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Transforming Guidelines Into Electronic Tools

Transforming Guidelines Into Electronic Tools. Richard N. Shiffman, MD, MCIS Yale Center for Medical Informatics New Haven, Connecticut, USA. Overview. Cultural contrasts Computer-based Decision Support Ways developers can help implementers

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Transforming Guidelines Into Electronic Tools

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  1. Transforming GuidelinesInto Electronic Tools Richard N. Shiffman, MD, MCIS Yale Center for Medical Informatics New Haven, Connecticut, USA

  2. Overview • Cultural contrasts • Computer-based Decision Support • Ways developers can help implementers • Implementers have some tools that may help developers • URL and email are on my last slide!

  3. ultures Rick Shiffman

  4. Suave and debonair

  5. Cultural difference: food

  6. We Read Different Journals

  7. August 20–24, 2007 We Meet in Different Places(at the same time!)

  8. Language differences • Guideline prose • Woolly, fudgy • Both inadvertent and deliberate • C#, JAVA, ASBRU, GLIF, … • Precise • Ambiguity causes crashes More About This Later…

  9. SAME GOAL:DIMINISHING INAPPROPRIATE PRACTICE VARIATIONPROMOTING KNOWLEDGE-BASED CARE Hip Fx (McGlynn. NEJM 2003) Pneumonia Diabetes Asthma Colorectal Cancer CHF Hypertension Senile Cataract % Receiving Recommended Care

  10. Strategies • Authors: Sculpting recommendations to match evidence • Implementers: Operationalizing recommendations in a system that influences behavior

  11. High Probability of Effectiveness • Patient-specific reminder at time of consultation • Grimshaw JM and Russell IT. Effect of clinical guidelines on medical practice: a systematic review of rigorous evaluations. Lancet 1993

  12. Computer-Based Decision SupportSystematic Reviews

  13. Findings • Computer-based decision support regularly—but not always—improves the process of care • Outcomes—though infrequently measured—sometimes improve

  14. CDSS Definition • A system that compares patient characteristics with a knowledge base and then guides a health provider by offering patient-specific and situation-specific advice CP Friedman JC Wyatt

  15. Functions of CDSS Randolph AG. JAMA 1999

  16. Documentation Templates Interpreter

  17. Documentation Templates Calculator Interpreter

  18. Relevant Data Summary

  19. Interpreter

  20. Alerts / Reminders Order Creation Facilitator InfoButton

  21. Thoughtful Assistant

  22. (Electronic) Implementers Need More Help from Developers Language Obstacles to Implementation Define Recommendation Strength

  23. Translation of Guideline Knowledge for Decision Support • Different recommendations would be given for the same patient using …encoded representations of vaccine- and breast mass workup guidelines formulated by different members of the (same) laboratory. Patel VL.JAMIA 1998

  24. Why is attention to implementability important? • “We found that it was possible—if not inevitable—that two encoders would encode the same guideline in two different ways. Sources of variation included differences in the order in which data elements are collected, differences in the level of detail represented, differences in the use of atomic sentences or composite sentences in criteria, differences in the specification of data elements, and omissions due to human error…

  25. Statement of fact is NOT a recommendation • Adjuvant hormone therapy for locally advanced breast cancer results in improved survival in the long term. • Clinicians should prescribe adjuvant hormone therapy for locally advanced breast cancer (when/unless?)…

  26. “Ambiguity”: Resolution by classification • Ambiguous statements are interpretable in more than one discrete way • “I’ll meet you at the bank.” • “MS”: morphine sulfate, magnesium sulfate; multiple sclerosis • “LAD”: left axis deviation, lymphadenopathy • Vague- lack a crisp threshold in a single dimension • “Fever,” “tall” • Underspecified - lack specificity in multiple dimensions • “sufficiently ill to warrant immediate antimicrobial therapy”

  27. Deliberate vaguenessand underspecification • Insufficient evidence • Inability to reach consensus • Legal concerns (standard of care) • Economic reasons • Ethical/religious issues (e.g., concept of “burden,” “futility of care”) • What if authors were transparent about • the reason for AVUL?

  28. Authors Should Be Explicit About • WHEN {under what circumstances} • WHO should • Do WHAT • To WHOM • HOW • WHY

  29. AUTHORS SHOULD USE STRONG VERBS • Active voice • Passive masks the actor • Appropriate choice of deontic operators • The clinician must, must not; the Committee strongly recommends • The clinician should, should not; the Committee recommends • The clinician may; the Committee suggests • The dreaded “consider”

  30. GLIA (GuideLine Implementability Appraisal) • Helps to identify obstacles to implementation • Provides feedback to guideline authors to anticipate and address these obstacles before a draft guideline is finalized • Assists implementers to select guidelines and to focus attention on anticipated obstacles • GLIA is available from http://gem.med.yale.edu/glia

  31. How does GLIA complement AGREE? • Limited to issues related to implementation • Emphasis on individual recommendation (rather than the guideline as a whole) • Concordance • Of 23 AGREE items (and 31 GLIA items) • 5 have equivalent questions in GLIA • 3 have similar questions in GLIA

  32. GuideLine Implementability Appraisal(GLIA) • Decidability - precisely under what circumstances to do something • Executability - exactly what to do under the circumstances defined) • Effect on process of care - the degree to which a recommendation impacts upon the usual workflow of a care setting) • Presentation and formatting - the degree to which the recommendation is easily recognizable and succinct • Measurable outcomes - the degree to which the guideline identifies markers or endpoints to track the effects of implementation of this recommendation

  33. GLIA Constructs (2) • Apparent validity - the degree to which a recommendation reflects the intent of the developer and the strength of evidence • Novelty/innovation - the degree to which a recommendation proposes behaviors considered unconventional by clinicians or patients • Flexibility - the degree to which a recommendation permits interpretation and allows for alternatives in its execution • Computability - the ease with which a recommendation can be operationalized in an electronic information system

  34. Guideline Authors are committed to appraising the quality of scientific evidence • As they should! • But they regularly fall short in helping users understand how to use the information • Implementers are rarely interested in evidence quality per se • Implementers need authors’ assessment of strength of recommendation

  35. Tripod of Concepts Confidence (we’ve got benefits & harms right: Evidence Quality) Benefits vs. Harms Assessment Importance of Adherence Recommendation Strength

  36. American Academy of PediatricsGrading Recommendation Strength Strong Option Rec Option No Rec Strong Rec

  37. Clinicians and Strong Recommendations • Benefits of the recommended approach clearly exceed the harms • Quality of the evidence is excellent • Clinicians should follow such guidance unless a clear and compelling rationale for acting in a contrary manner is present • Optimal source for P4P

  38. Clinicians and Recommendations • Benefits exceed the harms • Quality of the evidence on which this recommendation is based is not as strong • Clinicians generally should follow such guidance but also should be alert to new information and sensitive to patient preferences.

  39. Clinicians and Options • Evidence quality is suspect or well-designed, well-conducted studies have demonstrated little clear advantage to one approach versus another • Options offer flexibility in decision making about appropriate practice, although they may set boundaries on alternatives • Patient preference should have a substantial role in influencing clinical decision making • Hard to hold clinicians accountable (P4P)

  40. Electronic Implementers and Recommendation Strength • Strong recommendation • Cannot close form until issue is addressed • Recommendation • Recommended action is default; some effort required to override • Option • Radio buttons, checkboxes for choices within limited range

  41. (Electronic) Implementers have some tools that can help developers GEM EXTRACTOR eGLIA Action-types Implementation Section

  42. Logical Analysis with Highlighters • UTI 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...

  43. XML: From a small number of discrete colors to an unlimited palette

  44. XML • Multi-platform, Web-based, open standard • “Tags” enclose and describe text <inclusion.criterion>hematuria</inclusion.criterion> • Human-readable, yet can be processed by machine • Markup can be performed by non-programmers • “Hot”—considerable energies invested in X-tech

  45. GEM • Knowledge model for guideline documents • GEM adopted as a standard by ASTM in 2002; GEM II updated and re-standardized in 2006 • Models heterogeneous information contained in guidelines • Multi-level hierarchy (>100 elements) indicates relationships

  46. GEM II-Top Level

  47. Conditional

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