In the last decades, there has been a growing interest in measuring the efficiency of hospitals using different methodological approaches, mainly represented by data envelopment analysis (DEA) and stochastic frontier analysis (SFA). In this study, we estimate efficiency measures of performance for a sample of Panamanian public hospitals over an 11‐year period (2005–2015) using both traditional methods (DEA and SFA) and compare them with efficiencies estimated with an alternative approach, the so‐called StoNED (stochastic semi‐nonparametric envelopment of data), which combines the virtues of those methods in a unified framework. One of the most interesting features of the public health system in Panama is that it is segmented, as hospitals are operating under two parallel management schemes (the Ministry of Health and the Social Security Fund), thus in our empirical analysis we will also focus on exploring the differences between hospitals operating under each regime. Our results show that there are certain divergences in the efficiency scores estimated with different methodologies, but for all of them it is possible to detect that Panamanian hospitals experienced a clear decrease in their efficiency levels throughout the period evaluated, being this much higher in the hospitals belonging to the Social Security Fund.

In Latin American and Caribbean countries, the main concern of public health care managers has been traditionally placed on problems related to funding, payment mechanisms, and equity of access. However, more recently, there is a growing interest in improving the levels of efficiency and reducing costs in the provision of health services. In this paper we focus on measuring the technical efficiency and productivity change of public hospitals in Panama using bootstrapped Malmquist indices, which allows us to assess the statistical significance of changes in productivity, efficiency, and technology. Specifically, we are interested in comparing the performance of hospitals belonging to the two different management schemes coexisting in the country, the Social Security Fund (SSF) and the Ministry of Health (MoH). Our dataset includes data about 22 public hospitals (11 for each model) during the period between 2005 and 2015. The results showed that the productivity growth of hospitals belonging to the SSF has been much higher than that of the hospitals belonging to the Ministry of Health over the evaluated period (almost 4% compared to 1.5%, respectively). The main explanation for these divergences is the superior growth of technological change in the former hospitals, especially in the final years of the evaluated period.