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. 2024 May 1;24(1):561.
doi: 10.1186/s12913-024-10940-1.

Hospital performance evaluation indicators: a scoping review

Shirin Alsadat Hadian  1 , Reza Rezayatmand  2 , Nasrin Shaarbafchizadeh  3 , Saeedeh Ketabi  4 , Ahmad Reza Pourghaderi  5
Affiliations

Hospital performance evaluation indicators: a scoping review

Shirin Alsadat Hadian et al. BMC Health Serv Res. .

Abstract

Background: Hospitals are the biggest consumers of health system budgets and hence measuring hospital performance by quantitative or qualitative accessible and reliable indicators is crucial. This review aimed to categorize and present a set of indicators for evaluating overall hospital performance.

Methods: We conducted a literature search across three databases, i.e., PubMed, Scopus, and Web of Science, using possible keyword combinations. We included studies that explored hospital performance evaluation indicators from different dimensions.

Results: We included 91 English language studies published in the past 10 years. In total, 1161 indicators were extracted from the included studies. We classified the extracted indicators into 3 categories, 14 subcategories, 21 performance dimensions, and 110 main indicators. Finally, we presented a comprehensive set of indicators with regard to different performance dimensions and classified them based on what they indicate in the production process, i.e., input, process, output, outcome and impact.

Conclusion: The findings provide a comprehensive set of indicators at different levels that can be used for hospital performance evaluation. Future studies can be conducted to validate and apply these indicators in different contexts. It seems that, depending on the specific conditions of each country, an appropriate set of indicators can be selected from this comprehensive list of indicators for use in the performance evaluation of hospitals in different settings.

Keywords: Hospital; Indicators; Performance evaluation.

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Conflict of interest statement

The authors declare no competing interests.

Figures

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Fig. 1
Study selection and data abstraction
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