Employment status and healthcare utilization in Indonesia: a multilevel analysis across developed and underdeveloped districts.

Abstract

Introduction: Informal workers are a priority for health equity. However, Indonesian employment laws provide limited legal social protection to informal workers, which may constrain access to health insurance. From the supply side, underdeveloped districts continue to face a shortage of higher-level health facilities that accept National Health Insurance (Jaminan Kesehatan Nasional, JKN). This study examines disparities in outpatient and inpatient treatment utilization between formal and informal workers in Indonesia, and explores how geographic context and health insurance coverage shape these utilization patterns.

Methods: Separate analyses were conducted for developed and underdeveloped districts using two-level binary logistic regression models. Individual-level data were drawn from the 2024 National Socioeconomic Survey (SUSENAS) and integrated with district-level data from the 2024 Village Data Census (PODES). The study included 97,042 working-age individuals (aged ≥15 years) with poor self-rated health status residing in 452 developed and 62 underdeveloped districts. Outpatient and inpatient treatment utilizations were specified as the outcome variables. Employment status was treated as the primary exposure, and interaction terms were included to assess the modifying role of health insurance.

Results: In underdeveloped districts, formal workers had higher outpatient utilization (adjusted odds ratio (aOR) 1.51, 95% confidence interval (CI) 1.43-1.60) and inpatient (aOR 1.08, 95%CI 0.92-1.28) utilization than informal workers. Between-district heterogeneity is large, with intraclass correlation coefficient values of 25.61% for outpatient utilization and 38.26% for inpatient utilization. For the outpatient model, the interaction between employment status and health insurance shows that the odds for insured formal workers increased by 2.05 times, uninsured formal workers increased by 1.51 times, and insured informal workers increased by 1.49 times more than uninsured informal workers. For the inpatient model, the interaction shows that the odds of insured formal workers increased by 5.81 times, uninsured formal workers increased by 1.08 times, and insured informal workers increased by 4.27 times more than uninsured informal workers. In developed districts, between-district heterogeneity shows intraclass correlation coefficient values of 10.18% for the outpatient model and 15.77% for the inpatient model. There was no statistically significant association between formal workers (aOR 1.00, 95%CI 0.99-1.00) and informal workers to outpatient utilization. For the outpatient model, the interaction shows that the odds for insured formal workers increased by 1.44 times and insured informal workers increased by 1.40 times compared to formal and informal uninsured workers. Formal workers (aOR 0.92, 95%CI 0.91-0.94) have slightly lower inpatient utilization than informal workers. For the inpatient model, the interaction term shows that the odds for insured formal workers increased by 3.04 times, uninsured formal workers decreased by 0.92 times, and insured informal workers increased by 2.92 times more than uninsured informal workers.

Conclusion: Disparities in outpatient and inpatient treatment utilization based on employment status were observed only in underdeveloped districts, with formal workers having higher utilization than informal workers. Supply-side factors masking a structural inequality trap unintentionally contribute to healthcare utilization in underdeveloped districts. Furthermore, the interaction between employment status and health insurance shows that the benefit of employment status on healthcare utilization was mediated by health insurance coverage, albeit in distinct ways in developed and underdeveloped districts. Health insurance can provide social protection, particularly to informal workers residing in underdeveloped districts, but its effectiveness is limited due to supply constraints.