Heterogeneous Effects of Decreasing the Cost‐Sharing for Outpatient Care on Health Outcomes in China: A Propensity Score Matching and Causal Machine Learning Approach.

Background: To improve accessibility and financial support for outpatient services, China introduced a scheme to decrease cost‐sharing for outpatient care under the Urban Employee Basic Medical Insurance. This study evaluates the health impacts of this policy and examines its heterogeneous effects. Methods: Utilising data from the 2018 China Health and Retirement Longitudinal Study, we analysed 2896 individual‐level observations across 105 prefectures. Propensity score matching and a causal forest model were applied to evaluate the effects on chronic disease status, body pain, self‐rated health, and hospitalisation, while accounting for various demographic, socioeconomic, residential, health‐related behaviours, and prefecture‐specific factors. Results: The reduction in cost‐sharing was significantly linked to decreased probabilities of chronic disease (Average Treatment Effect (ATE) = −0.0619, p < 0.01), body pain (ATE = −0.0715, p < 0.05), and hospitalisation (ATE = −0.0592, p < 0.001), as well as improved self‐rated health (ATE = 0.1557, p < 0.001). These benefits may be attributed to reduced out‐of‐pocket payments for outpatient care (ATE = −287.6112, p < 0.01) and increased outpatient visits (ATE = 0.0414 visits, p < 0.05). Causal forest analyses revealed that older individuals, those with higher educational attainment, higher household income, urban residents, and those engaging in healthier behaviours exhibited larger treatment effects. Conclusions: Decreasing outpatient cost‐sharing in China has beneficial health outcomes, with variations in its impact based on socio‐economic status and health behaviours. It is advisable to further increase reimbursement rates and broaden benefit packages for outpatient care, while addressing the unequal distribution of benefits. [ABSTRACT FROM AUTHOR]