医疗保健中的效率决定因素:通过综合的正规相关性分析-数据包围分析/保证区域模型进行系统审查
1Akdeniz University, Antalya, Turkey.
概括
本研究引入了一种混合法定相关性分析 (CCA) 和数据包围分析 (DEA) 模型,以准确测量医疗保健效率. 权重关键变量大大提高了模型识别高效医疗保健系统的能力.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 运营研究 运营研究
- 计量经济学 计量经济学
背景情况:
- 准确测量医疗保健效率对于资源分配至关重要.
- 以前的研究经常使用许多变量,可能会稀释效率得分.
- 基于其影响的输入和输出权重提供了更现实的效率评估.
研究的目的:
- 提出一种新的三步混合系统,将法定相关性分析 (CCA) 和数据包围分析与保证区域 (DEA/AR) 结合起来,用于测量健康效率.
- 通过消除非影响因素并强调具有影响力的因素来完善变量选择.
主要方法:
- 对63项医疗保健效率研究 (2000-2020年) 的系统审查确定了共同的输入和输出变量.
- 规范相关性分析 (CCA) 用于先验统计分析来确定变量权重和关系.
- 使用五项变量减少程序,应用了重量受限的DEA/AR模型,确定了三个关键输入和三个输出.
主要成果:
- 该研究确定了医生和护士的数量是最有效的投入,婴儿死亡率是最有效的输出.
- 拟议的CCA-DEA/AR模型发现与基本DEA相比,健康效率较低的国家,通过可变加权证明了通过可变加权增加的歧视力.
- 在DEA分析中的权重变量显著提高了它区分高效和低效实体的能力.
结论:
- 开发的CCA-DEA/AR模型为医疗保健效率提供了更准确和更现实的评估.
- 医疗管理人员可以利用这个模型来识别资源不足和过剩,从而实现有针对性的效率提高.
- 优化资源配置,以模型的见解为指导,可以提高公共和私营部门的医疗保健产出.
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