数据包裹分析的可视化在初级卫生服务中的数据包裹分析
Ane Elixabete Ripoll-Zarraga1, José Luis Franco Miguel2, Carmen Fullana Belda2
1Department of Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. ane.ripoll-zarraga@uab.cat.
Health care management science
|May 2, 2025
概括
初级医疗保健中心可以通过减少特定药物处方和优化患者分配来提高效率. 专注于预防护理的中心表现出更好的成本效益,特别是在管理处方费用方面.
科学领域:
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
- 计量经济学 计量经济学
背景情况:
- 传统的公共卫生效率分析往往忽视了初级保健提供者.
- 数据包围分析 (DEA) 是评估决策单位 (DMU) 效率的常用方法,但在区分单位和处理异常值方面存在局限性.
- 现有的DEA增强,如超效率和交叉效率,可能会排除极端情况,忽视专业化.
研究的目的:
- 引入和应用DEA可视化来分析公共初级卫生中心的效率.
- 在为老年人服务的中心中识别低效的来源和专业化的模式.
- 为改善初级医疗保健的资源配置和成本效益提供见解.
主要方法:
- 利用了DEA可视化,将DEA与多变量统计方法集成在一起.
- 分析了2018年马德里82家公共初级卫生中心为老年人提供服务的数据.
- 识别了低效率来源,专业化模式和极端情况,但没有消除异常值.
主要成果:
- 确定了效率低下,包括对特定药物的偏好,而不是通用药物的处方,这有助于增加成本.
- 发现了两个异常中心,基础设施成本高,人员不成比例.
- 发现强调预防护理的中心更具成本效益,特别是在降低处方费用方面.
结论:
- DEA可视化提供了一种强大的方法来识别医疗保健机构的低效率和专业化.
- 优化药物处方和重新分配患者等策略可以提高初级保健效率.
- 专注于预防护理模式可以节省大量成本,特别是在药品支出方面.
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