clinical informatics virec cyberseminar series 2006 clinical informatics attributes of an ideal...
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VIReC CyberSeminar Series 2006
Clinical InformaticsClinical Informatics
Attributes of An Ideal Informatics System with
Highlights from a State of the Art Conference
Denise M. Hynes, Ph.D., R.N.
Director, VIReCDirector, VIReCResearch Health Scientist, MCHSPR COEResearch Health Scientist, MCHSPR COE
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HSR&D Resource Centers
CCiiDERDER = Center for Information Dissemination & Education Resources = Center for Information Dissemination & Education Resources
HERCHERC = Health Economics Resource Center = Health Economics Resource Center
metricmetric = Measurement Excellence & Training Resources Information Center = Measurement Excellence & Training Resources Information Center
VIReCVIReC = VA Information Resource Center = VA Information Resource Center
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Series/Course Objectives
• To learn about applications in clinical informatics in research and quality improvement efforts– VA and non-VA efforts
• To understand approaches for evaluating clinical informatics and IT interventions
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Selected Course Topics• Attributes of an Ideal Information System:
Highlights from a State of the Art Conference• Approaches for Evaluating Health Informatics
Technology and CDSS• Implementation of CDSS in Hypertension
Management• Implementation of a CDSS in Mental Health• Using CDSS in Pain Management• Informatics Applications for Promoting Collaborative
Care
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Session Objectives
• Understand the key aspects to consider in a clinical information system
• Understand the desired attributes of a clinical information system
• Become aware of the barriers and facilitators to use of IT in healthcare and research
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IOM Quality Chasm Report, 2001
• Predominance of chronic care
• Need for evidence-based practice
• Critical value of information technology
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IOM Committee on Quality of Health Care in America
• Point-of-care access to health literature and evidence-based guidelines
• Computer-assisted decision support systems;• Computerized patient clinical data• Automation of decisions to reduce errors• Electronic communication between providers • Electronic communication between providers
and patients
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Informatics Support for Clinical Practice Guideline Implementation
Step Facilitators Informatics Support
AwarenessPriming Activities such as
profiling of baseline performance
Profiling from prescription order and diagnosis database
Acceptance
Active education such as Academic Detailing;
Clinical Opinion Leaders
Present evidence relevant to patient; allow opinion leaders to browse knowledge base
AdoptionEnabling strategies such
as incorporation into clinic workflow
Integration with existing EMR/CPRS
AdherenceReinforcing Strategies such
as remindersPoint-of-care patient-specific
advisories & alerts
Pathman, et al. Medical Care 1996; 34:873-889
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Diffusion of Innovation Theory: Key Dimensions
• Nature of the innovation itself
• How communication channels can be impacted
• Time
• Social system and organizational context
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Challenge of Using Information Technology (IT) for QI
• Integrating new forms of decision support into legacy data systems and electronic record interfaces
• Sociotechnical aspects
Goldstein, et al., JAMIA 11: 368-76, 2004.
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Berg’s Sociotechnical Success• Technical success
– generates correct recommendations offline– extracts and uses patient data correctly– integrates with CPRS to display for the right
• Patient,• Provider• Clinical location• Time window
– tracks the data needed for research evaluation
• Sociological success– clinicians find it usable and useful
Berg, M., Int J Med Inf, 1999. 55(2): p. 87-101.
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Social Challenges of IT in Health
• Clinicians’ time constraints– Strike balance between ease of access to system and
ease of ignoring it– Balance with interpersonal needs of patients
• Variability in comfort with computers– And virtually no training time available
• Lack of consensus/agreement about the guidelines
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State of the Art Conference Summary
Attributes of an Ideal Integrated Informatics System that Supports
Implementation of Evidence
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The ideal information management system supports managers, providers and patients to achieve practice and outcomes consistent with evidence
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• Supports knowledge-based decisions • Evaluation/Reporting Capability • Evolves with health care system• Accurate/Correct Content • Standardized/Compatible
Attributes of the Ideal Information System
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• Defined Accountability: organization vs. provider
• Equitable: “No service/facility left behind”• Sustainable • Secure
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• Usable – Integrated – All electronic– flexible– transparent to users– non intrusive – easily up-datable
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• Current Information Systems do not fully utilized knowledge-based decision support
• Clinical reminders, order check system, notification and alerts
• Data capture limited to local system• Difficult to prioritize• Handling of adverse events
Priority 1: Supports knowledge-based decisions
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Strategies:• Research on how to prioritize• Require research to include data on added
value in terms of mortality and morbidity
Barrier: too much info/provider overload
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Strategies: • National patient data record• Patient ownership of patient data, guidelines and
reminders• Common patient identifier• Common provider identifier• Integration across systems• Research on what information users need
Barrier: lack of integration
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Strategies: • Basic research in managing information
complexity• Alignment of research priorities with
clinical management • Performance measures focused on how
much evidence informs practice• Regular presentation of significant
translation research findings to senior leadership
Barrier: Operationalizing evidence
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Strategies: • Flexibility in decision support with required
feedback about reasons for non-compliance and barriers to compliance
• Local review of compliance with local solutions (tailored training)
• Add autonomy in other areas: e.g., guideline input, self-review, link to reference materials
Barrier: Threats to provider autonomy
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• rapid monitoring and feedback for evidence-based practice
• recommend appropriate treatment (reminders), track actual treatment and results, provide ongoing analysis of effectiveness
• Support analysis and review at different levels and contexts
Priority 2: Reporting/Evaluation Functions
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Strategies: • More automation of data (e.g., link
diagnosis to test)• Review and monitoring of data
quality• Linkages to other information in EHR
so provider doesn’t have to reenter (e.g., test results)
Barrier: Data issues
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Reporting complexity requires specialized knowledge
Strategies: • Use OLAP cubes to simplify user
generation of reports
Barrier: Reporting complexity
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Reporting function on existing patient care system eats system resources, slows response time
Strategies: • Move reports off system – put analytical
tools on a system separate from pt care system
Barrier: System resources
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• Aspects of the information system are based on prior care models
• Current methods of data collection may not match business process or support evidence-based practice
Priority 3: Information system needs to evolve with health care system
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Strategies:• Develop patient-centered data
collection methods, core data elements, and system capacity for patient-based health data sets
• Encourage basic research on capturing home care data for all stakeholders
Barrier: Emphasis on provider-level activities and provider-
entered data
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• Focus on outcomes (maintaining/improving functional status of the patient), not workload
• encourage “just in time” rather than “just in case” visits, collect interim data remotely
Barrier: Emphasis on workload rather than care received by
patient
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Some Summary Remarks
• Technology must be tailored to providers’ needs• Fit into workflow in real time• Minimize request for additional information• Meet need for speed• Elicit feedback and respond• Tracking mechanisms needed to support research