Heterogeneous effects of decreasing the cost-sharing for outpatient care
on health outcomes in China: A propensity score matching and causal
machine learning approach
Abstract
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: Utilizing data from the 2018
China Health and Retirement Longitudinal Study, we analyzed 2,896
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
hospitalization, while accounting for various demographic,
socioeconomic, residential, health-related behaviors, 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
hospitalization (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 behaviors 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 behaviors. It is advisable to
further increase reimbursement rates and broaden benefit packages for
outpatient care, while addressing the unequal distribution of benefits.