18 Research Showcase Liu, Kai, Wenting Liu, and Alex Jingwei He. “Evaluating Health Policies with Subnational Disparities: a Text-Mining Analysis of the Urban Employee Basic Medical Insurance Scheme in China.” generic policy. By using the emerging ‘text-as-data’ methodology and drawing from subnational policy documents, this study developed a novel approach to policy measurement by analyzing policy big data. This approach is applied to examine the impacts of China’s Urban Employee Basic Medical Insurance (UEBMI) on individuals’ out-of-pocket (OOP) spending. Substantial disparities are found in policy choices across prefectures when categorizing the UEBMI policy framework into benefitexpansion and cost-containment reforms. Overall, the UEBMI policies lowered enrollees’ OOP spending in prefectures that embraced both benefit-expansion and cost-containment reforms. In contrast, the policies produced ill effects on OOP spending of UEBMI enrollees and uninsured This paper studies heterogeneous effects and distinct policy choices across localities under the same T workers in prefectures that carried out only benefit-expansion or cost-containment reforms. The micro-level impacts of UEBMI enrolment on OOP spending were conditional on whether prefectural benefit expansion and cost-containment reforms were undertaken in concert. Only in prefectures that promulgated both types of reforms did UEBMI enrolment reduce OOP spending. These findings contribute to a comprehensive textmining measurement approach to locally diverse policy efforts and an integration of macro-level policy analysis and microlevel individual analysis. Contextualizing policy measurements would improve the methodological rigour of health policy evaluations. This paper concludes with implications for health policymakers in China and beyond. Health Policy and Planning 38.1 (2023): 83-96. Local policy discrepancy in the UEBMI reforms
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