Public-private partnership (PPP) initiatives are extending around the world, especially in Europe, as an innovation to traditional public health systems, with the intention of making them more efficient. There is a varied range of PPP models with different degrees of responsibility from simple public sector contracts with the private, up to the complete privatisation of the service. As such, we may say the involvement of the private sector embraces the development, financing and provision of public infrastructures and delivery services. In this paper, one of the oldest PPP initiatives developed in Spain and transferred to other European and Latin American countries is evaluated for first time: the integrated healthcare delivery Alzira model. Through a comparison of public and PPP hospital performance, cost and quality indicators, the efficiency of the PPP experience in five hospitals is evaluated to identify the influence of private management in the results. Regarding the performance and efficiency analysis, it is seen that the PPP group obtains good results, above the average, but not always better than those directly managed. It is necessary to conduct studies with a greater number of PPP hospitals to obtain conclusive results.

In Spain, the COVID-19 pandemic has impacted the various regions of the country differently. The availability of reliable and up-to-date information has proved to be fundamental for the management of this health crisis. However, especially during the first wave of the pandemic (February–August 2020), the disparity in the recording criteria and in the timing of providing these figures to the central government created controversy and confusion regarding the real dimension of the pandemic. It is therefore necessary to have objective and homogeneous criteria at the national level to guide health managers in the correct recording and evaluation of the magnitude of the pandemic. Within this context, we propose using Benford’s Law as an auditing tool to monitor the reliability of the number of daily COVID-related deaths to identify possible deviations from the expected trend.