A constraint satisfaction approach to data-driven implementation of clinical practice guidelines
| Autor: | Craig, Kuziemsky, Dympna, O'Sullivan, Wojtek, Michalowski, Szymon, Wilk, Ken, Farion |
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| Rok vydání: | 2008 |
| Předmět: |
Subject Headings
Medical Records Systems Computerized Artificial Intelligence Practice Guidelines as Topic Information Storage and Retrieval Articles Decision Support Systems Clinical Algorithms Decision Making Computer-Assisted United States Natural Language Processing Pattern Recognition Automated |
| Zdroj: | AMIA ... Annual Symposium proceedings. AMIA Symposium. |
| ISSN: | 1942-597X |
| Popis: | Despite significant research efforts, the implementation of computerized clinical practice guidelines (CPG) in practice remains problematic for a number of reasons. In particular most guideline representation models do not deal adequately with incomplete or inconsistent clinical data. We present a constraint satisfaction approach to address such shortcomings by focusing on CPG data rather than CPG representation. We model a CPG as a set of data-driven constraints which are used to generate complete solutions for describing a patient state from incomplete clinical data, where the patient state is confirmed by the user. Inconsistent input data can be temporarily eliminated and final feasible solutions (permitted complete solutions from a CPG) can pinpoint inconsistencies in original input data alongside allowable guideline data. We demonstrate a sample implementation of the approach for a pediatric asthma CPG. |
| Databáze: | OpenAIRE |
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