Measuring the Efficiency of Public Hospitals in Saudi Arabia Using the Data Envelopment Analysis Approach

Abstract

This purpose of this paper is to measure technical and scale efficiencies of public hospitals in 20 regions in Saudi Arabia. Furthermore, these estimates and the slack-based forecasting and the sensitivity analysis of the stability of efficiency scores were calculated. The researcher used Data Envelopment Analysis (DEA) technique based on two models - CCR and BCC, with an input-oriented approach. The Ministry of Health in Saudi Arabia published the Health Statistical Year Book for the years, 2010, 2011, 2013, 2014 and 2015 from which the data were obtained. The variables chosen included the number of beds, staff nurses and doctors as inputs, and outpatients, inpatients and surgeries representing outputs. Results indicate that the BCC model tends to classify more regions as efficient. The average PTE score of inefficient hospitals was 88 percent over the period in question, which implies that inputs could be reduced by 12 per cent without it impacting in any way on the service provided. Hospital managers and policy makers will thus play a critical role in ensuring that resources are utilised to their full potential in order to optimise efficiency. The inefficient regions could make their hospitals efficient by following the efficient regions as peers. Finally, it was found that there is stability in the efficiency scores of hospitals as revealed by sensitivity analysis, even when taking into account the exclusion of the most efficient hospitals.