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

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)

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

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

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)

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)

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 ExampleGoal Statement from Joint National Committee

Guideline on the Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.

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?”)

QualiGuide: General architecture

TemporalAbstraction

KB

PatientsCDR

GuidelineKB

Retrieve guidelines

to be applied

Intelligent patient’sdata queries

Qualiguide

Idanserver

Semi-structuredguideline

Fully-structuredguideline

DeGeLserver