Active membership and claim pressure in Indonesia's national health insurance: An exploratory regression study of BPJS Kesehatan monitoring data - Shultonnyck Adha (Health Economics Insights Journal, 2026)
Indonesia's Jaminan Kesehatan Nasional (JKN), administered by BPJS Kesehatan, is one of the world's largest single-payer social health insurance programs and has become central to Indonesia's progress toward universal health coverage. Yet high population registration is not identical to fiscal sustainability. This study examines whether the active population coverage rate is associated with claim pressure and financial resilience in JKN during the 2023-2024 monitoring period. The analysis uses official aggregate data from Dewan Jaminan Sosial Nasional's Monthly Report Monitoring JKN as of December 31, 2024. The data set contains 11 monthly observations for which active coverage, registered participants, active participants, net Dana Jaminan Sosial (DJS) health assets, fund resilience, and the claim ratio could be extracted consistently from public reporting. Ordinary least squares regressions with heteroskedasticity-robust standard errors were estimated. Descriptive results show that active population coverage increased from 76.07% in December 2023 to 78.83% in December 2024, while the claim ratio remained above 100% in every observed month. In the simplest specification, a one percentage-point increase in active population coverage was associated with a 1.84 percentage-point lower claim ratio. This relationship became statistically non-significant after adding a monthly trend, indicating that the observed association should be interpreted as exploratory rather than causal. The findings suggest that improving active membership is necessary for revenue adequacy but insufficient on its own; health economics policy should also address utilization growth, hospital payment incentives, chronic disease management, and contribution compliance. The paper contributes a transparent regression template for further BPJS research using microdata or provincial panels.