Regional planning studies has a long history which made for using public resources effective and efficiently. In Turkey 89 different Public Hospital Associations (PHA) was conducted based on provincial levels for the aim of using health resources more efficiently. In this study technical efficiency of 89 different PHA in Turkey was examined by using input and output indicators and using Data Envelopment Analysis (DEA) and machine learning techniques by dividing them into two clusters in terms of similarities in input and output indicators. As a result of the study it is seen that PHA which have higher population and service density are more efficient than others. Number of inpatients is a determinator factor of efficiency which is one of the indicators of service density.
Key words: Public Hospital Associations, Productivity, Data Envelopment Analysis, Machine Learning Techniques. JEL Codes: I18, C61, C67, C53 Article Language: EnglishTurkish
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