and whether
outcomes vary by the timing of or motivation for search
behaviors.
Primary Funding Source: AHRQ
●Hospital-Physician Portals: A First Step In Sharing
Patient Data Across Care Settings
Joy Grossman, Ph.D., Thomas S. Bodenheimer, M.D., Kelly
McKenzie
Presented By: Joy Grossman, Ph.D., Senior Health
Researcher, , Center for Studying Health System Change, 600
Maryland Ave., SW, #550, Washington, DC 20024; Tel: 202484-3298; Fax: 202-484-9258;
Email: jgrossman@hschange.org
Research Objective: To assess the extent of the adoption of
information technology (IT) to share clinical data among
providers in local communities.
Study Design: Qualitative analysis of site visit interviews with
health care executives in 12 Community Tracking Study (CTS)
markets selected to be nationally representative of
communities with populations over 200,000. CTS Round 5
site visits were conducted between January and June 2005.
Over 256 respondents were asked how IT was used to share
clinical data across patient care settings within and across
organizations and the extent to which stakeholder
organizations were engaged in activities to promote
community-wide clinical data sharing activities.
Population Studied: Largest hospitals/hospital systems,
physician groups, safety net providers, and health plans and
local health IT organizations and experts in the 12 CTS
communities.
Principal Findings: Most large hospitals have or are
developing physician portals to provide admitting physicians
with remote access to critical patient records. Portals may also
give physicians the ability to perform transactions such as
ordering tests and signing charts. We found little data
sharing among unaffiliated organizations beyond the evolving
community-wide efforts in Indianapolis and Boston and initial
collaborative discussions in several other sites. Competition
among hospitals for physicians is a key factor driving adoption
of proprietary physician portals. In contrast, provider and
health plan competition and adversarial relationships between
providers and plans are viewed as significant barriers to
community-wide clinical data sharing.
Conclusions: Physicians portals have more limited data
sharing than that envisioned under community-wide health
information exchanges. Access is restricted to physicians
affiliated with the hospital. Moreover, portals are typically
confined to hospital records and in only a few cases provide
access to ambulatory care data. Nonetheless, given the long
time-horizon to developing a national health information
network, physician portals are a small but significant step
towards more complete clinical data exchange. Whether these
proprietary systems are an intermediary step in the evolution
of a nationwide system of clinical data exchange remains to be
seen.
Implications for Policy, Delivery, or Practice: Policy makers
need to consider the important role market competition plays
in spurring or hindering IT adoption. Proposed changes to the
Stark and anti-kickback rules may make it easier for hospitals
to support IT adoption among physicians. They are more likely
to do so if they perceive a competitive advantage to tie
physicians more closely to their institutions. In contrast,
market competition is a substantial barrier to developing
collaborative community-wide efforts, particularly in larger,
more competitive markets where health care organizations are
already making substantial proprietary investments in IT.
Primary Funding Source: RWJF
●New York State Physicians and the Adoption of
Innovation: Use of Internet and E-Mail in Practice, 19992004
Sandra McGinnis, Ph.D., Jean Moore, BSN, MSN, Chris
Morrett, Ed Salsberg, M.P.H.
Presented By: Sandra McGinnis, Ph.D., Research Associate,
Center for Health Workforce Studies, School of Public Health,
University at Albany, 7 University Place, Rm-B334, Rensselaer,
NY 12144; Tel: 518-402-0250; Fax: 518-402-0252;
Email: slm12@health.state.ny.us
Research Objective: To examine the predictors of physician
use of Internet/e-mail for five practice-related functions, and
to examine changes in the profiles of users over time as the
prevalence of use increases.
Study Design: Data are taken from the New York State
Physician Reregistration Survey, which surveys physicians on
their characteristics and practice patterns as they renew their
license on a three-year cycle. Since 1999, the survey has
included a question about use of the Internet/e-mail for five
functions: obtain lab results, x-rays or hospital records; obtain
information about treatment alternatives; communicate
with/answer questions from patients; obtain Continuing
Medical Education credits; and transmit prescriptions to
pharmacies. Ordinary least squares regression is used to
analyze the predictors of technology use during the three
survey cycles. Predictors are compared for the same types of
use during different periods, to provide a profile of how
physicians move through the five stages of adoption of
innovation introduced by Rogers (1995).
Population Studied: Physicians active in practice in New York
State, 1999-2004.
Principal Findings: Use of Internet/e-mail by physicians has
increased for all five of the functions analyzed between 19992004. Use rates in the 2003-2004 do not exceed 50% for any
function, however, indicating that physician use of technology
remains in either the early adopter or early majority stage for
all five functions. Predictors of technology use vary between
the five functions. The profile of users for each function also
changes over time, with age and gender differences in
particular becoming less salient between users and non-users
between the innovator, early adopter, and early majority stage.
Conclusions: Use of Internet/e-mail by physicians in New
York State has increased markedly, but has not yet entered the
late majority stage. Use of Internet and e-mail is being
adopted more quickly for some functions (e.g. obtaining CME)
than for others (e.g. transmitting prescriptions). The profile of
physicians who use Internet/e-mail for functions that are less
common differs in some important ways from the profile of
physicians who use the technology for functions that have
become more common. In particular, demographic
characteristics of physicians are more associated with use in
early stages of adoption, while practice patterns such as
specialty and setting are more associated with use in later
stages of adoption. Results also imply, however, that the early
users of technology for one function are not necessarily the
early users of technology for other functions, pointing to a
need for further research focused on the adoption of specific
types of technology.
Implications for Policy, Delivery, or Practice: Given the
tremendous attention focused on implementing better health
information technology systems, the results may prove a
valuable tool to identify physicians who are the first to use
Internet/e-mail technology for various functions and those
who still do not use Internet/e-mail for these functions. This
has important implications for marketing new technologies
towards those who are more likely to be innovators, while
targeting policies designed to encourage technology use
towards physicians who may be most resistant to use of
technologies. This may also inform the design of new
products and services to complement and capitalize on
existing patterns of use, leading to more efficient transitions
to new technologies.
Primary Funding Source: Other
Related Posters
Health Information Technology
Poster Session A
Sunday, June 25 • 2:00 pm – 3:30 pm
●The Influence of Environmental Factors on EHR
Adoption by Physicians
Maziar Abdolrasulnia, M.B.A., M.P.H., Richard M. Shewchuk,
Ph.D., Nir Menachemi, Ph.D., W. Jack Duncan, Ph.D., Douglas
J. Ayers, Ph.D., Robert G. Brooks, M.D.
Presented By: Maziar Abdolrasulnia, M.B.A., M.P.H.,
Doctoral Student, Health Services Administration, University
of Alabama at Birmingham, 2010 5th Street South,
Birmingham, AL 35205; Email: maziabdo@uab.edu
Research Objective: Despite the benefits associated with
electronic health record (EHR) systems, physicians have been
slow to adopt this technology. Existing studies that have
examined EHR adoption have largely ignored environmental
factors that may influence the decision to adopt. We examined
the relationship between county level characteristics and EHR
adoption in small to medium-sized physician practices.
Study Design: This project combined both primary and
secondary data. The two main sources of the data include (1)
A physician IT survey conducted in Florida during the spring
of 2005; and (2) 2004 area resource file (ARF) containing
county characteristics. Based on the associated healthcare
literature, we operationalized environmental factors per
county as physicians per capita, Medicare managed care
penetration, and poverty level. We used hierarchical logistic
regression analysis to examine the relationship between these
environmental factors and EHR adoption by physicians.
Population Studied: A total of 2961 physician practices were
analyzed. The majority (94%) of physician practices were in
urban area, 38% were solo practices, 48% were in groups of
two to five, and 14% were in groups larger than 6. Mean (std.
dev.) years since medical school of the sample was 21.1
(±10.0) years.
Principal Findings: Overall 17.4% of physicians self-reported
adoption of EHRs. After controlling for practice and county
level characteristics, physicians per capita was positively and
significantly associated with EHR adoption (OR = 1.15, p =
.015) and percent Medicare managed care penetration was
negatively and significantly associated with EHR adoption (OR
= .981, p <.001). Physicians practicing in an HMO setting were
more likely than single specialty practices to adopt EHRs (OR
= 2.46, p = .039). Additionally, physicians in groups of six or
more were more likely to adopt EHRs than those practicing
solo (OR = 1.73, p = .001). Moreover, physicians adopting
other type of information technologies were more likely to
adopt EHRs than those not adopting or adopting few
information technologies (OR = 1.46, p < .001). Lastly, years
since medical school and county poverty rate were not related
to EHR adoption by physicians.
Conclusions: Competitive, regulatory, and practice
characteristics are associated with the decision to adopt EHRs
by physicians. Adoption of EHRs may be even more
advantageous in certain environments.
Implications for Policy, Delivery, or Practice: Our findings
suggest that environmental factors influence the adoption of
EHR systems by physicians. These findings may assist both
policy makers and physicians who are interested in promoting
EHR adoption and/or better understanding the strategic
environment and it’s affect on the adoption of this technology.
Primary Funding Source: CMS
●The Foundation for Medicaid’s Role in the Adoption of
Health Information Technology
Shaun Alfreds, M.B.A., Michael Tutty, MHA, Jay Himmelstein,
M.D., M.P.H., Mark Frisse, M.D., Patricia MacTaggart, M.B.A.,
Bruce Greenstein
Presented By: Shaun Alfreds, M.B.A., Project Director, Center
for Health Policy and Research, University of Massachusetts
Medical School, 222 Maple Avenue, Shrewsbury, MA 01545;
Tel: (508) 856-8634; Email: shaun.alfreds@umassmed.edu
Research Objective: This paper defines the challenges and
opportunities that state and federal agencies might play in
leveraging HIT developments to improve the quality of
healthcare for Medicaid beneficiaries and the efficiency of
Medicaid operations. In addition, it provides actionable policy
recommendations from national experts for federal and state
agencies.
Study Design: An advisory committee of thought leaders
from federal and state governments, policy organizations, HIT
vendors, and healthcare provider groups was convened to
identify key issues and research necessary to inform an expert
panel meeting held in March of 2006. Recommendations of
the advisory committee and the expert panel are summarized
and presented in this paper.
Population Studied: Medicaid agencies, Medicaid
beneficiaries, and providers serving Medicaid covered
individuals throughout the country.
Principal Findings: The value of HIT as a tool to provide
higher quality of care and more efficient operations has been
recognized. Interoperable health information systems are
evolving into regional health information networks, which may
further mature into a National Health Information
Infrastructure. Medicaid agencies, the largest payer of
healthcare for low income and vulnerable populations, must
participate in these information sharing networks not only to
realize the benefits for their beneficiaries and internal
operations, but also in order to address the needs of Medicare
beneficiaries, the commercially insured, and the uninsured. To
date however, Medicaid agencies have had limited
involvement with advanced HIT due to the complexity of the
populations served, the providers serving them, and perceived
legal, fiscal and regulatory barriers. Overall recommendations
for Medicaid involvement in the HIT arena are provided with
specific emphasis on five areas. These are: 1) Using HIT to
Improve Healthcare Quality for Medicaid Beneficiaries, 2)
Leveraging HIT to Improve Medicaid Agency Efficiencies, 3)
Financial and Non-Financial Incentives to Illicit Medicaid
Provider Adoption of HIT, 4) Legal and Regulatory Issues in a
Medicaid Context, and 5) Case Studies of Medicaid and State
Government Involvement in HIT Initiatives.
Implications for Policy, Delivery, or Practice: This paper
captures key recommendations made by thought leaders and
policy experts on necessary policy decisions defining the roles,
needs, and priorities of Medicaid programs in facilitating the
use of HIT to achieve safe, high quality, accessible, and
efficient healthcare for Medicaid beneficiaries as well as the
citizens of the states they serve.
Primary Funding Source: AHRQ
●Electronic Health Records in Four Community Physician
Practices: Impact on Quality and Cost of Care
Dawn Bazarko, RN, M.P.H., W. Pete Welch, Ph.D, Kimberly
Ritten, Yo Burgess, , Robert Harmon, M.D., M.P.H., Lewis G.
Sandy, M.D., M.B.A.
Presented By: Dawn Bazarko, RN, M.P.H., Senior Vice
President, Care Improvement Strategies, United Clinical
Advancement, UnitedHealthcare, 5901 Lincoln Drive, MN012S117, Edina, MN 55436; Tel: 952-992-4283; Fax: 952-992-5028;
Email: dawn_m_bazarko@uhc.com
Research Objective: To assess the impact of the electronic
health record (EHR) on cost (to the payer) and quality of care
in physician practices in the community. Most other such
studies to date have been limited to a single practice with inhouse research capabilities.
Study Design: Retrospective before-after-study-control.
Studying multiple community practices requires two types of
information: a large claims database and local knowledge of
which practices had EHRs. With the help of the medical
directors of a large managed care organization (MCO), we
identified four community physician practices (in three
metropolitan areas) that had implemented EHR in the last five
years. These practices were interviewed both before and after
our data analysis. About fifty practices without EHR were
identified in the same county as one of the study practices.
As we defined them, periods before and after implementation
varied across study practices but were the same for a study
practice and its controls. We used two commercially-available
software products to analyze episodes involving one of four
chronic conditions. Episode Treatment GroupsTM (ETGs)
were used to measure cost of care and adjust it for casemix.
Allowed charges on claims were “re-priced” to remove any
impact of price differences. EBM ConnectTM was used to
analyze the rate of adherence to clinical guidelines as a
measure of quality. Several guidelines were used for each of
the four chronic care conditions. Tests for significance were
applied to the difference in the change (in cost or quality)
between study and control practices.
Population Studied: Patients enrolled in a large MCO who
had at least one of four chronic conditions: hypertension,
hyperlipidemia, diabetes, and selected heart conditions.
About 90,000 episodes of care were analyzed.
Principal Findings: The implementation of the EHR did not
significantly affect the cost per episode (minimum detectable
difference of 3.5 percent of the mean). It had a significant,
modest positive impact on the quality measure of guideline
adherence for hypertension (2 percentage points) and
hyperlipidemia (5 percentage point), but no significant impact
for diabetes and coronary artery disease. Interviews with the
study practices revealed that the timing and
comprehensiveness of EHR implementation varied across
practices, creating an intervention variable that was
heterogeneous.
Conclusions: Guideline adherence is increasing across
practices without EHRs and slightly faster in practices with
EHRs. The increase in non-EHR practices is consistent with
reports that many of the functionalities of EHRs can be
obtained in other ways. Measuring the impact of EHRs on
cost per episode is challenging, because of the difficulty of
capturing the later costs of a chronic condition.
Implications for Policy, Delivery, or Practice: Our findings
tentatively suggest that the advantages of current EHRs may
be overstated.
Primary Funding Source: AHRQ
●HIT and QI: A State-Wide Educational Quality
Improvement RCT among Texas Rural Hospitals
Giovanni Filardo, M.P.H., Ph.D., David Nicewander, MS, Percy
Galimbretti, M.D., Ph.D., Susan McBride, Ph.D., RN, Josie
Williams, M.D., MMM, David Ballard, M.D., MSPH, Ph.D.
Presented By: Giovanni Filardo, M.P.H., Ph.D.,
epidemiologist, Institute for Health Care Research and
Improvement, Baylor Health Care System, 8080 North Central
Expressway, Suite 500, Dallas, TX 75206; Tel: 214-265-3633;
Fax: 214-265-3640; Email: giovanfi@baylorhealth.edu
Research Objective: Hospitals are under increasing pressure
to measure and report their quality of care and to improve
quality. Particularly with the growing popularity of “pay for
performance” programs, hospitals’ continued viability is
dependant on their ability to measure quality indicators and to
improve performance relative to these indicators. Although a
number of formal quality improvement education programs
are offered nationwide, we are conducting the first to target
rural hospitals.
Study Design: A hospital-randomized controlled trial,
following implementation of a web-based hospital quality of
care benchmarking and case review tool in rural and small
community hospitals in Texas. Sixty hospitals or more that
demonstrate the successful implementation of the web-based
tool will be randomly assigned to receive a rapid cycle
educational program on methods and techniques for
implementing and evaluating quality improvement initiatives
or not (control group). The seven day (three 2 day methods
sessions interspersed over 2 months with project coaching
between sessions and during follow-up, coupled with a daylong project reporting conclave) educational program will
enroll for each hospital a physician, nurse and administrator.
The curriculum is designed to facilitate the development of
skills and competencies needed to implement quality
improvement efforts. The incremental benefit of this
educational program – over and above the effect of the
benchmarking and case review tool – will be evaluated by
comparing quality of care measures (Centers for Medicare and
Medicaid Services core inpatient indicators for eligible
patients admitted with congestive heart failure [CHF] or
community acquired pneumonia [CAP]), patient safety
(selected Agency for Healthcare Research and Quality [AHRQ]
indicators), and all-cause inpatient mortality between the
treatment and control groups for 2 years following the
educational intervention.
Population Studied: Rural and small community hospitals in
Texas, defined as hospitals located in a county in Texas with
<150,000 inhabitants according to data from the U.S. Bureau
of the Census 2000, or listed in the American Hospital
Association 2003 dataset and designated as a Critical Access
Hospital.
Principal Findings: The minimum detectable differences
between study groups, estimated for the selected patient
safety and quality indicators using methods appropriate for
cluster-randomized studies with a binary outcome have been
calculated on a sample of 66 small community rural or small
community hospitals in Texas. Given the estimated baseline
rates for composite quality scores for CHF (62%) and CAP
(56%), the size of the hospital cohort enables detection of 13%
and 10% differences (a=.05, power=.8) respectively, between
study groups.
Conclusions: N/A
Implications for Policy, Delivery, or Practice: This project
begins the work of assessing the current information
technology capabilities of rural and small community
hospitals in the United States, and determining how these
capabilities can best be enhanced to improve the quality in
such hospitals. It also addresses the issue of whether extant
quality of care measures are applicable to rural and small
community hospitals, or whether their low patient volumes
and other unique characteristics require the development of
tailored measures. This project is supported by the AHRQ
(RFA-HS-04-011).
Primary Funding Source: AHRQ
●Evaluation of Ambulatory EHR Deployment: Quality and
Fiscal Effects
Neil Fleming, Ph.D., CQE, Donald Kennerly, M.D., Ph.D.,
Edmund Becker, Ph.D., Robert Mayberry, Ph.D., M.P.H.,
Steven Culler, Ph.D., David Ballard, M.D., MSPH, Ph.D.
Presented By: Neil Fleming, Ph.D., CQE, Vice President,
Health Care Research, Institute for Health Care Research and
Improvement, Baylor Health Care System, 8080 North Central
Expressway, Suite 500, Dallas, TX 75206; Tel: 214-265-3601;
Fax: 214-265-3640; Email: neilfl@baylorhealth.edu
Research Objective: The objective is to quantify the effects of
an ambulatory electronic healthcare record (AEHR) on the 6
Institute of Medicine domains of quality and financial
performance in primary care practices.
Study Design: This is an observational cohort study
comparing quality and financial measures pre-and post
implementation of an AEHR across HealthTexas Provider
Network (HTPN), the ambulatory care component of Baylor
Health Care System (BHCS) in Dallas, TX. Comparisons will
be based on patient-, physician-, and practice-level data, for
measures of Safe, Timely, Effective, Efficient, Equitable, and
Patient-centered care. Measures of practice financial
performance (monthly practice margin [overall patient
revenues minus practice expenses] per physician) and practice
financial efficiency (practice expense per RVU and staffing
expenses) pre- and post-AEHR implementation will be
compared. AEHR implementation will be staggered across
practices over 3 years, allowing both cross-sectional (between
AEHR practices and non-AEHR at fixed time points) and
longitudinal (between measures collected within the same
practices before and after AEHR implementation)
comparisons. Net financial impact of the AEHR, including
actual costs of implementation and maintenance, will be
determined. Patient safety will be measured according to the
rate of adverse events (including drug-related events) detected
in the elderly Medicare population using the Institute for
Healthcare Improvement’s ambulatory care trigger tool preand post-AEHR implementation. Effective care will be
operationalized using a composite measure for delivery of 11
adult clinical preventive services (CPS). Patient satisfaction
survey data incorporate patient-centeredness (overall
satisfaction and willingness to recommend) and timeliness
indicators (time waited for appointment and office waiting
time). Equity will be evaluated by comparing performance on
safety, effectiveness, timeliness, and patient-centeredness
measures across age, gender, race/ethnicity, and socioeconomic status. Efficiency will be measured using physician
RVUs, based on CPT-4 codes from patient visits, for services
related to laboratory/pathology, and radiology.
Population Studied: HTPN includes 66 practices throughout
Dallas-Fort Worth. Since processes of care and associated
costs differ by specialty, this analysis will focus on primary
care physicians and practices (32 practices and 183
physicians).
Principal Findings: Baseline data show 14% of patients wait
>30 days between making and keeping an appointment, and
15% have >30 minute in-office wait times; the composite score
for the 11 CPS indicators (proportion of opportunities per
patient achieved) is 0.87; 92% of patients report excellent or
very good satisfaction with their physicians, and 97% report
they would recommend their physician to other people.
Baseline equity data show patients with higher SES are more
likely to receive CPS that those with lower SES (0.87 mean
composite score vs 0.83) and more likely to report “excellent”
or “very good” satisfaction (93% vs 90%). Minimum
detectable effects (? = 0.05, power =0.80) are 4.5% for adverse
drug events; 0.11 standard deviations for time waited for an
appointment and in-office waiting time; 2.2% for delivery of
CPS; and 0.05 standard deviations for overall satisfaction with
physician and willingness to recommend.
Conclusions: n/a
Implications for Policy, Delivery, or Practice: This study will
inform decisions to invest in AEHR from both quality and
fiscal perspectives.
Primary Funding Source: No Funding
●Multi-Hospital System Membership and Diffusion of
Health Information Technology
Michael Furukawa, Ph.D.
Presented By: Michael Furukawa, Ph.D., Assistant Professor,
Health Management and Policy, Arizona State University, P.O.
Box 874506, Tempe, AZ 85287-4506; Tel: (480) 965-2363; Fax:
(480) 965-6654; Email: Michael.Furukawa@asu.edu
Research Objective: Health information technology (HIT) is
widely-regarded as a key strategic resource to increase
efficiency and improve quality of care. Despite growing
interest in HIT by managers and policymakers, few studies
have examined the determinants of HIT adoption. In
particular, little is known about the role of multi-hospital
system membership in the diffusion of HIT across hospitals
and affiliated organizations. This study seeks to address this
gap in the literature by examining the effect of system
membership on the adoption of HIT by hospitals, sub-acute,
and ambulatory facilities.
Study Design: The primary data source is the 2004 HIMSS
Analytics (HA) Database, which contains detailed information
on the adoption of HIT within integrated health delivery
systems. The HA database is linked to the 2002 AHA Annual
Survey Database, which provides information on hospital
characteristics and system membership, and to the 2004 Area
Resource File, which provides information on area
characteristics. I test the overall effect of system membership
and of system type (centralized, centralized
physician/insurance, moderately centralized, decentralized,
and independent) on HIT adoption, controlling for facility and
area characteristics. Dependent variables include specific HIT
applications (e.g., computerized patient records,
computerized physician order entry), and the type of HIT
defined by 4 categories: financials and business office; medical
records and administrative; management and human
resources; and clinical and ancillary departments. I estimate
probit regressions of the probability of HIT adoption and
negative binomial regressions of the count of HIT within each
category. I address the potential endogeneity of system
membership using propensity score weighting in a
multinomial selection model.
Population Studied: U.S. short-term, non-federal hospitals
and affiliated organizations in 1,453 integrated health care
delivery systems. The sample includes 3,989 hospitals, 3,007
sub-acute, and 18,008 ambulatory care facilities.
Principal Findings: I find that multi-hospital system
membership is a strong determinant of HIT adoption. Overall,
system membership is associated with greater adoption
across all categories of HIT, but most significantly for
management and financial applications. Facilities in
centralized physician/insurance health systems are much
more likely to adopt clinical IT relative to independent hospital
systems.
Conclusions: Members of multi-hospital systems have
greater levels of HIT adoption than facilities in independent
hospital systems. However, system membership appears to
have a differential effect on the type of HIT, with only
marginally significant effects on the adoption of clinical IT.
HIT adoption also varies by system type, suggesting that
centralization, integration, and insurance offerings are key
system characteristics that are associated with the adoption of
clinical IT.
Implications for Policy, Delivery, or Practice: The
consolidation and integration of hospitals, physicians, and
affiliated organizations into multi-hospital systems has
important implications for the adoption and diffusion of HIT.
System membership may confer network effects because HIT
adoption confers benefits to the adopter as well as affiliated
facilities. The findings of this study suggest that governance
and organizational structure play a key role in the diffusion of
HIT across facilities within a system.
Primary Funding Source: No Funding
●Evaluation of an Integrated, Web-based Computer
System for Patients Living with HIV/AIDS
Daniel Gentry, Ph.D., M.H.A., Stacie Metz, M.P.H., M.S.W.,
MA, Kathye Gorosh, M.B.A.
Presented By: Daniel Gentry, Ph.D., MHA, Associate
Professor, Dept. of Health Management and Policy, Saint
Louis University School of Public Health, 3545 Lafayette, Salus
Center 300, St. Louis, MO 63104; Tel: 314-977-8152; Fax: 314977-1441; Email: dgentry@slu.edu
Research Objective: To conduct a process and outcome
evaluation of a patient-centered, web-based computer system
for people living with HIV/AIDS; 7 process evaluation
questions and 4 outcome evaluation questions were specified.
Study Design: This was a prospective study that followed and
compared four different cohorts who utilized the Community
and Minority Education and Training Initiative for HIV/AIDS
(COMET). The vast majority of data were systematically and
routinely collected over a period of 18 months (November
2003-May 2005); the data collection was integrated into the
web-based system. Additional qualitative data were collected
through client focus groups.
Population Studied: Four populations were studied: 79
English-speaking CORE Center patients who were returning
users; 137 new English speaking patients; 108 Spanishspeaking users; and 86 users from a separate communitybased organization. All patients were living with HIV/AIDS.
Total n=410.
Principal Findings: Five types of principal findings are
reported: client demographics, client COMET usage, provider
COMET usage, COMET client focus group feedback, and
service referrals for COMET clients. Selected findings include:
64% of COMET users on HIV/AIDS medications reported
being non-adherent at some point; the most frequently
accessed COMET activity was the "Knowledge" function
(provides information on the immune system, medication,
wellness, etc.). In addition to findings, limitations are also
discussed.
Conclusions: Stengths of the COMET program included: the
opportunity to learn and use computers, and increased access
to the patient's own medical information. Weaknesses of
COMET included: delays in posting of lab results, limited
computer and COMET training for clients, and very limited
participation by physicians and other providers.
Implications for Policy, Delivery, or Practice: Patient
empowerment, self management and medication adherence
are areas of growing importance in terms of improving patient
access and quality and for cost-effectiveness. The COMET
program has received additional funding not only for
continuation but also for replication by other service
providers. The results of this evaluation will be used to
improve the program, designate additional outcome
measures, and develop tools for program monitoring. Both
the full evaluation report(34 pages) and an executive summary
(3 pages) will be made available to session participants.
Primary Funding Source: U.S Office of Minority Health
●Record Linkage Research and Informed Consent: Who
Consents?
Nicole Huang, Ph.D., Shu-Fang Shih, MS, Hsing-Yi Chang,
Ph.D., Yiing-Jenq Chou, M.D., Ph.D.
Presented By: Nicole Huang, Ph.D., Assistant Professor,
Institute of Public Health, National Yang Ming University, 155,
Li-Nong Street, Section 2, Taipei, 112; Tel: 886-2-28201458;
Fax: 886-2-28261002; Email: syhuang@ym.edu.tw
Research Objective: Recently, linking survey data on
individuals with administrative records has become a popular
data source in medical and public health research.
Government requirement of written informed consent before
accessing health records may introduce a selection bias if
consenting patients differ from those who do not give
consent. This study aimed to compare interviewees of a
national health survey who consent and refuse for access to
their national health insurance records in Taiwan.
Study Design: A cross-sectional study
Population Studied: A national representative sample
(n=14,611 adults) of the general adult population aged 20
years or older were interviewed by the staff of the Taiwan
National Health Interview Survey (NHIS)and asked for a
written permission for their National Health Insurance records
to be reviewed. Survey responses were used to compare
interviewees by consent status.
Principal Findings: Of the 14 611 NHIS participants, 12 911
(88%) gave consent, and 1 700 (12%) denied consent. The
multivariable analysis indicates that the elderly aged 65 or
above, the illiterates, people with monthly household income
less than US$ 950, and the rural area residents were more
likely to decline consent than their counterparts. On the other
hand, health status did not seem to have a strong influence
on consent -giving or -withholding.
Conclusions: Consenters differed from non-consenters
significantly in important aspects such as age, educational
background, socioeconomic status and residential location.
The non-uniform distribution of these variables may be
significantly related to utilization and health outcomes.
Implications for Policy, Delivery, or Practice: Therefore,
record linkage research restricted to consenters only, runs the
risk of miss-characterizing the utilization and health outcomes
of the general population and lead to selection bias. Higher
refusal rates observed among sub-populations of the elderly
and the illiterate suggest that more effective communication
strategies may help to reduce refusal rates among these
groups. This may minimize possible selection bias in large
scale record linkage studies in Taiwan.
Primary Funding Source: Taiwan's National Science Council
●Facilitating the Implementation of Health Information
Technology in the State of Louisiana Through Medicaid
Michelle Lim Warner, M.P.H.c
identifying ways to achieve widespread implementation at the
national level.
Primary Funding Source: No Funding
Presented By: Michelle Lim Warner, M.P.H.c, Master in
Public Health Candidate, School of Public Health and Health
Services, George Washington University, 4615 North Park
Avenue #909, Chevy Chase, MD 20815; Tel: (202) 841-9639;
Email: milim@gwu.edu
Research Objective: Louisiana has a unique opportunity to
re-design its health care system by focusing its re-building
efforts on creating an interoperable health information
technology (HIT) infrastructure. Medicaid, as the single
largest purchaser of health care in a state, is in a unique
position to further this effort. This paper will explore and
identify optimal strategies for Medicaid to employ in order to
facilitate the implementation of HIT in the State of Louisiana.
Study Design: Involves an extensive review of the literature
related to HIT and discussions with thought leaders from
Louisiana state government, the federal government and
experts in the field of health care financing, health policy,
Medicaid administration, and electronic health information
systems.
Population Studied: Louisiana Medicaid Agency, Louisiana
Medicaid recipients and providers serving Medicaid covered
individuals
Principal Findings: HIT has the potential to improve health
care quality and the efficiency of a health care delivery system.
Yet widespread adoption and use of such technology has been
occurring at a far slower pace than is desirable. Many
barriers, such as cost and legal and regulatory impediments,
have limited the rapid adoption of HIT. However, the
ramification of Hurricane Katrina to the Louisiana health care
system illustrated the critical need for HIT to preserve and
protect patient health records and maintain a working health
care delivery system. As any state’s largest single purchaser of
health care, Medicaid is in a position to facilitate the
implementation of HIT. Medicaid has many levers from
which to further this effort – one of which is purchasing for
quality. Louisiana is currently ranked 49th in the nation in
terms of health care quality, and can benefit from having an
HIT infrastructure supporting its health care system.
Specifically, Medicaid can employ payment strategies such as
pay-for-performance to incentivize its providers to utilize HIT.
Medicaid can also employ regulatory and other providerrelated approaches, as well as partnering with other funders to
facilitate and achieve HIT implementation.
Conclusions: Medicaid has a significant impact on furthering
the HIT movement and can be leveraged to facilitate the
implementation of HIT in states.
Implications for Policy, Delivery, or Practice: This paper
provides a new lens from which to view the evolution of HIT
implementation in two ways: (1) by focusing on HIT
implementation at the state-level and (2) by identifying
strategies for Medicaid to leverage in facilitating the effort and
furthering the HIT movement. Much of the visible activity
around HIT adoption and implementation are occurring at the
national level. Yet the problems and issues related to health
care delivery are addressed at the local level. Furthermore, the
potential of HIT to improve health care is first realized at the
local level. As such, taking a look at how the largest purchaser
for a state can move the HIT agenda forward is critical to
●Improving Cancer Symptom Management through
Information Technology
Tami Mark, Ph.D. M.B.A., Barry Fortner, Ph.D., Gina Johnson,
APRN, MSN, Xue Song, Ph.D.
Presented By: Tami Mark, Ph.D. M.B.A., Associate Director,
Outcomes Research, Thomson/Medstat, 4300 Connecticut
Avenue, NW Suite 330, Washington, DC 20008; Tel: (202) 719
-7832; Fax: (202) 719-7801; Email: Tami.Mark@thomson.com
Research Objective: To conduct a randomized trial to assess
the ability of a computerized symptom screening and
educational program to improve cancer symptom
management following chemotherapy (specifically,
depression, pain, and fatigue).
Study Design: The PACE system was installed in two
community cancer clinics naive to the intervention. Patients
were randomized to receive the PACE system or standard
care. Assessments were distributed monthly or bi-monthy to
determine whether physicians were discussing symptoms,
whether symptoms were being treated, the level of symptoms
experienced, the level of satisfaction with information
provided about cancer treatment, and attitudes towards pain
management. Subsequent surveys were conducted with
providers to determine their level of satisfaction with the PACE
System™ (survey is presently in the field).Between June, 2004,
and December, 2004, 350 patients were screened at two
community oncology clinics. Of those patients, 78 met the
inclusion criteria and were invited to participate in the study.
Forty-eight (48) patients agreed to participate. The most
frequent reason for exclusion was that patients were not newly
initiating chemotherapy.
Population Studied: Patients treated at two community
oncology clinics who were starting chemotherapy, were 18 and
older, and literate.
Principal Findings: The monthly patient reported assessment
showed a trend toward more provider discussion of pain
symptoms among patients with pain (p 0.12) and less
discussion of fatigue among patients without fatigue (p =
0.004). There was no difference in discussion of depression
although patients with depression were less likely to report
that the clinic could have done more to assess their
symptoms (p = 0.09). Patients in the intervention group had
lower scores in the memorial symptom assessment scale in
follow-up months than patients in the intervention group (p =
0.03) indicating lower levels of symptoms. There were no
differences between the control and intervention groups in the
scores on the HADS-anxiety scale, the HADS-depression
scale, and the Spitzer QoL life instrument. Patients in the
intervention group were more satisfied with the information
that they received on chemotherapy treatment and had less
fatalistic attitudes towards pain management.
Conclusions: There is evidence that The PACE System™ is
having a positive effect on cancer symptom identification,
targeting, and management, as well as patient information
about and attitudes towards cancer symptom management.
Implications for Policy, Delivery, or Practice: The NIH
recently concluded that cancer symptom management has
lagged behind cancer treatment and that frequently symptoms
go undetected and untreated. Information technology can be a
viable method for improving symptom assessment and
management as well as educating patients about cancer
treatment.
Primary Funding Source: RWJF
●The Effect of IT Adoption on JCAHO Performance Scores
in Florida Hospitals
Nir Menachemi, Ph.D., M.P.H., Anol Bhattacherjee, Ph.D.,
Neset Hikmet, Ph.D., Onur Kayhan, B.S., Robert G. Brooks,
M.D.
●Barriers to Ambulatory EHR: Who are “Imminent
Adopters” and How do They Differ From Other
Physicians?
Nir Menachemi, Ph.D., M.P.H.
Presented By: Nir Menachemi, Ph.D., M.P.H., Assistant
Professor, Division of Health Affairs, Florida State University
College of Medicine, 1115 West Call Street, Tallahassee, FL
32306; Tel: (850) 644-2362; Fax: (850) 645-2859; Email:
nir.menachemi@med.fsu.edu
Research Objective: This empirical study examines the
relationship between healthcare information technology (IT)
investments and operational performance in Florida hospitals.
Unlike most prior studies in this area that have measured IT
investment at the macro or facility level, we measure IT
investment at the micro or technology level, which allowed us
to explore technological differences among various types of IT
investments.
Study Design: This unique project combines both primary
and secondary data. The primary data comes from a hospital
IT survey conducted in Florida between May and October
2003. Secondary data, used to construct the dependent
variable (operational performance), was obtained from the
Joint Commission of Accreditation of Healthcare
Organizations (JCAHO). JCAHO is an independent national
agency responsible for auditing and certifying performance
and quality ratings of US hospitals. Using the IT data
collected, and previously devised methods, we operationalized
IT capabilities in three main hospital functional areas;
administrative, clinical, and strategic. Regression analyses
were used to examine the relationship between these IT
capabilities and overall JCAHO performance score. Each
model specified bed-size and hospital case-mix as covariates.
Population Studied: A total of 96 Florida hospitals were
included. They were representative of hospitals in the state in
terms of size, system-affiliation, and tax-status.
Principal Findings: Our measure of overall IT utilization
(p=0.04) was positively associated with operational
performance as measured by the JCAHO performance scores
(R2=0.115). However, clinical IT adoption (p=0.006), and not
administrative (p=.232) or strategic IT (p=0.13) adoption, was
responsible for this strong and significant relationship.
Conclusions: Hospitals in our dataset that have adopted
more clinical IT applications performed better on JCAHO
performance evaluations. This occurred most probably
because clinical technologies such as computerized physician
order entry systems, chart tracking systems, and laboratory
information systems, are directly targeted at improving and
transforming the management and delivery of healthcare.
Implications for Policy, Delivery, or Practice: This study
provides evidence that the adoption of IT, particularly clinical
applications, is associated with improved operational
performance. Additionally, our findings provide preliminary
evidence that not all categories of HIT have equivalent effects
on facility performance. Therefore, unlike previous studies,
different classes of health IT should be examined separately to
achieve a better estimate of the performance effects of health
IT.
Primary Funding Source: No Funding
Presented By: Nir Menachemi, Ph.D., M.P.H., Assistant
Professor, Family Medicine and Rural Health, Florida State
University College of Medicine, 1115 West Call Street,
Tallahassee, FL 32306; Tel: (850) 644-2362; Fax: (850) 6452859; Email: nir.menachemi@med.fsu.edu
Research Objective: Despite existing knowledge regarding
EHR barriers in the ambulatory setting, little is known,
specifically, about physicians who are likely to adopt EHR
imminently. The current study identifies these imminent
adopters and compares their barriers to other physicians.
Study Design: Mailed survey of Florida physicians (n=14,921)
about barriers to EHR and adoption intentions. Physicians
were categorized as, current EHR users, “imminent adopters”
(those planning to adopt EHR within 1 year), “interested
adopters” (those planning to adopt EHR but not within 1
year), and those not considering EHR. Chi square analysis
and binary logistic regression models were used to identify
trends among imminent adopters and to compare barriers
among physicians in each of the adoption categories above.
Population Studied: Florida physicians practicing in the
ambulatroy setting.
Principal Findings: : Imminent adopters were significantly
less likely to be in solo practice (19.6 vs. 40.0%, P<.001) and
more likely to be in an urban area (P=.044) or in a multispecialty practice (P=.023). Imminent adopters were also
more likely to be practicing family medicine (.014), or
obstetrics/gynecology (P=.038). When compared to their
physician colleagues, imminent adopters perceived EHR
barriers very differently. For example, imminent adopters were
significantly less likely to consider upfront cost of
hardware/software [OR=0.35(0.30, 0.45)] or that an
inadequate return on investment [OR=0.25(0.19, 0.34)] was as
a major barrier to EHR. Moreover, imminent adopters
differed from their colleagues with respect to numerous other
productivity and technical barriers.
Conclusions: Policy and decision makers interested in
promoting the adoption of EHR among physicians should
focus on the needs and barriers of those most likely to adopt
EHR. Given that imminent adopters differ considerably from
their peers, current EHR incentive programs that focus on
financial barriers only may prove suboptimal in achieving
immediate widespread EHR adoption.
Primary Funding Source: CMS
●Validity of ICD10 administrative data in recording
comorbidity information
Hude Quan, M.D. Ph.D., Bing Li, MA, L Duncan Saunders,
Ph.D., William A Ghali, M.D. M.P.H.
Presented By: Hude Quan, M.D. Ph.D., Assistant Professor,
Community Health Sciences, University of Calgary, 3330
Hospital Dr. NW, Calgary, T2N 4N1; Tel: (403) 283 5307;
Email: hquan@ucalgary.ca
Research Objective: To evaluate the validity of the
International Classification of Disease, 10th Version (ICD-10)
administrative hospital discharge data and to determine
whether there were improvements of the validity compared
with ICD-9-CM data.
Study Design: We reviewed randomly selected charts at all
Alberta teaching hospitals to determine presence or absence
of recorded comorbidities and re-coded the same cases using
ICD-9-CM. We assessed the agreement between ICD-10
administrative data and chart review data for recording
comorbidities constitute the Charlson index and Elixhauser
comorbidity measure and then the agreement between recoded ICD-9-CM coded data and chart review data for
recording those comorbidities. Finally, we compared the
accuracy of ICD-10 data relative to chart data with the accuracy
of ICD-9-CM data relative to chart data for those
comorbidities.
Population Studied: Inpatients discharged during January 1
and June 30, 2003 from four teaching hospitals in two large
Canadian cities
Principal Findings: We reviewed 4008 inpatient records for
assessment of validity to 33 comorbidities. Compared to the
chart data, the ICD-9-CM data under reported 30
comorbidities and ICD-10 data under-reported for 31
comorbidities. Six comorbidities had higher prevalence in ICD10 than ICD-9-CM data. Sensitivity a measure of the accuracy
of recording presence of comorbidities in administrative data
when these were present in chart data ranged 9.3 - 95.7% for
ICD-9-CM and 12.7- 93.7% for ICD-10 data. Positive predictive
value that determines the extent to which a condition present
in the administrative data was also present in the charts
ranged 10.5-100% for ICD-9-CM and 11.0 – 100% for ICD-10
data. Specificity to determine the accuracy of reporting
absence of these comorbidities in the administrative data
when these diseases were absent in the charts and negative
predictive value to determine the extent to which a condition
absent in the administrative data was truly absent according
to the chart data were higher than 85% for both ICD-9-CM and
ICD-10 databases.
Conclusions: ICD-10 administrative data were coded
reasonably well on comorbidity variables although some
comorbidities defined based on ICD-10 administrative data
tended to be underestimated compared with those defined
using patient chart data. Validity of ICD-10 data is similar with
that of ICD-9-CM data in recording 33 comorbidities in our
sample.
Implications for Policy, Delivery, or Practice:
Implementation of ICD-10 may not significantly impact on risk
adjustment in quality of care assessment relative to ICD-9CM.
Primary Funding Source: Canadian Institutes of Health
Research
●Security Issues in Outsourcing
Ebrahim Randeree, M.B.A.
Presented By: Ebrahim Randeree, M.B.A., Ph.D. Candidate,
Management Science & Systems, University at Buffalo, 248
Jacobs Management Center, Buffalo, NY 14260; Tel: (716) 2077251; Fax: (716) 645-6117; Email: er4@buffalo.edu
Research Objective: The issue of trust and risk in hospital
relationships was extended beyond traditional focus as
outsourcing models were introduced. As outsourcing service
providers evolve, the evolution of IT networks and the
adoption of EMRs will increasing information assurance
threats. This paper develops a conceptual model of
outsourcing adoption in the presence of increased threats; it
investigates trust and risk variables that affect the adoption
and management of the relationships between hospitals and
vendors - specifically focussing on the management of the
outsourcing contract and the issue of security.
Study Design: Conceptual model with theory review and
proposed empirical study
Population Studied: Hospitals
Principal Findings: None - Theoretical exploration at this
time!
Conclusions: Pending empirical survey
Implications for Policy, Delivery, or Practice: The effect of
outsourcing relationships on the way we perceive security and
organizational boundaries is changing. The potential risks to
both the vendor and the client emerging from adoption can be
quite different. The role of IT security and information
assurance within hospitals may influence the direction of
contracting and vendor management. THis paper explores
information assurance concerns under HIPAA and combines
the analysis with outsourcing adoption.
Primary Funding Source: No Funding
●EMR options in Private & Small Group Practices
Ebrahim Randeree, M.B.A.
Presented By: Ebrahim Randeree, M.B.A., Ph.D. Candidate,
Management Science & Systems, University at Buffalo, 248
Jacobs Management Center, Buffalo, NY 14260; Tel: (716) 2077251; Fax: (716) 645-6117; Email: er4@buffalo.edu
Research Objective: The adoption of EMRs has been slow
with renewed impetus for small groups and solo physicians to
follow larger hospital systems. The options facing physicians
may be improving but many are still reluctant to sign-on. This
study explored physician concerns and investigates the
options available.
Study Design: Qualitative w/interviews
Population Studied: Private Physicians, Small Group
Practices
Principal Findings: Qualitative interviews provide depth that
is not evident in survey analysis. Physicians express cost
concerns as well as lack of IT skills within practices.
Conclusions: The challenges faced by this group may create
new concerns for IT solutions providers. Prelimenary results
provide advocates and technology vendors with the right mix
of incentives to increase adoption.
Implications for Policy, Delivery, or Practice: This paper
presents a research model and investigates the options
(partner with a hospital system, use an ASP model, do-ityourself) available to physicians engaged in EMR adoption.
Primary Funding Source: No Funding
●User Perceptions of Barcode Medication Administration
Systems
Julie Sakowski, Ph.D., Thomas Leonard, RN MPA, Jeffrey
Newman, M.D. M.P.H.
Presented By: Julie Sakowski, Ph.D., Sr. Health Services
Researcher/ Health Economist, Sutter Health Institute for
Research & Education, 345 California Street Suite 2000, San
Francisco, CA 94104; Tel: (415) 296-1808; Fax: (415) 296-1844;
Email: sakowsj@sutterhealth.org
Research Objective: Electronic barcode medication
administration systems (BCMA) have been developed to
reduce medication errors and increase patient safety. These
systems utilize barcodes placed on medications and patient
identification bands to match medications being administered
with orders entered in the pharmacy system and alert the
clinician if any discrepancies are detected. The ability of these
systems to prevent medication administration errors has been
documented. However, the impact of these systems on
overall patient safety, how the adoption of BCMA changes
nursing and other health care provider work flows, and the
impact on patient and provider perceptions of quality of care
remains unclear. This study fills that gap by evaluating
clinician perceptions of BCMA, how it affects the delivery of
health care, and its impact on patient safety.
Study Design: An anonymous, written survey was distributed
to nurses and respiratory care practitioners using BCMA for
inpatient medication administration. The survey employed a
combination of closed end questions where respondents
either indicated their agreement with a statement or rated the
amount of change resulting from the adoption of BCMA (i.e.
increased, decreased, or had no effect) and open ended
questions to provide more detail and context. The survey
collected information on respondent characteristics,
effectiveness of the BCMA training, BCMA ease of use, quality
of the warnings, medication administration process changes,
and impact on patient safety and satisfaction. Frequencies
and descriptive statistics were calculated for the survey results
and variation in responses due to user characteristics was
analyzed using logistic regressions. Focus groups were
conducted to gain a more detailed understanding of the
survey results and explore themes surfaced by the open ended
responses. A human subjects review exemption was granted
before the survey was distributed.
Population Studied: Clinicians using a barcode medication
administration system (eMAP) to deliver over 8,500,000
inpatient doses at 9 hospitals affiliated with Sutter Health, a
network of not-for-profit community hospitals located in
Northern California.
Principal Findings: Preliminary analysis of responses from a
sample of 57 completed surveys from 4 hospitals indicates
users believe the system prevents errors, is easy to use, and
increases patient safety. 88% of respondents indicated that
they believed the BCMA system increased patient safety. 85%
stated the system increased patient perceptions of safety and
61% reported it increased patient satisfaction. 77% rated the
system easy to use, but 46% indicated the system provided
too many warnings. 45% of the respondents believe that the
use of BCMA greatly increased the amount of time it takes to
administer medications and 55% have had to change the
amount of time dedicated to other patient care tasks. 60% of
the respondents indicated using BCMA increased their job
satisfaction.
Conclusions: Users believe that BCMA systems are easy to
use and increase patient safety.
Implications for Policy, Delivery, or Practice: BCMA
systems can be an effective tool for reducing medication
errors and increasing patient safety, but a concerted effort
needs to be made to ensure that the warnings the system
generates are appropriate, understandable, clinically relevant,
and actionable.
Primary Funding Source: No Funding
●Does Pay for Performance Affect the Adoption of Quality
Enhancing Practices by Child Health Providers (CHPs)?
Lisa Simpson, MB, BCh, M.P.H., FAAP
Presented By: Lisa Simpson, MB, BCh, M.P.H., FAAP; Email:
lsimpso1@hsc.usf.edu
Research Objective: Pay for performance programs (PFP) link
physician compensation to quality and use of information
technology applications. These programs are increasingly
being promoted as an effective strategy to improve healthcare
quality by child health providers (CHPs). Nationally it is
unknown the extent to which these programs affect
physicians’ behavior in relation to quality. The purpose of this
study was to assess the extent to which CHPs behavior is
linked to PFP and whether this is associated with increased
adoption and use of health information technology
applications including electronic health records, email and
personal digital assistants.
Study Design: The current study is limited to Child Health
Providers (CHPs) who responded to a larger survey of all
ambulatory physicians in the state of Florida. The
independent variables include physician and practice
characteristics (i.e. age, race/ethnicity, specialty, practice
size/type and Medicaid volume) and a number of
compensation variables (i.e. patient surveys, measures of
clinical care, use of clinical information technology, and quality
bonus). Analyses included descriptive statistics, univariate
analyses and logistic regression to compute adjusted odds
ratios for the adoption of health information technology
applications.
Population Studied: Pediatricians, family practitioners and
pediatric sub-specialists received an instrument that included
additional questions on quality of care. Specifically, this study
analyzed results from all pediatricians, family practitioners
serving greater than 20% children, and pediatric subspecialists (n=1,014).
Principal Findings: About a third or less of CHPs report that
the following are a major or minor factor in their
compensation: measures of clinical care (37.6%), patient
surveys (31.4%), use of information technology (26.9%) and
quality bonus/incentive payments (25.1%). A majority of
CHPs report that the following are NOT compensation
factors: email with patients (89.6%), phone consultation
(86.6%) and group patient visits (86.9%). Results from the
logistic regression found that those in the minor category
(quality bonus) were 2.71 times more likely to have EHR
(p=.023) than those in the “not a factor” category. Those in
the major category for (quality bonus) were 3.27 times more
likely to have EHR (p=.018) than those in the “not a factor”
category. The logistic regression also found that those in the
minor category (use of IT for compensation) were 8.35 times
more likely to have EHR (p=.001) than those in the “not a
factor” category.
Conclusions: Pay for performance programs may already be
affecting 25-30% of child health providers. The extent to which
these are affecting technology adoption will be further
examined to determine whether results differ for high volume
Medicaid providers.
Implications for Policy, Delivery, or Practice: This
information may be the first of its kind in the pediatric arena
to demonstrate that PFP efforts are promoting the adoption
EHRs. A better understanding of the characteristics of these
PFP programs is needed to understand their impact on
patient care, quality and outcomes.
Primary Funding Source: No Funding
●Electronic Office Based Applications Supporting Quality
of Care
Lisa Simpson, MB, BCh, M.P.H., FAAP
Presented By: Lisa Simpson, MB, BCh, M.P.H., FAAP; Email:
lsimpso1@hsc.usf.edu
Research Objective: The literature provides numerous
studies that have identified that office based capabilities may
lead to improved quality. However, the extent to which these
applications exist in a sample of community based physicians
serving children remains unclear. The purpose of this study is
to assess the extent to which physicians serving children have
electronic and other capabilities known or believed to improve
quality of care.
Study Design: The current study is limited to Child Health
Providers (CHPs) who responded to a larger survey of all
ambulatory physicians in Florida. The independent variables
include physician and practice characteristics (i.e. age,
race/ethnicity, specialty, practice size/type and Medicaid
volume). Quality related variables include physician ability to
perform certain quality functions (e.g. sending reminder
notices), experience with process failures (e.g. missing patient
information), and beliefs about the effectiveness of various
strategies to improve quality (e.g. involvement in
collaboratives). Initial analyses included descriptive statistics
and univariate analyses. An index was constructed to
characterize a quality enabled practice which then served as
the dependent variable in a multivariate analysis of
independent factors associated with higher scores on this
quality enabled practice index. The index is an un-weighted
sum of single points credited for each of several office
functions judged to be associated with higher quality such as
having an EHR, clinical decision support, weight based dosing
or growth charting etc.
Population Studied: Pediatricians, family practitioners and
pediatric sub-specialists received an instrument that included
additional questions on quality of care. Specifically, this study
analyzed results from all pediatricians, family practitioners
serving greater than 20% children, and pediatric subspecialists (n=1,014).
Principal Findings: Less than half of CHPs report being able
to perform certain quality related functions (e.g. 44.5% send
reminder notices for preventive care, 26.5% receive prompts
for special follow up care). CHPs have the ability to create
patient lists by diagnosis somewhat or very easily (44.1%)
more often than patient lists by medications (15.5%) or
laboratory results (17.1%). CHPs report rarely or never
observing the following process failures: repeated tests
because findings were unavailable (62.2%); or medication
errors (82.7%). The logistic regression findings suggest that
African American physicians were twice as likely to have
practices that ranked in the top 50% of quality enabled
practices (p=.017) than White, Hispanic, or Asian child health
providers. Additionally, CHPs who are less than 40 or more
than 60 years of age are credited with higher scores.
Conclusions: Office based capabilities felt to be associated
with higher quality have not been widely adopted by child
health providers. This suggests that improvements in the
quality and safety of care for children and adolescents may
continue to lag behind adult populations unless specific
attention is paid to the needs of child health providers.
Implications for Policy, Delivery, or Practice:
Primary Funding Source: No Funding
●The Effect of Information Technology on Quality of Care
in the Veterans Health Administration
Joanne Spetz, Ph.D., Ciaran Phibbs, Ph.D.
Presented By: Joanne Spetz, Ph.D., Associate Professor,
Community Health Systems, University of California, San
Francisco, 3333 California Street, Suite 410, San Francisco, CA
94118; Tel: 415-502-4443; Fax: 415-476-4113; Email:
jojo@alum.mit.edu
Research Objective: Computerized patient records and bar
code medication systems are gaining favor in the health care
industry. These systems are believed to reduce patient care
errors and improve the work environment for medical
professionals, although there is little objective research on the
effects of these systems on patient care and staff morale. In
the late 1990s, the Veterans Health Administration (VHA)
implemented two major information systems to enhance
record-keeping and quality of care. The Computerized Patient
Record System (CPRS), phased in over the past decade,
consists of a comprehensive electronic patient medical record,
including outpatient and inpatient services. The Bar Code
Medication Administration (BCMA) system, which was in all
VA medical centers by 1999, created a computerized
pharmacy ordering, distribution, and administration system
for use in the inpatient setting. This paper examines the
effects of CPRS and BCMA on hours worked by nursing staff
and adverse events experienced by patients.
Study Design: Several VA data systems provide data about
nurse staffing and patient outcomes. Nurse staffing is
measured as hours worked and overtime hours. Patient
outcomes are measured using the AHRQ Patient Safety
Indicators and Inpatient Quality Indicators. Other patient
outcomes measures, such as those used by Needleman and
Buerhaus, also are used. All VA facilities were surveyed to
obtain exact implementation dates of modules of CPRS and
BCMA. The effects of CPRS and BCMA on staffing and
outcomes are identified by estimating multivariate regression
equations with panel data from the late 1990s through early
2000s. For each equation, the dependent variable is the
outcome of interest, with the explanatory variables including
whether CPRS or BCMA was implemented, patient
characteristics, facility characteristics, and other factors.
Population Studied: All facilities in the Veterans Health
Administration.
Principal Findings: Adoption dates of the information
technology systems varied widely across VA facilities.
Preliminary results from the quality analysis are expected in
February, 2005.
Conclusions: There is substantial need for ongoing
evaluation of IT systems in healthcare.
Implications for Policy, Delivery, or Practice: The lessons
learned from this study will be of great importance to the
future adoption of health IT systems.
Primary Funding Source: RWJF
●Putting Medicaid Providers on the Map: An Evaluation of
Address Record Quality in a State-Level Medicaid Provider
Database
John Stewart, MS, M.P.H., Ana Lopez De Fede, Ph.D., Alina S.
Wyatt, BS
Presented By: John Stewart, MS, M.P.H., GIS Manager,
Institute for Families in Society, University of South Carolina,
1600 Hampton St, Columbia, SC 29208; Tel: (803) 777-5516;
Fax: (803) 777-1120; Email: jstewart@gwm.sc.edu
Research Objective: Increasingly, patient and medical
provider address records are geocoded (geographically
located) to estimate small-area disease incidence rates,
identify disease clusters, delineate health care provider
shortage areas, and calculate travel distance to medical care.
Although a number of health researchers have examined
positional accuracy issues associated with automated
geocoding software, inadequate attention has been paid to the
quality of address records in large administrative data sets.
This study evaluates address record quality in a state-level
Medicaid provider database, identifies common address
record errors, and provides solutions for handling multiple
address record deficiencies.
Study Design: Address records for physicians providing
primary or specialty care to South Carolina Medicaid
recipients in 2003 were obtained in digital format from the
South Carolina Medicaid Management Information System
Address record quality was evaluated both manually and with
an automated address standardization/error correction
software package (ZIP4). Address record errors, including
missing data, invalid ZIP Code information, misspellings, and
nonstandard abbreviations, were tabulated by error type.
Identified address record deficiencies then were corrected
using ZIP4 and a variety of Web-based business and
professional directories.
Population Studied: Stratified sample of physicians providing
primary or specialty care to South Carolina Medicaid
recipients in 2003 (n = 16,333).
Principal Findings: Notably, 12.7% of all physician address
records lacked complete street address information. The
majority of these records provided only post office box
numbers. Approximately 5% of all address records contained
obsolete or otherwise invalid ZIP Code information and
roughly 3% contained verifiable street misspellings. More
than one in ten address records used nonstandard city name
abbreviations (e.g., “CHAS” for “Charleston”) and
approximately 2% lacked proper directional prefixes/suffixes.
Finally, more than 17% of address records employed
nonstandard unit (e.g., building, suite) designations.
Conclusions: Of the physician address records examined, a
substantial proportion provided only post office box
information, which does not permit geocoding at the street
address level. Health information system initiatives to
improve provider address record quality should promote the
use of standardized street addresses including valid street
numbers, appropriate directional prefixes/suffixes, and unit
information. In most instances, address record errors
encountered by secondary users of administrative data can be
corrected using address standardization software and such
Web-based directories as Google, SuperPages, Yahoo Yellow
Pages, USPS ZIP Code Lookup, and AMA DoctorFinder.
Implications for Policy, Delivery, or Practice: Enhanced
address record quality can improve health care provider
geocoding results, thereby strengthening state and local
health professional shortage area assessment, health care
resource allocation, and health policy formation.
Primary Funding Source: Other Government
●Impact of Electronic Prescribing on use of Generic and
Preferred Medications
Christine Vogeli, Ph.D., Michael A. Fischer, M.D. MS, Margret
Stedman, M.P.H., Rainu Kaushal, M.D. M.P.H., Timothy G.
Ferris, M.D. M.P.H., Joel Weissman, Ph.D.
Presented By: Christine Vogeli, Ph.D., Instructor of Medicine,
Institute for Health Policy, Massachusetts General Hospital,
50 Staniford Street, 9th Floor, Boston, MA 02114; Tel: 617 7240984; Fax: 617 724-4738; Email: cvogeli@partners.org
Research Objective: Controlling spending on prescription
drugs remains a critical issue for patients, physicians,
insurers, and policymakers. Generic medications represent
one important source of potential savings on prescription
drugs. Computerized prompts embedded in electronic
prescribing (eRx) systems have the potential to increase
generic prescribing. We studied the extent to which an eRx
system is related to generic medication use.
Study Design: In October 2003, two major health insurers,
their PBMs, and a large e-prescribing company collaboratively
launched a voluntary e-prescribing program in Massachusetts
in which prescribers were provided with eRx software and free
handheld PDAs. The e-prescribing system allows
prescriptions to be written either with a handheld PDA device
or on a personal computer linked to the internet.
Prescriptions are immediately transmitted to pharmacies
electronically or by fax. We studied the impact of an officebased eRx system on the use of generic medications using a
pre-post design. We evaluated all prescriptions filled by one
of the major health insurance plan during a one-year baseline
period (April 2003-March 2004) and one year after the
initiation of the eRx system within the plan (April 2004-March
2005). The insurance plan grouped medications into three copayment tiers, with generic medications having the lowest copayments, followed by preferred brand-name and nonpreferred brand-name medications. The eRx system uses
color-coded text to identify medication co-payment tiers, with
preferred generic medications appearing in green. We used
claims for medical services to identify patients under the care
of physicians who began using the eRx system during the
study period and defined a cohort of patients who had seen
physicians who were writing electronic prescriptions. We
calculated by month the average proportion of prescriptions in
each co-payment tier for patients before and after they had
seen an electronic prescribing physician.
Population Studied: Patients cared for by physicians
practicing in a large sample of community practices in
Massachusetts in 2004-2005.
Principal Findings: We identified 243,000 patients who had
seen a physician using the eRx system, accounting for over 4.1
million prescriptions. During the baseline period, generic
medications accounted for an average of 54.4% of filled
prescriptions. Over the following year, the proportion of
generic medications was 57.0%, an increase of 2.6% (p<0.01).
The increase in generic medications corresponded to a
decrease in the use of preferred branded medications (second
tier) from 33.3% to 32.1% (p=0.04); and a decrease in the use
of non-preferred medications (third tier) from 12.3% to 10.9%
(p<0.01).
Conclusions: Use of generic medications increased slightly
after initiation of an eRx system in a sample of communitybased practices, with corresponding decreases in the use of
branded medications requiring higher co-payments.
Implications for Policy, Delivery, or Practice: For many
patients facing sharply tiered co-payment systems, increased
use of generic medications offers the potential for
considerably reduced out-of-pocket expense. ERx systems are
one important tool to promote more widespread use of
generic medications in the outpatient setting, even in states
that already require generic substitution.
Primary Funding Source: AHRQ