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Modeling Recommendation Sets of Clinical Guidelines. Samson Tu Stanford Medical Informatics Stanford University School of Medicine HL7 Working Group Meeting Memphis, TN September 11, 2003. Outline. Original work-item goal Reformulated work item Review of past work
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Modeling Recommendation Sets of Clinical Guidelines Samson Tu Stanford Medical Informatics Stanford University School of Medicine HL7 Working Group Meeting Memphis, TN September 11, 2003
Outline • Original work-item goal • Reformulated work item • Review of past work • SAGE implementation experience • Next steps?
Original work-item goal • To develop standardized “flowchart” model for human understanding and computer encoding • Expressive process model • allows sequencing, repetition, and concurrency (branching and synchronization) • Integration of decision making and activity specification • Visual clarity • Well-understood semantics
Background: problems • What is a flowchart? • Different usages: not all diagrams represent processes • Workflow process model may not be appropriate for all • Study of guideline diagramming conventions Tu, SW, Johnson, PD, Musen, MA (2002). A Typology for Modeling Processes in Clinical Guidelines and Protocols, Stanford Medical Informatics Report SMI-2002-0911
Reformulated work item • “Flowcharts” viewed as organized sets of guideline recommendations • Recommendation consists of • context: clinical setting, patient state, current therapy, provider role, triggering event • decision: encapsulate decision-making knowledge • action: computer or clinical actions • Two classes of “recommendation set” • activity graph • decision map • Common ground for various guideline models Tu, SW, Campbell, J, Musen, MA, The Structure of Guideline Recommendations: A Synthesis, AMIA 2003 Symposium
Activity graph • Used to specify processes • computational and care processes • branching and synchronization (split/join) • Directed graph of • context • decision step • action step • route: purely for branching and synchronization • Adapted from Workflow Management Coalition process model evaluate ACE as cause cough gone? cough after ACE = yes cough gone? unevaluated Cough (AND split) (AND split) presumed PNDS = yes cough gone =no treat presumed PNDS abnormal CXR? (AND join) order chest radiograph
Decision map • Used to model • If/then statements • Augmented transition network • Connected graph • One alternative allowed at decision point • Decision tree • An action is followed by a set of possible context nodes • Collection of decision points • context, decision, action nodes • differ from activity graph in the underlying computational model continue lifestyle change ?BP_controlled.eq(“true”) hypertensive no medication initiate med substitute med hypertensive w/ medication add drug increase dose
Review of past work • Proposal of using WfMC process model as basis for “flowchart” (2001-05 Minneapolis) • Visio stencil and template (2002-01 San Diego) • Review of literature (2002-05 Baltimore) • Mapping of guideline process to WfMC process and then to Petri net (2002-05 Atlanta) • Reformulation of work item as model of “recommendation set” (2002-10 Baltimore) • Partial reconciliation with HL7 RIM (2003-01 San Diego) • Incorporation into SAGE guideline model (2003-04 San Antonio)
Recommendation set in use: SAGE implementation experiment • Selection of guideline • Development of usage scenarios • Specification of guideline logic, data model, and terminology • Encoding of guideline in Protégé-2000 • Simulation of implementation in IDX clinical information system (CIS)
Selection of guideline and development of usage scenarios • Immunization guideline selected for first end-to-end experiment • Four usage scenarios • Neonatal orders for immunization immediately after birth • Primary care immunization with standard care protocol in place • Primary care immunization, physician confirmation • Population-based reminders to patients or providers
Specification of guideline logic • Interpretation and operationization of guideline recommendations • Formulation of guideline logic sensitive to scenarios guideline documents IF NO CONTRAINDICATION TO HEP B AND NO REASON FOR DEFERRAL AND NUMBER OF HEP B VACCINE DOSES = 3 AND DOSE GIVEN WITHIN 7 DAYS OF BIRTH AND 3RD DOSE GIVEN BEFORE 6 MONTHS AGE AND TIME FROM LAST DOSE IS >= 8 WEEKS AND AGE < 19 YEARS THEN ADVISE MONOVALENT HEP B VACCINE IM DUE clinical scenarios
Specification of data model • A data model constrains how data is viewed and used in computable guideline • Detailed data models correspond to constraints on vMR classes Anaphylactic reaction to influenza vaccine is a Allergy where code is vaccines allergy allergen is influenza vaccine reaction is anaphylaxis vMR classes Concepts in guideline logic
Specification of guideline terminology • Make reference to standard terminologies whenever possible • Need to define new terms ‘anaphylaxis’ = SNOMED CT:39579001 contaminated wound lesion = ‘wound lesion’ with associated morphology ‘contaminated laceration’ chronic pulmonary disease = ‘Chronic respiratory disease’ AND ‘Disease of lower respiratory system’ reference terminology concepts in guideline logic
Encoding of guideline in Protégé-2000: top-level processes • Top-level activity graphs model DSS interactions with providers through clinical information system • Highly dependent on workflow
Immunization guideline logic as decision map • A decision involve choice of assertion to make about an immunization • Due and can be given • Deferred • Contraindicated or not due • Assertion about immunizations tested at top-level activity graph
Lessons from SAGE experiment • Top-level processes model guideline DSS reactions/interactions with CIS • guideline DSS not in control of workflow • separation of workflow and medical knowledge • Decision map (coupled with a decision model) provides good cognitive correspondence with rule-like recommendations • Guideline encoding dependent on scenarios • dependence on workflow • dependence on formulation of recommendations
Limitations of SAGE experiment • Multi-level multi-choice recommendations not tested • Refinement of medication recommendations • Alternative classes of medications with individual indications and contraindications • Complex medical processes not tested • Concurrent processes that require branching and synchronization • Multi-encounter processes
Next step? • Need for RIM harmonization? • Specification for balloting? • Date for closure?