Data Envelopment Analysis Applications on Primary Health Care Using Exogenous Variables and Health Outcomes

A data envelopment analysis was used to evaluate the efficiency of 18 primary healthcare centres in a health district of the Valencian Community, Spain. Factor analysis was used as a first step in order to identify the most explanatory variables to be incorporated in the models. Included as variable inputs were the ratios of general practitioners, nurses, and costs; as output variables, those included were consultations, emergencies, avoidable hospitalisations, and prescription efficiency; as exogenous variables, those included were the percentage of population over 65 and a multimorbidity index. Confidence intervals were calculated using bootstrapping to correct possible biases. Efficient organisations within the set were identified, although the results depend on the models used and the introduction of exogenous variables. Pharmaceutical expenditure showed the greatest slack and room for improvement in its management. Data envelopment analysis allows an evaluation of efficiency that is focussed on achieving better results and a proper distribution and use of healthcare resources, although it needs the desired goals of the healthcare managers to be clearly identified, as the perspective of the analysis influences the results, as does including variables that measure the achievements and outcomes of the healthcare services.