Transcript HCLS$$ClinicalObservationsInteroperability$EMR

Medical Informatics Perspectives on Leveraging the
Electronic Medical Record in Pharma
November 8, 2006
Scot M. Silverstein, MD
Assistant Professor of Healthcare Informatics and IT
Director, Institute for Healthcare Informatics
Drexel University, College of Information Science & Technology
(Former Director of Published Information Resources & The Merck Index, MRL)
Goals
• Promote better understanding of Medical Informatics as
a formal, cross-disciplinary clinical/IT specialty, lift veil
of mystery that leads to misuse of term.
• Raise awareness of national EMR initiatives on the
provider side, and how these may be increasingly
important to pharma in eClinical trials, post-marketing
surveillance and other needs.
• Raise awareness of difficulties in implementing largescale EMR, and how Medical Informatics professionals
can help (interestingly, analogous “sociotechnical” issues
are found in pharma).
The iSchools
Focus is on how people seek, use or interact with information using technology,
not simply on technologic devices and computer programs.
•
University of California, Berkeley
School of Information Management and Systems
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University of California, Irvine
The Don Bren School of Information and Computer Sciences
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University of California, Los Angeles
Graduate School of Education and Information Studies
University of Michigan
The School of Information
University of North Carolina
School of Information and Library Science
The Pennsylvania State University
School of Information Sciences and Technology
•
Drexel University
College of Information Science and Technology
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Florida State University
College of Information
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Georgia Institute of Technology
College of Computing
Rutgers, the State University of New Jersey
School of Communication, Information, and Library Studies
•
University of Illinois Urbana-Champaign
The Graduate School of Library and Information Science
Syracuse University
School of Information Studies
•
Indiana University
School of Informatics
University of Texas, Austin
School of Information
•
Indiana University
School of Library and Information Science
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University of Maryland
College of Information Studies
University of Pittsburgh
School of Information Sciences
University of Toronto
Faculty of Information Studies
University of Washington
Information School
Guiding Principles of Medical Informatics:
• Clinical IT will significantly benefit healthcare
quality, efficiency and costs only if done well.
• People issues are as critical towards success of
clinical IT initiatives in the provider sector as
well as in pharma.
The challenge:
• Deliver effective drug post-marketing
surveillance in an increasingly “aggressive”
marketplace.
U.S. Government Accountability Office (GAO)
• In a 2006 U.S. Government Accountability Office (GAO)
report to Congress on drug safety requested after congressional
hearings, a GAO investigation found that:
– FDA lacks clear and effective processes for making decisions about, and providing
management oversight of, postmarket safety issues. The process has been limited by a
lack of clarity about how decisions are made and about organizational roles, insufficient
oversight by management, and data constraints … There are weaknesses in the different
types of data available to FDA, and FDA lacks authority to require certain studies and
has resource limitations for obtaining data. Some of FDA's initiatives, such as the
establishment of a Drug Safety Oversight Board, a draft policy on major postmarket
decision making, and the identification of new data sources, may improve the
postmarket safety decision-making process, but will not address all gaps … FDA is
taking steps to identify additional data sources, but data constraints remain [1].
•
[1] “Drug Safety: Improvement Needed in FDA’s Postmarket Decision-making and Oversight Process”, United States
Government Accountability Office, Washington, D.C., March 2006, http://www.gao.gov/new.items/d06402.pdf , p. 5.
Gartner “Predicts 2006” document:
Life Science Manufacturers Adapt to Industry Transitions
http://www.gartner.com/DisplayDocument?doc_cd=134309
•
The swift and severe judgment in favor of the plaintiff in the first Merck Vioxx trial sent a shock wave
through the biopharma industry. It shows that biopharma manufacturers must do more to ensure that
healthcare providers and the public have an accurate, ongoing assessment of medication risks. Biopharmas
must also ensure that information on these risks is communicated promptly in an open, understandable
manner. Posting clinical trial information on a web site is one step towards greater transparency, but does
not provide information in a way that [easily] enables ... comparisons of benefits and risks.
•
... It is still well recognized that all the possible side effects of a medication cannot be uncovered using
[only] a randomized sample of study subjects. The true test of [long-term] safety and efficacy can only be
determined when trial data is combined with other sources of information such as clinical encounters,
adverse events (MedWatch) or observational studies (National Registry of Myocardial Infarction).
•
In the future, it is hoped that the EMR system will capture point-of-care information in a standardized
format that can be used for drug surveillance. Today, biopharmas must be content with these other
available, if imperfect, information stores.
Gartner Predicts 2006 (cont.)
•
Biopharmas ... should look at risk from multiple perspectives ... they must also get
actively involved in defining the electronic health and medical record so that it
will contain the type of information required to make better safety assessments
in the future.
•
Biopharmas that ignore the opportunity to use analytical tools to proactively review
contradictory sources of study information (for example, pre- and post-approval
clinical data sets, as well as registries) will miss essential signals regarding product
safety. Yet today, only a small percentage of biopharmas routinely utilize
personnel with medical informatics backgrounds to search for adverse events in
approved drugs.
Institute of Medicine weighs in
• The Committee on the Assessment of the US Drug Safety System of the
Institute of Medicine has written that:
– … the committee believes there is an abundance of extraordinary research opportunities
that could substantially enhance the [FDA’s] regulatory processes with respect to both
the efficacy and safety of new therapeutics. Many of the opportunities involve the
creation of new algorithms and methods to improve the processes of preclinical and
clinical drug development and new processes to enable effective safety and efficacy
monitoring and evaluation over the entire lifecycle of a therapeutic [1].
–
[1] “The Future of Drug Safety: Promoting and Protecting the Health of the Public”, Committee on the
Assessment of the US Drug Safety System, Alina Baciu, Kathleen Stratton, Sheila P. Burke, Editors,
Board on Population Health and Public Health Practice (BPH), Institute of Medicine (IOM), 2006,
Recommendation 4.6, p. 104-105, http://fermat.nap.edu/books/0309103045/html/104.html
Institute of Medicine weighs in (cont.)
•
In its new 2007 report “Preventing Medication Errors: Quality Chasm Series”, the
Committee on Identifying and Preventing Medication Errors of the Institute of
Medicine has written that:
– Informatics experts should track progress on the national health-information
infrastructure, look for opportunities to gather information about drug safety and
efficacy after approval, coordinate partnerships with external groups to study the use of
electronic health records for [drug] adverse event surveillance, participate in FDA’s
already strong role in setting national standards and track the development of tools for
data analysis in industry and academe, and encourage the incorporation of the tools
into FDA practice where appropriate [1].
–
[1] “The Future of Drug Safety: Promoting and Protecting the Health of the Public”, Committee on the
Assessment of the US Drug Safety System, Alina Baciu, Kathleen Stratton, Sheila P. Burke, Editors,
Board on Population Health and Public Health Practice (BPH), Institute of Medicine (IOM), 2006,
Recommendation 4.6, p. 102, http://fermat.nap.edu/books/0309103045/html/102.html
What is Medical Informatics?
•
Medical Informatics studies the organization of medical information from fine-grained levels
(e.g., biomedical data modeling) to macro levels (e.g., MedDRA, UMLS), the effective use,
management and dissemination of information using computer technology (e.g., EMR,
CDSS, CPOE), and the impact of such technology on medical research, education, and
patient care.
•
Formal, NIH-sponsored field on which NIH has provided many millions of dollars in training
grants for ~ the last two decades.
•
Has been nearly invisible to pharma for numerous reasons, largely due to misunderstanding
of the field. Unfortunate.
•
e.g., My analysis in PIR ca. 2000 identified significant cheminformatics and biomedical
informatics gaps, and through innovative use of technology and compelling arguments we
increased funding and availability of targeted scientific information to MRL R&D at least
tenfold by late 2003 over averages kept since ~ 1989. eJournals /Alertlink/ SciFinder /
CrossFire etc.
The Informatics Subspecialties
NIH training programs in Medical Informatics
http://www.nlm.nih.gov/ep/GrantTrainInstitute.html
1-Harvard-MIT Division of Health Sciences & Technology, 2-Yale University, 3-Columbia University, 4-University of Pittsburgh, 5Johns Hopkins University, 6-Medical University of South Carolina, 7-Vanderbilt University, 8-Indiana University - Purdue University
at Indianapolis, 9-University of Wisconsin Madison,10-University of Minnesota Twin Cities, 11-University of Missouri Columbia,
12-Rice University, 13-University of Utah, 14-University of California Irvine, 15-University of California Los Angeles, 16-Stanford
University, 17-Oregon Health & Science University,18-University of Washington (training is provided by other universities via
internal funds as well).
Medical Informatics: What it is not
•
•
The increasingly common use of awkward expressions like "informatics technology" to refer
to clinical information systems is an example of semantic blur. Medical informatics is a
formal field of study and a scientific discipline. Computers in medicine is not the equivalent
of medical informatics.
Yet, position descriptions such as in these employments ads, with requirements for neither
clinical nor medical informatics training or experience, are often seen. From the Philadelphia
Inquirer:
–
Medical informatics analyst. [Company name] seeks a Medical Informatics Analyst to support resource management
and medical affairs in their data analysis needs. Through downloading of MCS database, PC-based analysis of clinical
and clinically-relevant financial data will be performed. Qualifications: BA/BS in computer science or related
discipline, 3-5 years experience in PC-based data analysis of health care information, knowledge of SAS or similar
analysis software, knowledge of mainframe DB2 database architectures, working knowledge of CPT-4 and ICD-9-CM
coding."
–
From an Internet biomedical employment service, Medzilla.com: [Company name] seeks a Director of Clinical
Informatics. Overall coordination of design specifications, implementation and support for all internet/browser based
systems. Assurance of continued, reliable and consistent resources and applications to all corporate personnel and
external users who may rely upon these systems. Documentation and control of said software systems including
package systems and license control if necessary. Provide ongoing maintenance oversight and management support for
said systems. Organize and train personnel, both internal and external, who will be using said products. Client contact
and development and assist Sales and Marketing as necessary in client presentations. Minimum of a BA. MBA
preferred.
Medical Informatics: what it is not
• Blur in usage of the term "medical informatics" is highly ironic. One major
area of study in medical informatics research is language (e.g., controlled
terminologies, computation linguistics) and data modeling.
• In applied efforts in that area, exhaustive attention to lexical and semantic
issues and intense thinking about precision and imprecision in language
have led to excellent tools such as the National Library of Medicine's
Unified Medical Language System. Now, it seems the medical informatics
field is often finding its own name used in an imprecise way.
• Imagine impact of similar difficulty with, say, Medicinal Chemistry…
Why is Medical Informatics Important to EMR and
other healthcare IT initiatives?
• A number of very expensive healthcare IT project difficulties and failures have
appeared in the literature in recent years in large part due to organizational
change resistance, internal political struggles, lack of expertise in IT
implementation processes most suitable for clinical environments, and other
sociotechnical issues.
–
–
–
–
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Cedars-Sinai Hospital in Los Angeles [Doctors pull plug on paperless system. American Medical News, Feb.
17, 2003]
Hospital of the University of Pennsylvania [Role of computerized physician order entry systems in
facilitating medication errors. Koppel et al., JAMA 2005;293(10):1197-203]
VA hospital CoreFLS failure - $472 million [http://www.usmedicine.com/article.cfm?articleID=932&issueID=66]
United Kingdom NHS initiative [Doctors fear £6bn IT project will be a fiasco. The Guardian, February 8,
2005. [http://society.guardian.co.uk/internet/story/0,8150,1407903,00.html]
Others [website Sociotechnical Issues in Health IT: Common Examples of Health IT Failure]
Pharma examples – CRISP project - In the 1990s, [pharma] struggled to erect a modernized clinical data
system known as CRISP (Clinical and Regulatory Information Strategic Program), a project that current and
former information systems workers came to regard as a $100 million loss. "This project ran into a lot of
problems," says one former manager who was involved near the beginning of the CRISP project.
[http://www.baselinemag.com/article2/0,1397,1608582,00.asp]
Why is Medical Informatics important? (cont.)
• Healthcare IT and its environment are core competence
• Recognition that organizations are simultaneously social (people, values,
norms, cultures) and technical (tools, equipment, technology). These
elements are deeply interdependent and interrelated. Good design and
implementation is not just a technology issue but also one of jointly
optimizing the combined sociotechnical systems.
• Medical Informatics training recognizes these issues and trains crossdisciplinary specialists accordingly. Curriculum example:
–
Fundamental of computer science
Medical language and terminology systems
Modeling of medical observations and data
Medical coding systems
Medical knowledge structures
Information organization and flows in medical practice
Quantitative models for medical decision making
Clinical decision support
Medical image processing
User interfaces and ergonomics in healthcare
Health information systems architecture
Security and confidentiality
Ethical and legal issues in electronic medical records
Organizational and sociological issues in clinical IT projects
Metrics and methods for evaluating healthcare information systems
Cost and investment issues in healthcare IT
National EMR Initiatives: U.S.
• Transforming Health Care: The President’s Health Information
Technology Plan
–
http://www.whitehouse.gov/infocus/technology/economic_policy200404/chap3.html
– President Bush has outlined a plan to ensure that most Americans have
electronic health records within the next 10 years. The President believes that
better health information technology is essential to his vision of a health care
system that puts the needs and the values of the patient first and gives patients
information they need to make clinical and economic decisions – in
consultation with dedicated health care professionals.
• Office of the National Coordinator for Healthcare IT (ONCHIT)established April 2004
–
http://www.hhs.gov/healthit/
National EMR Initiatives: U.K.
•
National Programme for IT in the NHS (described as “the world’s biggest
government IT project”)
–
–
•
http://www.connectingforhealth.nhs.uk/
The National Programme for IT, delivered by the new Department of Health agency NHS Connecting
for Health, is bringing modern computer systems into the NHS to improve patient care and services.
Over the next ten years, the National Programme for IT will connect over 30,000 GPs in the U.K. to
almost 300 hospitals and give patients access to their personal health and care information,
transforming the way the NHS works.
The infrastructure will include new components integrated into existing national
reporting databases:
–
–
A centralized national database, called the NHS Care Record, to include all patient electronic health
records. This data will likely be useful for epidemiological studies and drug surveillance on a national
scale (!)
A Patient Demographics Services operation that will act as an enterprise master patient index (EMPI)
for the entire country, based on the patient's NHS number, a national patient identifier, and
demographic and patient encounter information.
Pharma takes notice: Integrating Patient Information with Drug Development
Nov. 2005: “Merging Electronic Health Records & Electronic Data Capture: Integrating Patient
Information with Drug Development”
http://exlpharma.com/events/ev_brochure.php?ev_id=17
•
Exploring the Opportunity for Collaboration with Drug & Device Firms in Accelerating IT Adoption by Hospitals &
Physicians: The government’s 10-year plan to automate healthcare information exchange by creating the National Healthcare
Information Network presents an undeniable opportunity to synchronize patient information with drug development and
increase the overall quality of patient care.
•
Drug & device companies have been struggling for years to successfully and efficiently move away from paper data collection
towards electronic data capture and automated trials. Without a unifying body behind this push, data standards,
interoperability and infrastructure compatibility have not been achieved. By piggy-backing on this government-lead initiative
to automate healthcare, drug and device firms can reap the benefits of the increased efficiency IT adoption at the hospital and
physician level will offer and utilize this data for more streamlined drug development [and other uses – ed.]
•
ExL Pharma’s Merging EHR & EDC Conference is the “first opportunity for drug & device firms to gather with hospitals,
physicians and vendors to discuss strategies for accelerating IT adoption and achieving cross-functional data interoperability to
streamline processes, improve communication and maximize patient care.”
KEYNOTE PRESENTATION
Improving Patient Care while Optimizing Efficiency: Outlining the Potential Benefits from Merging Patient Care and Drug Development Efforts
Barbara Tardiff, MD, MBA
Executive Director, Research Information Services, Clinical & Regulatory Information Services
MERCK & CO., INC.
HOSPITAL PERSPECTIVE: The Challenges and Limitation of Merging Electronic Health Information Robert N. Hotchkiss, MD
Director, Clinical Research
HOSPITAL FOR SPECIAL SURGERY
STANDARDIZATION EFFORTS: Interchange Standards: The Key to Linking Healthcare and Clinical Research Information Rebecca Kush, PhD, President, CDISC
Landen Bain, Healthcare Liaison, CDISC
Sue Dubman, Director of Applications for the Center of Bioinformatics, NCI
Upcoming DIA-sponsored conference
• “The Quest to Enable the Electronic Clinical Trial: Finding
Clarity in a Confusing World” (Dec. 2006,
http://www.diahome.org/product/11116/06029.pdf
)
• Learning objectives:
– Discuss medical informatics opportunities to improve the benefit-risk
assessment of drugs
– Explain standard controlled terminology and its current and future use
– Summarize how changes in the drug development industry impact people and
processes
– Discuss how clinical research can help drive the adoption of healthcare IT
standards
– Describe how increasing data transparency can benefit the public interest
EMR for post-market surveillance: possible?
•
Use of EMR for drug surveillance has begun to be studied. There have been exploratory studies on this
topic and related areas:
–
–
–
–
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Murff et. al. reviewed current methodologies for detection of clinical adverse events including electronic methods that
can detect events using coded data, free-text clinical narratives, or a combination of techniques [1]
Gandhi et. al conducted a similar review specifically aligned to drug safety issues and believe computerized
monitoring for adverse drug events using rules or “triggers” is a high yield and relatively inexpensive strategy that
should be adopted by healthcare organizations [2].
Nebeker et. al. described prospective daily reviews of EMR data performed by pharmacists as an effective way to
detect adverse drug events [3].
Honigman et. al. reported on an automated, computer-based retrospective analysis for adverse drug events of one year
of data from an EMR, including records on over 23,000 patients. The conclusion was that computerized search
programs can detect adverse drug events in such data and that such detefction programs demonstrate “value added” for
the EMR [4].
Efforts in using EMR’s for drug post-marketing surveillance can also serve as a test bed for identifying and resolving
issues in broader uses of national EMR of even greater significance, such as syndromic surveillance for early epidemic
detection or detection of chemical terrorism or bioterrorism. Syndromic surveillance refers to using health-related data
that precede diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health
response. Hegmann et. al. described a system to detect possible bioterrorist attacks during the 2002 Olympic Games
using an EMR-based bioterrorism surveillance system. The system implemented 50 different analyses that examine a
range of symptoms to detect and track infectious diseases [5].
•
•
•
•
•
[1] “Detecting adverse events for patient safety research: a review of current methodologies”, Murff HJ, Patel VL, Hripcsak G, Bates DW, Journal of
Biomedical Informatics, 36(1-2):131-143, Feb-Apr 2003.
[2] “Identifying drug safety issues: from research to practice”, Gandhi TK, Seger DL, Bates DW, International Journal for Quality in Health Care, 12(1):6976, Feb. 2000.
[3] “High rates of adverse drug events in a highly computerized hospital”, Nebeker JR, Hoffman JM, Weir CR, Bennett CL, Hurdle JF, Archives of Internal
Medicine 165 (10): 1111-1116, May 23 2005.
[4] “Using computerized data to identify adverse drug events in outpatients.” J Am Med Inform Assoc. 2001 May-Jun;8(3):254-66.
[5] “Computer model developed at U. Utah monitors bioterrorism”, Daily Utah Chronicle (U. Utah), Feb. 4, 2002
EMR for postmarket surveillance (cont.)
•
Utilizing large quantities of EMR data, innovative statistical models and methods for analysis of extremely
large datasets (large number of observations or large number of dimensions), an active area of research, will
be necessary to supplement and replace more simplistic methodologies (e.g., adverse event frequency
comparisons) for leveraging EMR data. Research in computational statistics, for example, involves the
development of visualization and computationally intensive methods for mining large, nonhomogeneous, multi-dimensional datasets so as to discover knowledge in the data [1].
•
Research has been done specifically in the application of data mining techniques in drug surveillance. The
authors of one study describe knowledge discovery in databases (KDD), a technique to detect potential
adverse drug events involving the selection of data variables and databases, data preprocessing, data mining
and data interpretation and utilization. They describe data mining as encompassing a number of statistical
techniques including cluster analysis, link analysis, deviation detection and “disproportionality” assessment
which can be utilized to determine the presence of and to assess the strength of adverse drug event signals.
The authors concluded that in view of the importance of adverse drug events and the development of
massive data storage systems and powerful computer systems, the use of data mining techniques in
knowledge discovery in medical databases is likely to be of increasing importance in the process of
drug surveillance as they are likely to be able to detect signals earlier than more common methods
currently in use [2].
•
•
[1] Computational Statistics in the Data Sciences, George Mason University,
http://www.scs.gmu.edu/~jgentle/compstat/index.html
[2] “Application of data mining techniques in pharmacovigilance.” Wilson AM, Thabane L, Holbrook A., Br J Clin
Pharmacol. 2004 Feb;57(2):119-20.
False assumption and underestimations:
implementing EMR not as easy as it seems
• Medical informaticists study the issues that impede EMR
adoption in clinical settings.
• What you didn’t want to know about clinical information
technology in large medical centers: (compare issues to your
own project difficulties in pharma or CRO settings):
– See “Sociotechnologic issues in clinical computing: Common
examples of healthcare IT failure” at
http://www.ischool.drexel.edu/faculty/ssilverstein/medinfo.htm
Access Patterns to a Website on Healthcare IT Failure
Scot M. Silverstein MD, Yunan Chen, Christine Wania
College of Information Science & Technology, Drexel University
Visitor types
Background
3000
Organizational and human factors (sociotechnical) issues
associated with healthcare IT have led to project difficulties and
failures. Detailed case accounts might improve knowledge
sharing between healthcare organizations on lessons learned and
best implementation practices. Based on an online search for
web-based resources, there appears to be few relevant sites
containing either high-level or case-level information regarding
healthcare IT difficulty and failure. Case-level accounts
describing issues at a fine level of granularity, such as detailed
accounts of interactions among clinicians, IT personnel and
healthcare executives, are potentially useful learning resources.
Knowledge sharing via the Web on best practices for
management of sociotechnical impediments to healthcare IT is
thus suboptimal.
2842
2500
2000
1500
1000
564
332
500
239
149
97
93
11
0
ISP
Note: The terms in this diagram represent our categorization of the concepts used by Web
searchers to find our website. For example: “healthcare IT” might have been expressed
as “medical computing” or “clinical information technology.”
University /
Other
Healthcare
Educational Organization Organization
Institution
Unknown
Government
Organization
Healthcare
Related
Industry
Other
Individual
Visitor Countries distribution
Case Study Results
Research Questions
We studied access patterns to our website on healthcare IT difficulties. The
distribution of countries, website visitor types and query types are shown in the
following charts:
 To illustrate the level of interest and knowledge sharing about
Healthcare IT difficulties, we explored two research questions:
 What case-level information about healthcare IT project
difficulty and failure is available via the Web?
 Who is seeking this information?
Visitor Input Types
2500
2252
2000
Methods
1500
Conclusion
1000
We used our website, entitled “Sociotechnologic Issues in
Clinical Computing: Common Examples of Healthcare IT
Failure”, online since 1999, as a representative information
resource.
We first conducted a detailed Web search on various search
phrases representing the concept “healthcare IT failure” using
three major search engines (Google, Yahoo, and MSN). The
results showed that our website was nearly unique. We then
tracked views of our website from Sep 27th, 2005 to June 30th,
2006 with a free public tracking service, eXTReMe Tracking
(http://extremetracking.com).
206
500
166
132
0
Search Engine
Healthcare IT Site
Other
Non Healthcare IT
Site
Visitor Search Engine Referrer Input
774
800
700
600
423
500
Our website “Sociotechnologic Issues in Clinical Computing:
Common Examples of Healthcare IT Failure” is at URL:
389
400
We examined the access logs to determine viewer IP and referrer
(primarily search engine query, or link from another site) to
identify viewer demographics including country and organization
type, where available. No personally-identifiable information
was sought or obtained.
It appears there is an ongoing interest in information about
healthcare IT difficulty among searchers of varied
demographics, as evidenced by searches on these issues and
resultant “hits” on our website, one of the few websites that
specifically addresses these issues. At present such material is
uncommon. We believe Medical Informatics specialists can
contribute significantly to filling this information gap, and that
doing so would be very helpful to the healthcare IT
community.
227
300
193
200
116
100
0
Healthcare OR
IT OR Failure
Healthcare
AND IT
IT Failure
Healthcare IT
Failure
Unrelated
Project
Management
http://www.ischool.drexel.edu/faculty/ssilverstein/medinfo.htm
It was created by our first author via an informal collaboration of
AMIA clinical information systems working group members (CISWG) during 1998-2001.
Why is good clinical IT difficult?
•
Lindberg: “Computer Failures and Successes”, Southern Medical Bulletin 1969;57:18-21
–
•
Nemeth & Cook: “Hiding in Plain Sight”, Journal of Biomedical Informatics 38 [2005], 262–263
–
•
Computer experts per se have virtually no idea of the real problems of medical or even hospital practice, and
furthermore have consistently underestimated the complexity of the problems…in no cases can [building appropriate
clinical information systems] be done, simply because they have not been defined with the physician as the continuing
major contributor and user of the information.
Just beneath the apparently smooth-running operations [of healthcare] is a complex, poorly bounded, conflicted,
highly variable, uncertain, and high-tempo work domain. The technical work that clinicians perform resolves these
complex and conflicting elements into a productive work domain. Occasional visitors to this setting see the smooth
surface that clinicians have created and remain unaware of the conflicts that lie beneath it. The technical work that
clinicians perform is hiding in plain sight. Those who know how to do research in this domain can see through the
smooth surface and understand its complex and challenging reality. Occasional visitors cannot fathom this demanding
work, much less create IT systems to support it.
Wears & Berg: “Still Waiting for Godot”, JAMA Vol. 294 No. 2, July 13, 2005
–
Throwing IT at a health care system to remedy high medication error rates will not be effective unless the
organizational reasons for those failures also are addressed. These reasons are hidden in the "messy details" of
clinical work: complexity; uncertainty; conflicting goals; gaps in supplies, procedures, and coordination; brittleness of
tools and organizational routines.
The often divergent goals of three main groups within a medical center
From Sittig DF, Sengupta S, al-Daig H, Payne TH, Pincetl P. The role of the information architect at King Faisal Specialist Hospital and Research Centre.
Proc Annu Symp Comput Appl Med Care. 1995;:756-60
The Three Stakeholder Groups in More Detail
Administration (purchasers)
• CEO
• COO
• CFO
• Gen Counsel
• CIO
• IT staff
• Consultant
Information Technology (implementers)
• Clin leaders
(SVP, COS,
Dept. Chairs)
• Clinicians
• Service Mgr.
Medicine (users)
Observed Drivers: Health System Administration
Chief Executive Officer (CEO)
Chief Financial Officer (CFO)
Chief Operating Officer (COO)
General Counsel
Institutional reputation
Board issues
Internal relationships
Financial issues
Up-front costs (capital & expense)
Secondary dollars (longer-term clinical
revenue/technologic expense)
“Return on investment”
Skepticism
Operational changes (in processes)
Managerial control
Staffing
Costs
Liability / litigation on:
Clinical issues
Information security
Observed Drivers: Information Technology (MIS)
Chief Information Officer (CIO)
IT Staff
Consultants
Budget - effects on other projects,
especially MIS (management information
systems)
“Plug and Play” - ease of implementation,
human resource s
IT control - territoriality
IT reputation - insecurity in new clinical
domain
Fear - clinical environments are alien to MIS
Hands-on technology issue s
Job stability
Revenue
Client satisfaction
Future engagements
Observed Drivers: Clinicians
Clinical Leadership (Chief of Staff, VP for
Medical Affairs, Department Chairs, Nursing
VP)
Clinicians (primary users)
Service Line Administrator
Change to clinician workflow
Complaints
Care issue s
Usefulne ss of system (dataset issue s,
adaptability - opposite of plug and play)
Work changes / time issue s
Effects on care quality
Liability
“Grading” & physician practice reporting
Income
Effects on busine ss development
Institutional reputation
Clinician relations
The undesired dynamics
Administration
• CEO
• COO
• CFO
• Gen Counsel
• CIO
• IT staff
• Consultant
Information Technology
• Clin leaders
(SVP, COS,
Dept. Chairs)
• Clinicians
• Service Mgr.
Medicine
Medical Informatics as Intermediary
Administration
• CEO
• COO
• CFO
• Gen Counsel
MI
• CIO
• IT staff
• Consultant
Information Technology
• Clin leaders
(SVP, COS,
Dept. Chairs)
• Clinicians
• Service Mgr.
Medicine
The desirable dynamics
Administration
• CEO
• COO
• CFO
• Gen Counsel
MI
• CIO
• IT staff
• Consultant
Information Technology
• Clin leaders
(SVP, COS,
Dept. Chairs)
• Clinicians
• Service Mgr.
Medicine
Medical Informatics role
• Responsible for helping these three groups understand they
are all working toward the same goal, and ensuring medical
center personnel collaborate efficiently and productively.
• Understanding and work with the stakeholder drivers
(motivators) and dynamics (interactions) in detail will help
the MI proactively intervene and avoid retrospective
correction after problems have arisen.
Take-away points
• The emerging national EMR’s will provide a useful resource for
postmarketing drug surveillance activities and research.
• Clinical IT projects are complex social endeavors that happen to
involve computers, as opposed to information technology projects that
happen to involve doctors.
• An understanding of the internal dynamics by the medical informaticist
is an important asset towards facilitating success of EMR initiatives and
optimal leveraging of its capabilities for healthcare providers – and for
pharma.
• This understanding and experience relative to clinical IT is portable to
pharma and can be of great value in other eClinical initiatives and in
collaborations with the provider side.
Additional Reading
• Managing Technological Change: Organizational Aspects
of Health Informatics. Nancy M. Lorenzi, Robert T. Riley
(Springer-Verlag, 2nd edition, 2004, http://www.amazon.com/ManagingTechnological-Change-Organizational-Informatics/dp/0387985484 ).
• Advance for Health Information Executives: “Medical
Informatics, Friend or Foe”, R. Gianguzzi, May 1, 2002, p.
37-38
Dean Sittig, Director of the national Clinical Informatics
Research Network (CIRN) for Kaiser Permanente: "There are
many different constituencies, and hence views, which must be
considered when attempting to develop an integrated clinical
information management system in any large medical center ...
we believe that without a full-time, on-site [medical
informaticist], the difficulty of the task increases to the point of
becoming nearly impossible."
Questions?
SAYGR Registry
Yale-Saudi Arabia Collaboration in Clinical Genetics & Birth Defects
Dec. 1995
Informatics can take us to esoteric places:
Red Sand Dunes area, ~ 50 km w. of Riyadh