Health System Efficiency: A Fragmented Picture Based on OECD Data

卫生系统效率:基于经合组织数据的碎片化图景

阅读:1

Abstract

BACKGROUND: Globally, health expenditure as a percentage of GDP has increased in recent years, so evaluating the health care systems used in different countries is an important tool for identifying best practices and improving inefficient health care systems. OBJECTIVE: We investigate health system efficiency at the country level based on OECD health data. We focus on several aspects of health care systems to identify specific inefficiencies within them. This information hints at potential policy interventions that could improve specific parts of a country's health care system. METHODS: A discussion is provided of ideal-typical evaluations of health systems, ignoring data restrictions, which provide the theoretical basis for an analysis performed under factual data restrictions. This investigation includes health care systems in 34 countries and is based on OECD health data. Health care system efficiency scores are obtained using data envelopment analysis (DEA). Relative productivity measures are calculated based on average DEA prices. Given the severe data limitations involved, instead of performing an all-encompassing analysis of each health care system, we focus on several aspects of each system, performing five partial analyses. RESULTS: For each country, the efficiencies yielded by the five partial analyses varied considerably, resulting in an ambiguous picture of the efficiencies of the various health care systems considered. A synopsis providing comprehensive rankings of the analyzed countries is provided. CONCLUSION: Analysis of several aspects of the health care systems considered here highlights potential improvements in specific areas of these systems, thereby providing information for policymakers on where to focus when aiming to improve a country's health care system.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。