Primary healthcare management efficiency conditions the functioning of specialized care and has a direct impact on the outcomes of the health system and its sustainability. The objective of this research is to develop models to evaluate the efficiency, including health outcomes, of the primary healthcare centres (PHC) of the Clínico – La Malvarrosa Health District in Valencia. To evaluate efficiency, Data Envelopment Analysis (DEA) was used with output orientation and variable returns to scale, with panel data from the years 2015 to 2019. In rates per 10,000 inhabitants, the inputs are: medical and nursing staff and pharmacy cost. The outputs are: number of consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and pharmaceutical prescription efficiency. As exogenous variables: the percentage of population over 65 years old, over 80 and case-mix. Three models were developed, all of them with the same inputs and different combinations of outputs related to: healthcare activity, outcomes, and both, in order to study the influence of the different approaches on efficiency. Each model is analysed both without exogenous variables and with each of them. The efficiency results vary depending on the model used, although certain PHCs are always on, or very close to, the efficient frontier, while others are always inefficient. When healthcare activity outputs are considered, efficiency scores improve and the number of efficient PHCs increases. However, in general, the PHC score decreases throughout the evaluated period. This decrease is more pronounced when only activity outputs are included. DEA allows the inefficiencies of PHCs to be analysed and the efficient ones are clearly distinguished from the inefficient, although different efficiency scores are obtained depending on the model used. Evaluation can be according to healthcare activity, health outcomes or both, making it necessary to identify the expected objectives of the PHCs, as the perspective of the analysis influences the results.

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.

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia. Despite the frequency of the disease, the treatment strategies for AF are inefficient. We developed a cost-effectiveness model to evaluate potential improvements in the application of cardiac ablations to treat AF. These are surgical procedures to terminate the arrhythmia and restore Sinus Rhythm. A Markov Model with a time horizon of five years was built to represent the management of patients in AF. A Montecarlo simulation was developed as a sensitivity analysis when the effectiveness increases the estimate of the potential impact of an improvement on the efficacy of cardiac ablation. The result of the analysis showed 44% of patients were untreated in any way. The base case ends up with 45% of patients having sinus rhythm restored after five years. The Montecarlo simulation estimates that in 58% of cases, the alternative of increasing ablation effectiveness by 25% would be cost-effective. If the number of performed ablations is doubled, the robustness increases to 86%. In conclusion, the model of management of AF highlights the importance of not only increasing effectiveness, but also treating more patients. Our study shows that investing in new screening technology to increase the effectiveness of ablations would be cost-effective.