This research assesses inequality of the accessibility of health care. There is a need for a strong social commitment to good health. Good health increases the life expectancy of society, gives human beings the capability to participate in the community and contributes to the quality of life. A healthy population will stimulate economic growth which will reduce poverty.
Accessibility is defined as availability, concerning capacity and cost, and the physical accessibility, determined by travel time. To assess the accessibility of people to health care, a model has been developed and implemented in a case study in Yogyakarta province in the heart of Java. The model is GIS-based and uses the villages, hospitals and road network as input. Using a 30-minute maximum travel time, the model optimizes the service area of the hospitals. Poor people are limited in travel budget, hospital expenses, and travel mode.
The model shows that there exists no inequality in health care accessibility due to spatial distribution of the population. However, the different limitations for poor people cause their access to be worse.
Limited facilities cause poor people to have worse access to hospitals, as they can only use their health insurance for the poor at public hospitals. For the remote villages the establishment of public private partnerships has been proposed and also their locations, to reduce the existing inequality in health care access.
Poor people have limited means to travel to the hospitals. Those that are dependent on public transport have much worse access to hospitals. Establishing new hospitals at favorable locations would be expensive, as 28 extra hospitals are needed. Instead, the introduction of high quality moving health facilities is proposed, located at optimal locations of Puskesmas facilities to cover a maximum amount of villages and residents.
Limited budget for travel costs also have major effect on health care accessibility, as was shown in the model results. Therefore a subsidy for travel expenses is recommended to be included in the free health insurance for the poor.
Finally, the poor suffer from the sub optimal distribution of the 120 Puskesmas in the province. Considering the 30-min travel time limit the coverage could be reached by less facilities at better locations, thus relocation would improve accessibility. The modeling results suggest that the government should reevaluate the locations and policy on the Puskesmas locations.