A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions
A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions
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DOI：
10.1007/s10916-017-0841-1
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发表时间：
2017-12-01
影响因子：
5.3
通讯作者：
Abidi, Samina
中科院分区：
文献类型：
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作者：
Abidi, Samina
合并症的临床管理是一项挑战，特别是在临床决策支持环境中，因为它需要安全有效地协调多种疾病特异性临床程序，以制定对患者既有效又安全的合并症治疗计划。在本文中，我们追求多个疾病的具体临床实践指南（CPG）的整合，以管理内的计算机化临床决策支持系统（CDSS）的共病。我们提出了一个CPG集成框架，称为COMET（共病本体建模与执行），体现了知识管理的方法来建模，计算和集成多个CPG产生一个共病CPG知识模型，执行后可以提供基于证据的建议，处理共病患者。COMET利用语义网技术来实现（a）CPG知识合成，以将基于纸张的CPG转换为疾病特异性临床路径（CP），其包括基于来自领域专家的输入的专门的共病管理程序;（B）CPG知识建模，以使用科摩罗CPG本体来计算疾病特异性CP;（c）通过对齐多个本体建模的CP以开发统一的共病CPG知识模型来进行CPG知识集成;以及（e）使用推理引擎的CPG知识执行，以导出用于管理具有合并症的患者的CPG介导的建议。我们提出了一个网络可访问的COMET CDSS，为家庭医生提供CPG介导的合并症决策支持，以管理房颤和慢性心力衰竭。我们提出了我们的定性和定量分析的知识内容和可用性的彗星CDSS。
Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.