1. Guideline interaction scenarios  At the point of care Physicians apply marked-up guidelines, thus they Need to find an appropriate guideline in “ real time ” Require automated assistance in application of the guideline Are a large group of users Don ’ t have time to learn advanced features  At guideline-design time  Expert physicians mark-up guidelines, thus they Upload the guideline textual source Classify guidelines and mark-up their content Have to understand underlying semantics of the guideline representation. Are a relatively small group in each clinical domain Can use advanced mark-up tools Work off line  Knowledge engineers formalize the marked-up guidelines Have to know the syntax of the guideline representation. Use formal-specification graphical tools

2. DeGeL: a guideline ’ s lifecycle Medical Expert Physician at the point of care Knowledge Engineer Textual guideline source Classified and Marked-up guideline Formally represented guideline Applications (e.g., Gl Interpreter)

10. QualiGuide: Guideline-based Quality Assessment  Quality Assessment (QA) leads to Quality Improvement  There is a need for intelligent, retrospective assessment of clinicians ’ actions in the light of guideline recommendations

11. Intelligent QA: The Challenges The need to analyze the vast amounts of information available in modern clinical databases Guidelines can not specify in detail each real-life clinical scenario; there are potentially several legitimate ways to achieve the objectives of the guideline

12. Intelligent QA: The Solution  Compare the care-provider ’ s actions not only to the actions specified by the guideline, but also to the spirit of the guideline, formally represented as a set of intentions  Explain lack of adherence to specified actions using knowledge of Domain-independent strategies for guideline revision (e.g., substitution by an equivalent-effect action) Domain-specific effects of clinical actions (e.g., drug administration)

13. Representation of Intentions  The Asbru guideline specification language supports formal representation of intentions: Process intentions  Intermediate (e.g., monitor blood glucose every day)  Overall (e.g., patient had visited dietitian regularly once a week, for at least three weeks within each month) Outcome intentions  Intermediate (e.g., patient weight gain levels maintained slightly low to slightly high during application)  Overall (e.g., during the guideline, the patient had up to three episodes of hypoglycemia)

14. GOAL The goal of prevention and management of hypertension is to reduce morbidity and mortality by the least intrusive means possible. This may be accomplished by achieving and maintaining SBP below 140 mm Hg and DBP 90 mm Hg and lower if tolerated while controlling other modifiable risk factors for cardiovascular disease. Treatment to lower levels may be useful, particularly to prevent stroke, to preserve renal and to prevent or slow heart function failure progression The goal may be achieved by lifestyle modification, alone or with pharmacologic treatment. An Intention Example Goal Statement from Joint National Committee Guideline on the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.

15. Intelligent QA: the data access solution  Use of the IDAN Temporal-Abstraction mediator Access to clinical databases Response to complex temporal abstraction queries (e.g., “ Is this the third episode of severe anemia during the past year? ” )

16. QualiGuide : General architecture