Hospital performance evaluation models: A scoping review

Abstract

Evaluating the performance of hospitals, the largest budget consumers of the health system, is challenging. This scoping review aimed to identify and classify hospital performance evaluation models and their dimensions. A literature search was conducted across three databases using keyword combinations. The studies included performance evaluation models along with evaluation of efficiency, effectiveness, and efficiency related to the hospital. Eighty English language studies published between 2012 and 2022, the majority from Iran, USA, Brazil, and China, were included. The extracted models were classified into two categories: quantitative and qualitative. The quantitative models were divided into two main groups: 'parametric' and 'non-parametric'. Parametric models were divided into four methods: regression models, stochastic frontier analysis, neural network models, and factor analysis. Non-parametric models can be classified into five groups: data envelopment analysis (DEA) models, multi-criteria decision-making methods, performance management models, service quality models, and other models. The DEA model, which includes extensive functions, was the most common model used for evaluating hospital performance. Quantitative models for evaluating hospital performance focused on performance and efficiency terms. A key priority for future research is to compare the extracted models with real data from different hospitals and provide the most useful model according to the contextual factors of the hospital.