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Healthc Inform Res > Volume 15(4); 2009 > Article
Journal of Korean Society of Medical Informatics 2009;15(4):445-453.
DOI: https://doi.org/10.4258/jksmi.2009.15.4.445    Published online December 31, 2009.
Evaluation of Knowledge Model for a Hypertension Management CDSS Using a Standard-based Knowledge Authoring Tool
Hyun Young Kim1, Ji Hyun Kim1, In Sook Cho2, Yoon Kim3,4
1R&D Center for Interoperable EHR, Korea.
2Department of Nursing, School of Medicine, Inha University, Korea.
3Department of Health Policy and Management, College of Medicine, Seoul National University, Korea.
4Institute of Health Policy and Management, Seoul National University Medical Research Center, Korea.
Correspondence:  Ji Hyun Kim,
Received: 31 August 2009
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.

Key Words: Clinical Interpretable Guideline, Knowledge Modeling, Evaluation, Hypertension Management
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