Measuring the Efficiency of Tertiary Care Hospitals and Medical Colleges in Punjab, an Application of Non- Parametric Approach DEA

Asima Ihsan

Asian Journal of Economics and Empirical Research, 2017, vol. 4, issue 1, 14-24

Abstract: Efficient utilization of resources required that the healthcare units should operate at their full capacity and increase their efficiency to yields best quality healthcare services and more savings. To measure the capacity utilization of medical collages/attached teaching hospitals in Punjab, the study incorporated the Data Envelopment Analysis (DEA). This is a cross sectional study for the academic year 2015, by using the primary data collected by “Punjab Economic Research Institute (PERI)“. The main objective to address the efficiency issue in this study is to provide empirical evidence for public policy to provide for tertiary health care facilities. The results showed that 78% medical colleges in a sample data are unity, indicating that they are perfectly utilizing their resources while the remaining 22% have more close to unity, showing that they have only small capacity to increase their output within available resources. In case of teaching hospitals, there are 56% hospitals in Punjab, which are not operating at their maximum level of output indicating that they have the capacity to provide more services. While 44% are using their resources efficiently. The higher efficiency score of medical colleges/teaching hospital in provincial capital reflected the fact that Decision Making Units (DMUs) in Lahore are relatively more efficient in the management of resources. In the second stage, by using a Tobit regression, the inefficacies are regressed against various indicators of inputs and outputs. Finally, the finding of this study suggests some policy recommendation to make the medical colleges/teaching hospitals more resource effective in order to accelerate the highest efficiency scores.

Keywords: Data development analysis; Medical colleges efficiency; Hospitals efficiency; Tobit regression. (search for similar items in EconPapers)
Date: 2017
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