An Approach to Guideline Implementation With GEM

1. An Approach toGuideline ImplementationWith GEM Richard N. Shiffman, MD, MCIS, Abha Agrawal, MD, Peter Gershkovich, MD, Aniruddha Deshpande, MD Center for Medical Informatics Yale University School of Medicine New Haven, Connecticut USA

2. Overview • GEM – the Guideline Elements Model • Implementation Issues • 3 Tasks in Implementation • Knowledge extraction • Knowledge customization • Knowledge integration

3. Guideline Elements Model • Knowledge model for guideline documents • Multi-level hierarchy (>100 elements) • Conceived and built in XML • Permits modeling at several levels of abstraction • Models heterogeneous information contained in guidelines in a standard way (ASTM, HL7) • Facilitates translation of guidelines into a format that can be processed by computers • Can be used throughout guideline lifecycle JAMIA 2000

4. HS INF Title Citation Identity Release Date Availability Contact Status Companion Document Adaptation Developer Name Developer Committee Name Funding Endorser Comparable Guideline Health Practices Category Purpose Target Population Rationale Objective Available Options Implementation Strategy Health Outcomes Audience Exceptions Care Setting Clinician Users Evidence Collection Evidence Time Period Method Evidence Grading Combining Evidence Specification of Harm/Benefit Quantification of Harm/Benefit Value Judgment Patient Preference Qualifying Statement Cost Analysis Recommendation Conditional (decision variable) . Action . Logic . Knowledge Reason . Strength of Recommendation . Evidence Quality . . . Cost . Certainty . Testing Algorithm Eligibility Definition External Review Revision Pilot Testing Expiration Date Scheduled Review

5. GEM: Major Components Guideline Document Header Document Body Intended Audience Target Population Testing Revision Plan Identity Developer Purpose Method of Development Knowledge Components JAMIA 2000

6. Algorithm Recommendation Definition Term Action Step Condit’l Step Branch Step Sync Step Conditional Imperative Term Meaning Knowledge Components Knowledge Components

7. Knowledge Components Recommendation Conditional Dec Var Action Reason Evid Quality Recmdn Strength Flexblty Link Ref Certainty Logic Cost Value Dec Var Cost Action Benefit ActionRisk Harm Action Descripn Action Cost Dec Variable Descripn Test Param Sensitivity Specificity Predictive Value Conditional

8. Guideline Implementation • Creation of strategies, systems, and tools to operationalize the knowledge and recommendations set forth by guideline developers • Aim is to change behavior • Implementation differs from dissemination

9. Black Box Published Guideline Computer-Based Guideline Implementation Implementation Process

10. What goes on in the black box? • 3 sets of activities • Knowledge extraction • Knowledge customization • Knowledge integration • GEM tools and solutions

11. Knowledge extraction • Not systematic / duplicable • Requires dual expertise • Inconsistency of encoding • Sequence of data collection • Level of detail • Atomic or composite statements • Specification of data elements • Omissions due to human error • Different recommendations would be givenfor the same patient Ohno-Machado L, JAMIA 1998 Patel V, JAMIA, 1998

12. Markup is simpler than coding • Recommendation 3 If an infant or young child 2 months to 2 years of age with unexplained fever is assessed as being sufficiently ill to warrant immediate antimicrobial therapy, a urine specimen should be obtained by SPA or bladder catheterization; the diagnosis of UTI cannot be established by a culture of urine collected in a bag. (Strength of evidence: good) Urine obtained by SPA or urethral catheterization is unlikely to be contaminated...

13. GEM Cutter

14. UTI Recommendation in XML <decision.variable id=dv1>age</decision.variable> <value>2 months to 2 years</value> <decision.variable id= dv2>unexplained fever</decision.variable> <decision.variable id=dv3>sufficiently ill to warrant immediate antimicrobial therapy</decision.variable> <action id=a1>obtain urine specimen by SPA</action> <action id=a2>obtain urine specimen by catheterization</action> <reason>the diagnosis of UTI cannot be established by a culture of urine collected in a bag</reason> <evidence.quality>Good</evidence.quality> <logic>IF (dv1=2m-2y) AND dv2 AND dv3 THEN a1 OR a2</logic>

15. Knowledge Customization • Guideline content inadequate for operationalization • Guideline weaknesses • Lack explicit definitions (Tierney, JAMIA 1995) • Focus on omission errors • Do not account for comorbid conditions, concurrent drug therapy, timing of interventions • Level of abstraction often inappropriate • Incompleteness, inconsistency • Protection of habit or self interest

16. XSL Stylesheet Prose Guideline Document Metadata DOM GEM Cutter GEM Document Knowledge Extraction Knowledge Customization Logician ER

17. Decidable?

18. Element “source” attribute • Explicit • Inferred • Selection from controlled vocabulary (NGC)

19. Knowledge integration • Support local workflow • Source of information • Codes / vocabularies • User interface

20. Knowledge Integration Activities • Decide mode of delivery for advice • Prescriptive • Critiquing • Set bounds based on evidence quality, recommendation strength • Incorporate patient preference

21. Documentation Recommendation Explanation Registration Communication Calculation Presentation Aggregation Provide Services for Information Management Shiffman, et al., JAMIA 1999

24. In conclusion… • GEM documents can serve as portable knowledge repositories for decision support systems. • Knowledge extraction • Knowledge customization • Knowledge integration

25. http:// ycmi.med.yale.edu richard.shiffman@yale.edu