Spatial analysis of production efficiency in public hospitals

The primary aim of this study is to investigate the production efficiency of public hospitals in Turkey using the Spatial Stochastic Frontier Analysis (SSFA) method. Unlike traditional methods, the SSFA method considers spatial factors and unobserved heterogeneity, offering a more comprehensive and accurate estimation of hospital efficiencies. In cases where traditional methods fall short in measuring hospital efficiencies, the SSFA method provides more realistic and inclusive interpretations by modeling spatial dependencies and heterogeneity. Accordingly, this study aims to fill a gap in the literature by examining the applicability and effectiveness of the SSFA model in the field of healthcare services. The study utilizes data from 429 public hospitals in Turkey, covering the years 2012-2014. The SSFA model is applied through econometric modeling of outpatient treatment, inpatient treatment, and surgical output indicators. Different neighborhood definitions are used to reflect spatial effects. The main findings indicate a positive and significant spatial dependency for outpatient services, suggesting that the proximity of hospitals influences their efficiency in delivering outpatient care. However, no significant spatial interaction was detected for inpatient days and weighted surgical procedures. The presence of spatial effects significantly impacts efficiency scores in outpatient services, while such effects are not observed in other services. These findings demonstrate that the SSFA method provides more realistic results in measuring hospital efficiency. The study contributes significantly to the literature while offering valuable insights for policymakers and hospital administrators. Considering spatial dependencies allows for the development of more effective strategies in the planning and allocation of healthcare resources. The pronounced spatial interactions in outpatient services underscore the importance of geographically balanced distribution of healthcare services. Future studies applying the SSFA model to larger datasets and across different years in Turkey could enhance the understanding of temporal changes and trends, thereby enriching the literature further. Analyzing data from different years would offer opportunities to assess and improve the long-term impacts of health policies, providing deeper insights into the sustainability and efficiency of healthcare services. Such studies would also make significant contributions by reviewing the effectiveness of current policies and forming a solid foundation for future planning.