Abstract
BackgroundEstimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill. Such estimate poses several problems due to sample selectivity problems and an under-reporting of the incidence of illness. This study examines the effects of health insurance on healthcare demand in Indonesia, using samples that are both unconditional and conditional on being ill, and comparing the results.MethodsThe demand for outpatient care in three alternative providers was modeled using a multinomial logit regression for samples unconditional on being ill (N = 16485) and conditional on being ill (N = 5055). The ill sample was constructed from two measures of health status – activity of daily living impairments and severity of illness – derived from the second round of panel data from the Indonesian Family Life Survey. The recycling prediction method was used to predict the distribution of utilization rates based on having health insurance and income status, while holding all other variables constant.ResultsBoth unconditional and conditional estimates yield similar results in terms of the direction of the most covariates. The magnitude effects of insurance on healthcare demand are about 7.5% (public providers) and 20% (private providers) higher for unconditional estimates than for conditional ones. Further, exogenous variables in the former estimates explain a higher variation of the model than that in the latter ones. Findings confirm that health insurance has a positive impact on the demand for healthcare, with the highest effect found among the lowest income group.ConclusionConditional estimates do not suffer from statistical selection bias. Such estimates produce smaller demand effects for health insurance than unconditional ones do. Whether to rely on conditional or unconditional demand estimates depends on the purpose of study in question. Findings also demonstrate that health insurance programs significantly improve access to healthcare services, supporting the development of national health insurance programs to address under-utilization of formal healthcare in Indonesia.
Highlights
Estimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill
The multinomial logit (MNL) estimates show that the coefficient estimate for Asuransi Kesehatan (Askes) insurance was positive for public and private providers, but only significant for the former with a p-value at the 1% level
Based upon unconditional and conditional MNL estimations, I predicted the probabilities of using outpatient care by changing only the health insurance status while holding all other variables at their mean
Summary
Estimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill. Such estimate poses several problems due to sample selectivity problems and an under-reporting of the incidence of illness. This study examines the effects of health insurance on healthcare demand in Indonesia, using samples that are both unconditional and conditional on being ill, and comparing the results. Several published studies on healthcare demand estimate the probabilities of using healthcare services conditional on being ill sample [1,2,3,4]. Estimations of healthcare demand, often rely on estimating these marginal and conditional probabilities. Estimating healthcare demand conditional on the event of illness poses several problems. The total effects of prices on the demand can be inferred only from unconditionalestimation [8] and such estimations would produce long-run price effects [6]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
