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从非结构化健康记录中提取处方状态质量指标的自动化方法。

Automatic Methods to Extract Prescription Status Quality Measures from Unstructured Health Records.

作者信息

Alba Patrick R, Patterson Olga V, Richman Joshua S, DuVall Scott L

机构信息

VA Salt Lake City Health Care System.

University of Utah, Salt Lake City, UT.

出版信息

Stud Health Technol Inform. 2019 Aug 21;264:15-19. doi: 10.3233/SHTI190174.

Abstract

Hospital systems frequently implement quality measures to quantify healthcare processes and patient outcomes. One such measure that has previously been used is the Surgical Care Improvement Project (SCIP) quality measure of perioperative beta blocker continuation, SCIP-Card-2. The SCIP-Card-2 measure requires resource-intensive medical chart abstraction, limiting its application to a small sample of eligible patients. This paper describes a natural language processing (NLP) system for automatic extraction of SCIP-Card-2 quality measures in clinical text notes.

摘要

医院系统经常实施质量指标来量化医疗过程和患者治疗结果。之前使用过的一项此类指标是围手术期β受体阻滞剂持续使用的外科护理改进项目(SCIP)质量指标,即SCIP-Card-2。SCIP-Card-2指标需要耗费大量资源的病历摘要,这限制了其在一小部分符合条件的患者中的应用。本文描述了一种用于在临床文本记录中自动提取SCIP-Card-2质量指标的自然语言处理(NLP)系统。

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