ArticleBMC health services research2024
Modelling efficiency in primary healthcare using the DEA methodology: an empirical analysis in a healthcare district.
Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Total factor productivity growth and spatial-temporal evolution of China's health system: a three-stage DEA-Malmquist approach.Frontiers in public health · 2026Article
- Study on the efficiency of health resource allocation in the western region of China-based on three-stage DEA and Tobit regression analysis.BMC health services research · 2025Article
- Article
- Evaluating hospital performance with additive DEA and MPI: the Isfahan University of Medical Science case study.BMC health services research · 2025Article
- Article
- Efficiency of Primary Health Services in the Greek Public Sector: Evidence from Bootstrapped DEA/FDH Estimators.Healthcare (Basel, Switzerland) · 2024Article
- Dynamic Linkages Between Digital Health and Healthcare Value Chains: Evidence From a 3-Stage Network DEA Model.Inquiry : a journal of medical care organization, provision and financingArticle
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Abstract
backgroundPrimary 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.
methodsTo 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.
resultsThe 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.
conclusionsDEA 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.
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