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综合分析证据以完善护理路径。

Synthesizing analytic evidence to refine care pathways.

作者信息

Liu Haifeng, Li Xiang, Yu Yiqin, Mei Jing, Xie Guotong, Perer Adam, Wang Fei, Hu Jianying

机构信息

IBM Research - China.

IBM T.J. Watson Research Center, Yorktown Heights, NY, United States.

出版信息

Stud Health Technol Inform. 2015;210:70-4.

Abstract

Care pathways play significant roles in delivering evidence-based and coordinated care to patients with specific conditions. In order to put care pathways into practice, clinical institutions always need to adapt them based on local care settings so that the best local practices can be incorporated and used to develop refined pathways. However, it is knowledge-intensive and error-prone to incorporate various analytic insights from local data sets. In order to assist care pathway developers in working effectively and efficiently, we propose to automatically synthesize the analytical evidences derived from multiple analysis methods, and recommend modelling operations accordingly to derive a refined care pathway for a specific patient cohort. We validated our method by adapting a Congestive Heart Failure (CHF) Ambulatory Care Pathway for patients with additional condition of COPD through synthesizing the results of variation analysis and frequent pattern mining against patient records.

摘要

护理路径在为特定病症患者提供循证和协调护理方面发挥着重要作用。为了将护理路径付诸实践,临床机构总是需要根据当地护理环境对其进行调整,以便纳入最佳的当地实践并用于制定完善的路径。然而,整合来自本地数据集的各种分析见解既知识密集又容易出错。为了帮助护理路径开发者高效地开展工作,我们建议自动合成从多种分析方法得出的分析证据,并相应地推荐建模操作,以针对特定患者群体得出完善的护理路径。我们通过综合变异分析和频繁模式挖掘针对患者记录的结果,对慢性阻塞性肺疾病(COPD)附加病症患者的充血性心力衰竭(CHF)门诊护理路径进行调整,从而验证了我们的方法。

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