Lecture 2
History and Current use of Clinical Information Systems
CH 4 History and Evolution of
Health Care Information Systems

Definitions
◦ An Information System is an arrangement of
information (data), processes, people, and
information technology that interact to collect,
process, store, and provide as output the
information needed to support the organization
◦ Information Technology describes the
combination of computer technology (hardware
and software) with data and
telecommunications technology (data, image,
and voice networks).
Types of Health Care Information
Systems

Administrative Information System
◦ Primarily administrative or financial information
◦ Used to support management functions and general
operations
 Human Resource Management, Materials Management,
Patient Accounting or Billing, Staff Scheduling

Clinical Information System
◦ Contains clinical or health-related information used
by providers in diagnosing, treating, and monitoring
 Department: radiology, pharmacy, laboratory systems
 Clinical decision support: medication admin, CPOE,
EMR
History and Evolution
History and Evolution

Policy and market innovations and correlations
with IT
◦ Demand for IT driven largely by the market (follow the
money). The dollar seems to be a better motivator than
“doing the right thing”

1991 IOM report – The Computer-Based Patient
Record: an Essential Technology for Health Care
◦ Called on the adoption of computer-based records by the
year 2001
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HIPAA in 1996
IOM: To Err is Human (2000)
IOM Patient Safety: Achieving a New Standard
for Care (2004)
Ch 5: Current and Emerging Use of
Clinical Information Systems

The systems
◦ The electronic medical record
 CPR(computer-based patient record)EMR
 An electronic record of health-related information
on an individual that can be created, gathered,
managed, and consulted by authorized clinicians
and staff in one health care organization.
EMR
 Core Functions
◦ Health information and data (diagnoses,
medications, allergies, demographics,
narratives)
◦ Results management (test and procedure
results)
◦ Order entry and support
◦ Decision support (computerized decision support
capabilities such as reminders, alerts and
diagnosing)
HIMSS EMR Adoption Model
Stage
Cumulative Capabilities
Stage 0
• Some clinical automation may exist
Stage 1
• All three major ancillaries installed – laboratory,
pharmacy, and radiology
Stage 2
• Major ancillary clinical systems feed data to a
clinical data repository (CDR) that provides
physician access for retrieving and reviewing
results.
• CDR contains a controlled medical vocabulary
(CMV) and the clinical decision support system
and rules engine for rudimentary conflict checking
• The hospital may be health information exchange
(HIE) capable at this stage and can share
whatever information it has in the CDR with other
patient care stakeholders.
HIMMS EMR Adoption Model
Stage
Cumulative Capabilities
Stage 3
• Clinical documentation installed (eg. Vital signs,
flow sheets, nursing notes, care plan charting,
eMAR)
• First level of clinician decision support is
implemented to conduct error checking with order
entry (i.e., drug/drug, drug/food, drug/lab)
• Some level of medical image access from picture
archive and communication systems (PACS) is
available for access by physicians via the intranet
or other secure networks.
Stage 4
• CPOE for use by any clinician added to nursing
and CDR environment
• Second level of decision support related to
evidence-based medicine protocols implemented.
HIMMS EMR Adoption Model
Stage
Cumulative Capabilities
Stage 5
•
•
Stage 6
•
•
The closed loop medication administration environment
is fully implemented in at least one patient care service
area. The eMAR and bar coding or RFID are
implemented and integrated with CPOE and pharmacy to
maximize point-of-care patient safety processes for
medication administration
The “five rights” of medication administration are verified
at the bedside with scanning of the bar code on the unit
does medication and the patient ID
Full physician documentation/charting (structured
templates) are implemented for at least one patient care
service area for progress notes, consult notes, discharge
summaries or problem list and diagnosis list
maintenance.
A full complement of radiology PACS is implemented and
provides medical images to physicians via an intranet
and displaces all film-based images
HIMMS EMR Adoption Model
Stage
Cumulative Capabilities
Stage 7
• The hospital no longer uses paper charts to deliver
and manage patient care and has a mix of discrete
data, document images, and medical images
within its EMR environment
• Data warehousing is being used to analyze
patterns of clinical data to improve quality of care
and patient safety and care delivery efficiency
• Clinical information can be readily shared via
standardized electronic transactions with all
entities that are authorized to treat the patient or
a HIE.
• The hospital demonstrates summary data
continuity for all hospital services (e.g. inpatient,
outpatient, ED, and with any owned or managed
ambulatory clinics)
Stage 7 Hospitals in Texas
Baylor Scott & White (3 Hospitals)
 Children’s Medical Center (2 Hospitals)
 Texas Health Resources (11 Hospitals)

◦ https://www.himssanalytics.org/emram/stage7
caseStudies.aspx
EHRs and Docs

AMA: “The EHR has been reduced to a
tool for billing, compliance and litigation
that has sustained negative impacts on
doctors’ productivity”
◦ Documenting a full clinical encounter is pure
torment
◦ The government mandates that doctors use an
EHR, the EHR vendors’ templates can create
confusion and the appearance of fraud, which
opens the door for payers to decline
reimbursement.
EHRs and Docs
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Recent evidence that EHRs perpetuate fraud
Easier to “upcode”
EHRs produce more complete and accurate
documentation, and this could be leading
medical providers to seek reimbursement for
services they have always been providing but
weren’t properly documenting before.
CMS has history of billing and so can look for
trends in billing.
Physician Adoption

Barriers to Adoption
◦ Cost
◦ Lack of knowledge
◦ Workflow challenges
◦ Lack of interoperability
Reasons for increases
Demographics
1.
◦
2.
As older physicians retire and a new cohort
enters, resistance lessens.
Fear factor is dissipating – even among
older physicians.
Reasons for increases
Government incentives
1.
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◦
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2006 HHS granted Stark law exceptions and
anti-kickback safe harbors to hospitals so
they could help affiliated practices finance
EMRs and other technology.
About 1/3 of hospitals have offered financial
assistance for EMRs and more than 60%
offer physicians access to the hospital’s EMR
HITECH
Value of EMR

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Improved Quality, Outcomes, and Safety
Improved Efficiency, Productivity?
Time Savings?
Cost Reduction?
Improved Service and Satisfaction?
Computerized Provider Order
Entry (CPOE)

Identified by the Leapfrog Group as one of
the Four Leaps in Hospital Quality, Safety
and Affordability (CPOE, Evidence-Based Referral,
ICU “intensivist” staffing, Safe Practice Score).

A CPOE accepts physician orders
electronically, replacing handwritten or
verbal orders
Computerized Provider Order
Entry (CPOE)

Also provides decision support at the point
of ordering (duplicate test, drug-drug
interactions, allergies, etc). Might also
show the physician the cost of the drug

Also called CPOM (management) to
highlight that it is not just “entering
orders” but more about managing orders.
CPOE Adoption
CPOE seen as a major obstacle to getting
to Meaningful Use.
 For Stage 1:

◦ More than 30% of unique patients with at least one
medication in their medication list have at least one
medication entered using CPOE

For Stage 2:
◦ More than 60% of medication, 30% of laboratory, and
30% of radiology orders created by the EP during the
EHR reporting period are recorded using CPOE
CPOE Adoption

Involves major change in workflow
◦ Most hospitals have named a Chief Medical
Information Officer – physician champion.

Cerner, Eclipsys and Epic are the biggest
vendors in CPOE, with Cerner having the
most live hospitals. (McKesson and
MEDITECH also in game)
CPOE Resistance
CPOE and Workflow
Electronic Medication
Administration System eMAR

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About half of medication errors occur during
the ordering process (CPOE), but errors also
occur in dispensing, administering, and
monitoring medications.
Bar-code-enabled point of care (BPOC)
◦ The five rights:
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The right drug
to the right patient
through the right route
at the right dose
at the right time.
eMAR
◦
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◦
Patient wristband with barcode
Provider identification band with barcode
Bar-codes on the medication
Linked to orders
Telemedicine

The use of medical information exchanged
from one site to another via electronic
communications to improve patients’
health.
◦ Specialist referral services
◦ Remote patient monitoring
◦ Two delivery methods
 Store and forward – digital images from one
location to another. Teleradiology,
teledermatology and telepsych
https://www.youtube.com/watch?v=UyoooVg0CJQ
Telemedicine
 Interactive videoconferencing – face to face
consultation. Urban to rural.
◦ Peripheral devices such as stethoscope
◦ eICU
 http://searchhealthit.techtarget.com/definition/Electronic
-Intensive-Care-Unit-eICU
◦ Telesurgery
Telehealth

Telehealth includes the use of technology
to access remote health information,
diagnostic images, and education
◦
◦
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Email communication
Refilling prescriptions
Registering patient
Scheduling appointments
Personal Health Record

An electronic record of health-related
information on an individual that conforms
to nationally recognized interoperability
standards that can be drawn from
multiple sources while being managed,
shared, and controlled by the individual
◦ Consumer-empowerment
◦ Comprehensive
◦ Longitudinal
◦ Individual controls
Putting IT Together
Creating Value in Health
Care Through Big Data
Roski, et al.
The Promise of Big Data
2012: 500 Petabytes of health care Data
 2020: 25,000 Petabytes – 500 billion file
cabinets
 Potential for

◦ Greater customer knowledge
◦ Customized outreach
◦ Increased productivity, sales, economic
performance
What is Big Data?

Volume
◦ Massive amounts of storage, flexible, easily
accessible

Variety
◦ Structured and unstructured
 EHRs, Images, social media, mobile aps

Velocity
◦ Real time analysis
What is Big Data?
Potential For Big Data in
Healthcare

Delivery of Personalized Medicine
◦ Individualized diagnoses and treatments
Clinical Decision Support
 Reliance on Patient-Generated Data

◦ Mobile devices– target specific patients
Population Health Analyses
 Fraud Detection and Prevention

IT Infrastructure Required

Data Warehouse vs Data Lake
◦ Extract, transform, and load
Provenance

The history of the data’s origin,
ownership, use, and modification
◦ State requirements for how long data must be
stored
◦ The ability to use original data for analysis
 Ex, new payment models
Protecting Data Security and
Privacy

Cloud Service Provider (CSP)
◦ Flexibility and Elasticity
◦ Economies of scale and scope wrt security
Policy Concerns
Data sharing and collaboration
 Privacy

◦ Individual confidentiality vs community benefit