Centre for Health Economics, University of York, York, UK.
Department of Economics, University of York, York, UK.
Health Econ. 2021 Sep;30(9):2144-2167. doi: 10.1002/hec.4368. Epub 2021 Jun 6.
In many low- and middle-income countries, geographical accessibility continues to be a barrier to health care utilization. In this paper, we aim to better understand the full relationship between distance to providers and utilization of maternal delivery services. We address three methodological challenges: non-linear effects between distance and utilization; unobserved heterogeneity through non-random distance "assignment"; and heterogeneous effects of distance. Linking Malawi Demographic Health Survey household data to Service Provision Assessment facility data, we consider distance as a continuous treatment variable, estimating a Dose-Response Function based on generalized propensity scores, allowing exploration of non-linearities in the effect of an increment in distance at different distance exposures. Using an instrumental variables approach, we examine the potential for unobserved differences between women residing at different distances to health facilities. Our results suggest distance significantly reduces the probability of having a facility delivery, with evidence of non-linearities in the effect. The negative relationship is shown to be particularly strong for women with poor health knowledge and lower socio-economic status, with important implications for equity. We also find evidence of potential unobserved confounding, suggesting that methods that ignore such confounding may underestimate the effect of distance on the utilization of health services.
在许多低收入和中等收入国家,地理可达性仍然是获得医疗保健的障碍。在本文中,我们旨在更好地理解提供者距离与产妇分娩服务利用之间的全部关系。我们解决了三个方法学挑战:距离与利用率之间的非线性关系;通过非随机距离“分配”来解决未观察到的异质性;以及距离的异质性影响。我们将马拉维人口与健康调查家庭数据与服务提供评估机构数据联系起来,将距离视为连续处理变量,基于广义倾向得分估计剂量反应函数,从而可以探索在不同距离暴露下距离增量的影响中的非线性关系。我们采用工具变量法,研究了居住在不同距离医疗机构的妇女之间可能存在的未观察到差异。我们的研究结果表明,距离显著降低了在医疗机构分娩的概率,并且这种效果存在非线性关系。对于健康知识水平低、社会经济地位低的妇女来说,这种负相关关系尤为强烈,这对公平性有重要影响。我们还发现了潜在的未观察到的混杂因素的证据,这表明忽略这种混杂因素的方法可能会低估距离对卫生服务利用的影响。