표준 기반의 지식저작 환경을 이용한 고혈압 관리 의사결정지원시스템 지식 모델 평가
Evaluation of Knowledge Model for a Hypertension Management CDSS Using a Standard-based Knowledge Authoring Tool
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Objective: For the development of interoperable and sharable knowledge-based clinical decision support systems, it is important to evaluate the appropriateness of knowledge in each phase. In this study, an evaluation of early phase's knowledge model for hypertension management was conducted to develop a more precise and useful knowledge model. Methods: The knowledge model for hypertension management based on JNC7 was modeled using a knowledge representation tool based on SAGE. Two physicians were involved in evaluating the process of the knowledge model. They reviewed 36 scenarios and made recommendations based on the knowledge model. These recommendations were compared with those derived from the model. Results: Eight algorithms and 223 evidence statements were included in the knowledge model. The concordance rate of the recommendations between the physicians and the model for the goal BP were 61% and 93% by the respective physicians. Six scenarios showed low proficiency and efficiency for drug recommendation. Two refinements of the knowledge model were made based on the results. Conclusion: The evaluation process of the knowledge model in the early phase provides more precise and useful knowledge model in the next.
Abstract
Objective: For the development of interoperable and sharable knowledge-based clinical decision support systems, it is important to evaluate the appropriateness of knowledge in each phase. In this study, an evaluation of early phase's knowledge model for hypertension management was conducted to develop a more precise and useful knowledge model. Methods: The knowledge model for hypertension management based on JNC7 was modeled using a knowledge representation tool based on SAGE. Two physicians were involved in evaluating the process of the knowledge model. They reviewed 36 scenarios and made recommendations based on the knowledge model. These recommendations were compared with those derived from the model. Results: Eight algorithms and 223 evidence statements were included in the knowledge model. The concordance rate of the recommendations between the physicians and the model for the goal BP were 61% and 93% by the respective physicians. Six scenarios showed low proficiency and efficiency for drug recommendation. Two refinements of the knowledge model were made based on the results. Conclusion: The evaluation process of the knowledge model in the early phase provides more precise and useful knowledge model in the next.
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