Estimasi Dampak Program Asuransi Kesehatan pada Jumlah Kunjungan Rawat Jalan di Indonesia

Abstract

Background and method: This research aimed to selectthe best methods to predict the effect of health insuranceprogram on the numbers of outpatient visits in Indonesia. Theanalysis was applied to the second round of the IndonesianFamily Life Survey data (IFLS2).Result: The author compares the estimation results derivedfrom 6(six) econometrics technique count data model and selectthe best alternatives based on several statistics tests. Theresults confirm that Generalized Method of Moments (GMM)estimator is best to model the number of visits to public outpatient,whilst Hurdle Negative Binomial (HNB) is superior to model thenumber of visits to private one. It is proved that the insuredhave higher probability in the number of visits for outpatientservices then uninsured (p<1%). Supplies induce demandphenomena was not detected among the insured, howeverthis behaviour was likely happen where providers competitionare relatively high.Conclusions: This study concludes that estimates of healthcare demand given insurance have been shown to depend onthe empirical specification used in the analysis. Not controllingthe existence endogeneity of insurance leads to lower theparameter estimates. This study supports a national healthinsurance policy as an instrument to increase access to formalhealth care services.Keywords: health insurance, modeling, demand for health careservice