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[利用德国行政数据测量医疗结果质量]

[Measurement of medical outcome quality using administative data in Germany].

作者信息

Heller G

机构信息

Wissenschaftliches Institut der AOK, Bonn, BRD.

出版信息

Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2008 Oct;51(10):1173-82. doi: 10.1007/s00103-008-0652-0.

Abstract

While internationally low-effort reporting and quality assurance systems based on routine data for hospitals were implemented a long time ago, the evaluation of the treatment quality in hospitals according to section sign 137 SGB V in Germany still relies on special data collection, which demands considerable extra time and effort for the healthcare providers. The current article starts by addressing the question whether quality analyses using primary data sources should be preferred to analyses using secondary data analyses. Subsequently, current possibilities of measuring outcome quality, using administrative routine data, will be illustrated, referring to the large collaborative project Quality Assurance of Hospital Care with Routine Data (QSR). This project was carried out in order to examine possibilities of measuring quality based on routine administrative data in Germany from 2002-2007. The objectives of this article are to present a summary of the project's current status as well as to provide perspectives of future quality assurance with routine data in Germany. In addition, some general problems in measurement of outcome quality, the volume-prevalence problem and the problem of risk adjustment are presented, and possible solutions are proposed.

摘要

虽然国际上基于医院常规数据的低投入报告和质量保证系统早在很久以前就已实施,但在德国,根据《社会法典第五编》第137条对医院治疗质量进行评估仍依赖于特殊的数据收集,这需要医疗服务提供者投入大量额外的时间和精力。本文开篇探讨了使用原始数据源进行质量分析是否应优先于使用二手数据分析的问题。随后,将以大型合作项目“医院护理常规数据质量保证”(QSR)为例,说明利用行政常规数据衡量结果质量的当前可能性。开展该项目是为了研究2002年至2007年期间在德国基于常规行政数据衡量质量的可能性。本文的目的是概述该项目的当前状况,并提供德国未来利用常规数据进行质量保证的前景。此外,还介绍了结果质量测量中的一些常见问题、数量-患病率问题和风险调整问题,并提出了可能的解决方案。

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