多年来医疗保健支出的复杂相互作用:使用fsQCA在经合组织国家进行面板数据分析,具有政策影响
Shanren Nie1, Dong Liu2, Sheng Chen1
1School of Public Policy and Administration, Chongqing University, Chongqing, Chongqing, China.
PloS one
|May 21, 2025
概括
本研究使用模糊集定性比较分析 (fsQCA) 来探索2010-2022年37个经合组织国家的医疗保健支出 (HCE) 驱动因素. 它揭示了影响HCE的各种因果途径,提供了政策见解.
科学领域:
- 卫生经济学 卫生经济学
- 对比政策分析比较政策分析
- 量化社会科学 量化社会科学
背景情况:
- 医疗保健支出 (HCE) 是一个关键的全球关注.
- 了解HCE的复杂驱动因素对于有效的政策至关重要.
- 现有的研究往往缺乏对HCE决定因素的纵向比较分析.
研究的目的:
- 通过一种新的纵向方法,研究影响医疗保健支出 (HCE) 的因果结构.
- 开发和应用一个消费-供应-融资模型来分析HCE驱动因素.
- 为了比较纵向 (面板) fsQCA与横截面fsQCA用于HCE研究.
主要方法:
- 模糊集定性比较分析 (fsQCA) 应用于纵向面板数据.
- 从经济合作与发展组织 (OECD) 数据库 (2010-2022) 的数据分析.
- 包括37个经合组织国家,每个国家年被视为个案.
主要成果:
- 识别多个"因果谱"或导致不同程度HCE的因素配置.
- 证明因果模式的稳定性和一致性,随着时间的推移和跨国.
- 在不同的国家背景下观察到年度HCE关系的显著差异.
结论:
- 该研究强调了驱动HCE的因素的异质性,强调了需要具体背景的政策干预的必要性.
- 纵向fsQCA提供了一种可靠的方法,用于在面板数据中发现复杂的因果关系.
- 调查结果通过详细说明消费,提供和融资在塑造国家医疗保健支出方面的微妙相互作用,为政策管理提供信息.
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