Transcript Presentation Slides

Health Informatics has had a
favorable impact on patient care.
Agree or Disagree?
BCS Health Informatics Forum
October 4, 2005
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Denis Protti - University of Victoria
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Before we begin the debate, we need
to set the rules
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Some of the arguments
• In Favor
–
–
–
–
–
The Danish healthcare system can’t be all wrong
Chronic Disease Management evidence
CPOE - proven benefits if done properly
VistA – documented clinical outcome improvements
Data mining – impossible to do without computers
• Against
–
–
–
–
–
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Value for Money - Bend in England
Decision Support in GP Systems - NPSA in England
Ethical Use of Resources - Atherley in Canada
CPOE at Mount Sinai - Los Angeles
CPOE failures - JAMA paper
Denis Protti - University of Victoria
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Arguments in Favor
The Danish Health Care System
Can’t Be All Wrong
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National Health Network
• Used by 85% of the healthcare sector
– >2,500 different organisations
• All hospitals, all pharmacies, all laboratories and ~all
general practices take part
• All municipalities responsible for social care use it
• All health professionals by 2006
– Financial incentives for the last 25% of specialists
• Two million messages a month are exchanged (over
75% of the total communication in the primary sector)
• Central database of all prescriptions
– accessible to 331 pharmacies and GPs with a digital signature
• Central database of all lab results
– Accessible to all physicians and to patients themselves
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m o n th
MedCom -The Danish Health Data Network
Messages/Month
1200000 GP´s with EDI :
2116 = 96 %
e a c h
Specialists with EDI:
1000000
569 = 72 %
Hospitals with EDI :
63 = 100%
Pharmacies with EDI:
331 = 100 %
Doctors on Call:
D o c u m e n ts
Prescriptions
1039105 = 85%
1234883
73%
Disch. Letters
682923 = 88
938291
85 %
15 = 100 %
800000 Health Insurance:
17 = 100 %
75 messages /min
Lab. reports
543040 = 97
703538
82 %
600000
400000
Referrals
86539 = 52 %
200000
Reimbursement
17660= 78 %
0
92
93
94
95
96
97
98
99
20
O1
O2
O3
O4
O5
Lab Requests
19256 = 11 %
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From handwritten prescriptions to..
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EDIFACT-prescriptions
UNA:+.? '
UNB+UNOC:3+5790000120314:14+5790000172825:14+010430:1
456+26++++1'
UNH+15+MEDPRE:0:962:RT:SST012+Æskulap'
BGM+PRS:SKL:SST++9'
DTM+137:20010430145604:204'
PNA+PO++291714:YNR:SFU+++US:Max Berggren+US:MedCom'
ADR++1:Rugårdsvej 15++5000'
COM+66133066:TE'
EMP+4+PHY:SKL:SST'
PNA+SE++5790000172825::9'
DTM+97:20010430:102'
RFF+CH:200118'
ICD+DK:SKL:SST+NA:SKL:SST'
GIS+ZZZ:SKL:SST'
PNA+PAT+2512484916:CPR++++SCC:BERGGREN, NANCY
ANN'
ADR+1+1:PARK ALLE 48+Hillerød+3400++020:SKL:SST'
LIN+1++385229:AK:NVN:LMS'
IMD+A+DDP+:::creme'
IMD+A+DNM+:::Diproderm'
MEA+AAU+CT:::Tube a 60 g'
MEA+DEN+S:::0,05%'
PGI+10+NS:SKL:SST'
QTY+189:1:NMB'
PNA+GZ+++++AB:OR'
CIN+9+222:LDD:LMS:mod eksem'
EQN+2:ITE’
DTM+264:30:804'
DSG+5+104:LDD:LMS:udvortes 2 gange daglig'
TOD+2++OAD:SKL:SST'ADR+5+US:Vestergade 17++3400'
PNA+AB+++++US:Knud Mosebryggersen'
UNT+30+15'
UNZ+1+26'
BIOCHEMISTRY,
HEMATOLOGY,
IMMUNOLOGY
MICROBIOLOGY
HISTOPATH
CYTOLOGY
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VPN- Internet based
MedCom
Health Data Network by 2005
Center for
Sundheds-telematik
-
• Structured clinical messages
• Clinical e-mail
UNA:+.? '
UNB+UNOC:3+5790000120284:14+579
UNH+80901082504854+MEDRPT:D:93A
BGM+LRP++9+NA'
DTM+137:200001141247:203'
S01+01'
NAD+SLA+4201050:SKS:SST++Sygehu
SEQ++1'
SPR+ORG+60:SKS:SST+RPT01:SKS:SS
S01+01'
• Booking at GP´s / Specialists
• Look up – across regions:
– Lab results, Lab requisitions, X-ray reports
• Health Portal
• Patient monitoring, clinical databases
r
• Telemedicine
1
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1†
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Arguments in Favor
Chronic Disease Management
Evidence of Benefits
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One of many Chronic
Disease Management
success stories
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PUBLIC KEY INFRASTRUCTURE
Pharmacy
Online
Provider
Directory
Discharge
Summaries
Patient Status
Reports
GP Practice
GP Practice
ISP
ISP
Government
or Private
Health Insurer
EDI Message
Exchange
VPN
GP Practice
Child Immunisation
Diabetes
Infectious Disease
Disease
Management
Systems
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Pathology
Lab Test
Reports
Orders
Online Services
and Databases
ISP
GP Practice
AGPAL ACCREDITED
Radiology
Service
Test Reports
Orders
Denis Protti - University of Victoria
Public Health
Monitoring and
Surveillance
Systems
15
New Zealand Facts
• Used by 80% of all healthcare sector
organizations in New Zealand
– All hospitals, radiology clinics, private laboratories
– ~1,800 general practices.
– > 600 specialists, physiotherapists, other allied
health workers
• Over 3 million messages a month exchanged
– 95% of the communication in the primary health
care sector.
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New Zealand Facts
• Over 95% of GP offices are using one of
nine Practice Management Systems
– 75% use their systems to electronically send
and receive clinical messages such as
laboratory results, radiology results,
discharge letters, referrals, etc.
• ~ 50% of GPs now use the Internet on a
regular basis from their offices - including
communicating with their patients.
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HealthLink increasingly used to assist with
Chronic Disease Management
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HealthLink and the management of
chronic diseases
• Common software is used to enroll and track
patients on chronic disease management (CDM)
programs.
• The software contains best-practice guidelines for
care, and collects the latest clinical data about
each patient from laboratory and GP physician
office systems.
• Based on the latest available data, the software
automatically issues alerts, reminders and
recommendations to the relevant health care
providers as appropriate for and specific to each
patient.
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• As a result of these CDM applications of
information technology in primary care:
– Child immunization rates went from 75% to 95%.
– Control of diabetes improved – for patients with
HbA1c higher than 9 pre-enrolment was 34% and
this was reduced to 7% post-enrolment
– There was an 80% reduction in wait time for statins
for diabetes patients.
– Acute admissions were running at 9% per annum
growth rate prior to HealthLink
• By 2002, the growth rate was reduced to near 0%.
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Another success story
BC’s CDM Toolkit
• A secure website for licensed BC physicians,
and their delegates, to support General
Practitioners and collaboratives
– Anything more complex would face significant barriers
in a province where over 90% of doctors still keep paper
records
• Features
– Collaborative and comparative reports – performance
indicators and quality improvement measures
– Direct data imports from office based EMR software (no
more duplicate data entry)
– Linkage to the CDM Secure Website for secure file
transfer, and to other PHC/Health Registry services
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CDM Toolkit: Contextual Overview
Input data
Program
Administrator
Internet
(https,
TCP/IP)
Summary
stats
Firewall
Input
data
Input
data
Recall notices,
Provider stats,
Summary stats
Web
browser
Recall Notices,
Provider Stats,
Summary Stats
(manual)
Web
Server
Recall Notices,
Provider Stats,
Summary Stats
Input Data
Input data
PHC
Provider
Register
Updates
Toolkit
Data
Base
MSP CDM
Registers
Registers
HNFTP
(file
transfer)
File extract
(from clinic EMR)
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BC’s CDM Toolkit (cont’d)
• Provides clinical data analysis otherwise not available to
most family physicians, encouraging continuing
improvements in care.
• Within seven months of its introduction, about 13% of BC’s
family doctors (more than 450) were voluntarily using the
system, along with about 250 nurses, specialists and
supporting staff.
• The number of users exceeded 2,000 in March 2005.
• Results
– The proportion of patients on appropriate beta blockers
rose from 16% to 89%;
– The proportion of patients with documented selfmanagement goals rose from 5% to 57%.
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Pop 1:
G Wray
BC Avg:
42.3%
Goal:
90% of Diabetes Pts with at least 2
A1C tests within the past year
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Pop 2:
VIHA Wave 1
Goal:
85% of Diabetes Pts with A1C
values <7%
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VIHA Outcomes
• Diabetes - % with > 1 HbA1c in 1 yr
– BC (’02-03)
= 39 %
– VIHA (March/05) = 79 %
• CHF - Patients on recommended drugs (ACE-I):
– BC (’02-03)
= 50 %
– VIHA (March/05) = 85 %
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Arguments in Favor
Computerised Physician Order Entry
(CPOE) – Has Proven Value
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Effect of Physician Order Entry
(CPOE)
• 3 recent white papers on use of CPOE
• Medication errors are the low hanging
fruit of patient safety
• CPOE shown to reduce serious, nonintercepted drug errors by 55%
• In US, States are demanding it!
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The evidence that IT can enhance
patient safety is mounting
• Boston’s Brigham and Women’s Hospital,
demonstrated that CPOE reduced error rates by 55%
-- from 10.7 to 4.9 per 1000 patient days.
– Rates of serious medication errors fell by 88% in
a subsequent study by the same group.
– The prevention of errors was attributed to the
CPOE system’s structured orders and medication
checks.
• LDS Hospital in Salt Lake City demonstrated a 70%
reduction in ADEs after implementation of a CPOE
system.
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Rapid Identification and Tracking of
Adverse Events
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Arguments in Favor
The EHR system (VistA) at the Veteran’s
Administration is the gold standard when it
comes to measuring clinical outcomes
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Comparison of Quality of Care for VA Patients
• VA patients scored significantly higher for:
– Adjusted overall quality (67% vs 51%)
– Chronic disease care (72% vs 59%)
– Preventive care (64% vs 44%)
• The VA advantage was most prominent in areas where the VA has
established performance measures and active performance monitoring
• Other studies suggest contributions from:
– EHR, clinician reminders, structured templates, standing orders,
improved inter-provider communication, facility performance
profiling, accountability for performance and more integrated
delivery systems
Steven Asch, Elizabeth McGlynn et al
Comparison of Quality of Care for Patients in the Veterans’ Health Administration and
Patients in a National Sample
Annals of Internal Medicine 2004; 141:939-945
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The VA Computerized Patient Record
System
• Integrated computer-based medical record developed by
Department of Veterans Affairs
• Includes clinician order entry, note entry, results review,
imaging, decision support, remote data
• Integrated with pharmacy, laboratory, dietetics, vital
signs, nursing and bar code medication administration
programs
• Includes user authentication with signature codes,
business rules for user classes to ensure security and
appropriate use
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VHA CPRS
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• The VA's Quality Enhancement Research
Initiative (QUERI) is a large-scale,
multidisciplinary quality improvement
initiative designed to ensure excellence in
all areas where VA provides health care
services, including inpatient, outpatient,
and long-term care settings.
• The role of information systems is critical
to this quality improvement process.
Hynes DM et al
Informatics Resources to Support Health Care Quality
Improvement in the Veterans Health Administration
J Am Med Inform Assoc. 2004;11:344-350
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QUERI in action
• QUERI's development of information technology
tools is an important component of (and
contributor to) VA's overall informatics strategy.
• The resulting databases and data elements and
information technology tools provide valuable
information for patient care, quality improvement,
research, and management decisions, including
high-level policy formulation and resource
allocation.
• An example from the Ischemic Heart Disease
(IHD) QUERI's experience illustrates this point.
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QUERI in action
• When the IHD QUERI team proposed to develop
a national clinical reminder for lipid level
management, it quickly became clear that the
then-existing formal protocols and procedures
for clinical reminder development were
incomplete.
• An organizational realignment resulted in formal
links and collaborations leading to formalized,
well-documented processes for developing,
testing, and implementing national clinical
reminders in the clinical information system.
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VHA – Benchmark for Quality
Clinical Indicator
VA 2002
VA 2003
Medicare 03
Best Not VA or Medicare
Advised Tobacco Cessation (VA x3, others x1)
69
75
62
68 (NCQA 2002)
Beta Blocker after MI
97
98
93
94 (NCQA 2002)
Breast Cancer Screening
80
84
75
75 (NCQA 2002)
Cervical Cancer Screening
89
90
62
81 (NCQA 2002)
Cholesterol Screening (all pts)
91
91
NA
73 (BRFSS 2001)
Cholesterol Screening (post MI)
92
94
78
79 (NCQA 2002)
LDL Cholesterol <130 post MI
74
78
62
61 (NCQA 2002)
Colorectal Cancer Screening
64
67
NA
49 (BRFSS 2002)
Diabetes Hgb A1c checked past year
94
94
85
83 (NCQA 2002)
Diabetes Hgb A1c > 9.5 (lower is better)
17
15
NA
34 (NCQA 2002)
Diabetes LDL Measured
94
95
88
85 (NCQA 2002)
Diabetes LDL < 130
70
77
63
55 (NCQA 2002)
Diabetes Eye Exam
72
75
68
52 (NCQA 2002)
Diabetes Kidney Function
78
70*
57
52 (NCQA 2002)
Hypertension: BP < 140/90
55
68
57
58 (NCQA 2002)
Influenza Immunization
74
76
P
68 (BRFSS 2002)
Pneumocooccal Immunization
87
90
P
63 (BRFSS 2002)
Mental Health F/U 30 D post D/C
81
77*
61
74 (NCQA 2002) 38
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Arguments in Favor
Data Mining benefits are impossible
without computer technology
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• 20 Hospitals
• 100+ Clinics
• 450 employed physicians
• + Affiliated physicians
• Health Plans
• One million members and
affiliates
• Utah and southern Idaho
• $3.1B in annual revenue
• 25,000 employees
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Enterprise Data Warehouse
Integrated Reporting, Research and Analysis
EDW
Financial
Data
Claims&
Eligibility
Clinical
Data
Understanding the Care Process
 Healthcare Operations
Health Need
Diagnosis
AP/AR
Claims
Processing
Results &
Outcomes
Procedure
Patient
Perception
Episode of Care
 Supported by non-integrated data in Transaction Systems…
HNA
CIS/CDR
HELP
Rx
 Integrated in the Enterprise
Data Warehouse
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Lab
IDX
HDM
AS400
HPI
MC400
Survey
EDW
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IHC EDW: Then And Now
• 1.5 FTEs
• 1 million records of dubious quality
• Very academic prototype
• 10 users willing to take a risk
• 100 queries/month
1998
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2004
• 20 FTEs
• 4.2 billion records and growing
• “Mission Critical”
• 900 devoted users
• 80,000+ queries/month
• 3.9 Terabytes of data
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Motives Behind EDW & BI
• Fundamentally
– Drive healthcare costs down, quality up
• Sub themes
– Patient quality of life and safety, compliance,
evidence-based medicine, etc.
Reduce Mean Time To Improvement (MTTI)
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Low MTTI
• We may not like them, but…
• How do we measure their Cultural MTTI?
– Hours? Days? Weeks?
• They do epitomize analytic-driven, real-time process
improvement
– 423-terabyte system that churns data from 1,387 discount stores,
1,615 Supercenters, 542 Sam's Clubs, and 75 Neighborhood
Markets in the United States, plus 1,520 more stores worldwide
– Data available for analysis within 1-hour of a transaction
– Allows sales knowledge on East Coast to improve processes on
West Coast
– Anecdote: Thanksgiving Friday PC sales
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IHC Case Study
• Primary Care: Diabetes
– Motive: Improved long-term management of diabetes
patients
• RAND Study 2002: “64% of diabetic patients receive inadequate
care.”
– Integrates five disparate data sources
•
•
•
•
•
Lab
Problem list
Insurance claims: CPT’s and pharmacy
In-patient pharmacy
Hospital ICD-9
– Winner
• National Exemplary Practice Award 2002
– American Association of Health Plans
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Case Study: Diabetes Management
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Diabetes Management Peer Comparison Chart
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IHC Case Study 2
• CV Discharge Medications
– Motive: Basic protocol adherence
• Appropriate discharge meds ordered
following CV (IHD and MI) diagnosis
and treatment
– Results
• 1994: 15% (estimate, no hard data)
• 2004: 98% (hard data)
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The Real Benefits of BI
From IHC’s Cardiovascular
Clinical Program
Arguments Against
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There are those who prefer proven technology
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Arguments Against
Plenty of past failures to point to
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Past Clinical Information System Failures
Around The World
•
•
•
•
•
•
•
•
•
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Over budget / Delayed implementation
Partial implementation / Limited functionality
Replication failures - pilot succeeds, others fail
Temporary setback / Regroup - Redesign
Isolated system errors lead to patient harm
Major system outage / failure
Change CIS systems / vendors
Stop work on CISs
Total failure: Hospital closes due to system failure
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Public Health System
New South Wales, Australia
• NSW - 7 million people; Sidney - 3 million people
• Public Health System provides integrated hospital & community
services
• Budget $5 billion (US); 100,000 employees
• Geographically divisionalized structure
• Considerable dissatisfaction with current basic clinical &
administrative systems
– in-flexible, no Management Information
– Supplementary apps being developed
Southon et al. JAMIA 1997; 4:112-124.
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Public Health System New South Wales, Australia
• What happened...
– Financial - fairly extensively implemented
– Pathology - substantial success
– Patient Administration / Clinicals - completely withdrawn
after several pilots
Loss estimated $12 million US
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Lessons Learned...
• Difficulties Organizational NOT Technical
– Differences in business & operational environments
• NSW cost control rather than cost allocation
• NSW much larger span of control
• Main benefits due to integration of systems
• NSW no clerks available to enter orders
• Clinicians - some...not enough use to learn
Others...rotated out before they learned system
• Strategy developed at local hospital, formulated centrally
– Goal - cost-effective resource allocation
– Organizational structure - decentralized
• Local organizations focus on healthcare delivery, not costs
• Result: System selected did not meet local needs
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Arguments Against
Lack of evidence of public value
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• “The absence of a coherent body of evidence
demonstrating that effective use of ICT in health
can deliver real public value presents serious
problems....., it hampers public and political
debate on the use of ICT, potentially preventing
appropriate spending on ICT in the future.” (p. 83)
Jamie Bend
Public Value and e-Health
Institute for Public Policy Research
2004
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• “Until now, greater use of ICT has often
been seen as a good in of itself as part of a
process of modernisation. This is unlikely to
be the case in future and appropriate use of
ICT will have to be argued for and
supported with evidence that spending on
ICT will deliver benefits.” (p. 12)
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Protti’s formula for the future
• With deference and apologies to Albert E.,
perhaps the safest predictor of the future will
be to posit that it will be very much about
EbM2C
– Evidence-based Medicine
– Evidence-based Management
– Evidence-based Computing
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• “When the rapid development of ICT and
the ability of some systems to adapt to or be
altered for the specific environment in which
they will be used is also taken into account,
it becomes clear that evaluation of a new
computer system presents different
challenges to those faced when testing a new
drug.” (p. 58)
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The conundrum of measuring the
"IM&T investment"
• efficiency (doing things right) is easier to measure
than effectiveness (doing the right things)
• new systems are often intended to change difficult
to measure actions
• strategic systems elude measurement
• infrastructure investments cannot be cost justified
on a ROI basis
• it usually takes time for benefits to be identified
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• “It might take some time for the effects of a
new system to become clear. Possible
benefits of new ICT systems may only
become apparent after working practices
have altered to take advantage of the new
resource and this process could take several
months or years, presenting a particular
problem for those looking to evaluate pilot
projects.” (p. 58).
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• “While these barriers all offer possible
explanations for the fact that few benefits
are evident from previous e-health projects
and may yet adversely affect future projects,
none is insurmountable.” (p. 15).
• “As we demonstrated in chapter three, few
previous e-health projects have produced
real evidence of public value.” (p. 57).
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Arguments Against
Decision Support System Failures
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Further warnings from England
• A different form of caution comes in the December
2003 report released by the NPSA entitled
“Realising the Potential of GP Computer Systems
to Improve Patient Safety”.
• Since over 95% of GP practices in England are
automated and the most commonly used clinical
application are medication prescriptions which are
printed and carried to the pharmacy by the patient,
there was a commonly held belief that medication
errors were not a significant issue in primary care
in England.
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• To the surprise of many, the assessment of GP computer systems
revealed:
– lack of alerts in relation to contraindications – for example,
there was no warning of the risk of Reyes’ syndrome when
prescribing aspirin to an eight-year old child
– spurious alerts – for example a serious alert warning was
given for a commonly used and relatively safe drug-drug
combination
– failures of drug allergy warnings – depending on how the
allergy history had been recorded, warnings might or might
not be displayed
– risks of prescribing drugs with similar names – particularly
with penicillin (frequently used) and penicillamine (rarely
used and likely to do harm to some patients)
– lack of warning for inappropriate dosages – for example,
trying to prescribe methotrexate daily instead of weekly
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• Perhaps the most concerning finding was that
English GPs have come to rely on their computers
to provide alerts.
• More than 90% of GPs regarded computerised
alerts (including contraindication alerts) and
systems for recall for patient monitoring to be
important.
• The survey revealed that some GPs are not fully
aware of the safety features on their computer
systems and only a minority has had training on
the use of these safety features.
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Similar findings from the USA
Percentages of pharmacy computer systems that
failed to provide unsafe order alerts
Unsafe order not
detected %
Can override without
note %
Vincristine 3mg IV
X 1 dose (2 yo)
62
56
Cisplatin 204 mg IV
X 1 dose (26 kg
child)
63
55
Ketorolac 60 mg IV
(patient allergic to
ASA
12
64
Order
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Arguments Against
Ethical Use of Resources
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• “Since 1999, the federal and other governments in
Canada have repeatedly emphasized the value to
healthcare of electronic health records. In 2004, a
substantial UK investigation questioned the
evidence of public value of large scale, government
initiatives in healthcare information technology,
and of electronic health records in particular.”
Atherley G
Evidence of Public Value and Public Risk of Electronic Health Records:
An Issue for Social Justice?
ElectronicHealthcare
Vol. 4, No. 1, 2005
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• “Atherley examined the evidence pertaining
specifically to electronic health records as represented
in eight major health policy papers at the national
level published in Canada from 1999 to early 2005.
• He found during the period a decline in the concerns
expressed in the 8 policy papers about privacy,
security and availability of electronic health records
systems. It also found that some risks were barely
considered, if at all.
• Yet, during the same period, the Auditor General of
Canada issued strongly worded warnings about the
wide range of risks affecting information technology in
government.”
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• Atherley concluded that
a) evidence of public value and public risk of electronic
health records should be subject to the standards
increasingly used for and expected of evidence-based
medicine, and of assessments of pharmaceuticals and
medical devices;
b) at the national level, Canada lacks an independent
public accountability mechanism for analyzing public
value and public risk from electronic health records;
c) to the extent that, for electronic health records, the
public risks are plausible and the public values are
debatable, this lack is an issue of social justice.”
4-Apr-17
Denis Protti - University of Victoria
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Arguments Against
CPOE Failure at Mount Sinai
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Denis Protti - University of Victoria
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Medical Center
• Largest private hospital in California (850-bed hospital)
• Goals of $20 million Patient Care Expert (PCX) program:
– Help reduce medical errors,
– Allow physicians to electronically track their orders and
– Provide alerts when physicians prescribe treatments that would prompt
adverse reactions in patients.
• Big Bang adoption required all physicians to show they could use the new
system on 1 day or lose admitting privileges.
• 600,000 orders were logged on the system between October 2002 and
January 2003
• Over 400 physicians complained that "it was endangering patient safety and
required too much work,"
• PCX was suspended because “it was not easy enough to use and it took
too long to enter orders," not because of patient safety concerns.
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Medical Center
• Physician: “They poorly designed the system, poorly sold it and then
jammed it down our throats and had the audacity to say everybody loves it
and that it's a great system.”
• Administration: "Basically the hospital has decided to put on hold any
further experience with CPOE at least until 2006 while they work on other
aspects of the computer system to help with patient admissions, patient
flow, billing and so on.”
• Lessons Learned:
– Reinforces the importance of the cultural and organizational issues in
successful implementation
– Physicians must be the champions of this particular process in order to
bring it successfully to conclusion.
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Denis Protti - University of Victoria
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TDS 7000 Early Result
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Denis Protti - University of Victoria
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Arguments Against
CPOE – The Infamous JAMA Paper
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Denis Protti - University of Victoria
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• In March 2005, Professor Ross Koppel and colleagues from
the University of Pennsylvania published a paper on their
assessment of a commercial computer-based provider orderentry (CPOE) system that had been implemented at their
university hospital between 1997 and 2004.
• Their study showed that ‘‘a leading CPOE system often
facilitated medication error risks, with many reported to
occur frequently.’’ They concluded that ‘‘as CPOE systems
are implemented, clinicians and hospital must attend to errors
that these systems cause in addition to errors that they
prevent.’’
Koppel R, Metlay JP, Cohen A, et al.
Role of computerized physician order entry systems in facilitating medication errors
Journal of the American Medical Association
2005:293(10):1197-1203
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Denis Protti - University of Victoria
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• A main limitation of Koppel’s study is that it did not count
errors or adverse events, but instead measured only
perceptions of errors, which may or may not correlate with
actual error rates. Further, it did not count the errors that
were prevented. As such, it offers no insight into whether the
error rate was higher or lower with CPOE.
• Unfortunately, however, the press interpreted the study as
suggesting that CPOE increases the medication error rate.
While the authors did not state this, a press release put out by
JAMA did so.
Bates D
Computerized physician order entry and medication errors: Finding a balance
Journal of Biomedical Informatics
June 16, 2005
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• “We evaluated a vendor-developed/vendor-built system, the
predominant type in US hospitals, whereas several wellknown CPOE system studies were based on home-grown
applications tailored to the institution at hand.
• This useful distinction might explain some of the differences
between our findings and those of other scholars because
the constant re-evaluation, on-site research, and
responsiveness needed for good CPOE systems are more
likely to be found in the home-grown systems.”
Koppel R et al.
Neither panacea nor black box: Responding to three Journal of Biomedical Informatics
papers on computerized physician order entry systems
Journal of Biomedical Informatics
Article in Press - 2005
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• “As Bates indicates, after the initial installation of
the home-grown CPOE system at his institution,
they routinely tracked errors and problems and
made thousands of changes to the program,
because ‘‘it is just impossible to get it all right at
the outset, because the processes involved are so
complex.’’
• However, it is the vendor-developed/vendor-built
systems that are being installed nationwide,
generally in institutions with markedly lower
capability to adapt them than a large teaching
hospital like ours.”
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Other Closing Arguments
• In Favor
–
–
–
–
–
–
Telemedicine, wireless technologies, and remote monitoring
Patient portals and Personal Health Records
Bioinformatics (genomics and proteomics)
Existing and Evolving Clinical Technologies
Robotics and Virtual Reality Technologies
Etc.
• Opposed
–
–
–
–
–
–
–
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High costs of investment and wasted past expenditures
Lack of evidence from RCTs
Lack of clinician involvement and engagement
Insufficient government funding and incentives
Lack of change management strategies
Insufficient training and on-going support
Etc.
Denis Protti - University of Victoria
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Time for rebuttals and counter
arguments
THEN: Judging!!
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Denis Protti - University of Victoria
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In conclusion
• ‘We must stop blaming
people and start looking
at our systems. We must
look at how we do things
that cause errors and
keep us from
discovering
them…..before they
cause further injury’
Lucian Leape
Error in Medicine
JAMA 1994 : 272 1851-1857
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Barriers To IT Success In Healthcare
• Incestuous ideas and thinking
– We need to look at
manufacturing, aerospace,
banking, and retail for role
models. Look beyond HIMSS
and AMIA.
• We are committing vocabulary
overkill
– Death by a thousand cuts:
Vocabularies with 1 million
terms?!
– In pursuit of the perfect
standard vocabulary, we ignore
easy value with less perfection
• We do not treat IT as a true
profession
– We cross train clinicians and
expect them to be overnight
experts
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• Investment vs. Expectation is
misaligned
– Average: 3%-4% of budget on IT
compared to 8% in other industries
during their IT growth period
• What little data we collect, we
don’t analyze
– The ROI of an EHR/EMR is
negative if we fail to analyze the
data it collects
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We must keep the faith
• In hospitals in 1904
• It was not easy for all the doctors
to make the change. To some of
them the new way seemed more
cumbersome than the old, just
a lot of unnecessary red tape.
• It seemed much simpler to jot down a few notes in a
ledger lying open on the desk than to fill in all the blanks
on a form sheet, much easier to pull out one's own volume
and look up what old record was there than to call for an
envelope and wait till it was brought from the file.
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• At first some doctors just forgot about the record blanks
and used their ledgers when they were very busy, but in time
they all saw the worth of the new system
• (i.e. the medical record as we
know it today), and it became
a routine followed without
question and with tremendous
benefit.
Those introducing IT in health care settings
in the 21st century
can hope for as much success.
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Finite
[email protected]
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