Sager N, Lyman M, Tick L J, Nhàn N T, Bucknall C E
Courant Institute of Mathematical Sciences, New York University, NY 10012.
Proc Annu Symp Comput Appl Med Care. 1993:265-8.
A technique for monitoring healthcare via the processing of routinely collected narrative documentation is presented. A checklist of important details of asthma management in use in the Glasgow Royal Infirmary (GRI) was translated into SQL queries and applied to a database of 59 GRI discharge summaries analyzed by the New York University Linguistic String Project medical language processor. Tables of retrieved information obtained for each query were compared with the text of the original documents by physician reviewers. Categories (unit = document) were: (1) information present, retrieved correctly; (2) information not present; (3) information present, retrieved with minor or major error; (4) information present, retrieved with minor or major omissions. Category 2 (physician "documentation score") could be used to prioritize manual review and guide feedback to physicians to improve documentation. The semantic structuring and relative completeness of retrieved data suggest their potential use as input to further quality assurance procedures.
本文介绍了一种通过处理常规收集的叙述性文档来监测医疗保健的技术。格拉斯哥皇家医院（GRI）使用的哮喘管理重要细节清单被翻译成SQL查询，并应用于纽约大学语言字符串项目医学语言处理器分析的59份GRI出院小结数据库。医生评审人员将每个查询获得的检索信息表与原始文档的文本进行比较。类别（单位=文档）包括：（1）信息存在且检索正确；（2）信息不存在；（3）信息存在，但检索存在小错误或大错误；（4）信息存在，但检索存在小遗漏或大遗漏。第2类（医生“文档评分”）可用于确定人工审核的优先级，并指导向医生提供反馈以改进文档。检索数据的语义结构和相对完整性表明它们有可能用作进一步质量保证程序的输入。
