Abstract

Increased number of Oral and Dental Health Centers (ODHC) constracted underthe Health Transformation Program (HTP) in Turkey meets an important healthcare service requirement (Islıcık & Yar, 2018). to Evenly distribution of these dental services all over the country facilitates the public access and allows these services to gain continuity. Accesibility to sufficiently distributed dental service centers increases citizens physical and also mental well-beings , which is the therapeutic aspect of providening such public helth servises. Services social contribution is uncountable in terms of health issues for the people of the country. On the other hend they need quite amount og finantial support. Therefore, autorities in the country, especially healt service autority shoult consider running a financial performance analysis plan. In ODHC system, dentists are the main component for keeping the system running to provide an uninterrapted, continues and regular dental health services. For this reason, in the study, financial performance analyzes of existing ODHCs w.r.t the profitability per dentist were carried out by the help of Geographical Information Systems (GIS). Inverse Distance Weighting-IDW analyse technique provided by GIS is used to creat several performans distribution maps were produced w.r.t the several factors per dentist which are effective on the financial performans of ODHCs. For the seak of understandability, two most effective factors and the profitability as target factor are assigned to three primary colors for an effective visial interpretation of the relationship between the these most effective factors in terms of profitability per dentest in GIS enviroment. When the outputs are evaluated, a more understandable results on the relationship between the factors effecting the ODHCs’ financial performance are obtained by this visualiation techniqu for128 public ODHCs in Turkey, and the importance levels of the variables are then revealed in terms of ODHCs financial performances w.r.t. the locational data.

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