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IntroductionKey performance indicators are essential navigation tools for hospitals. They provide managers with valid information enabling them to identify institutional strengths and weaknesses and improve managerial performance. In this study, the synthesis of evidence relating to hospital performance indicators was carried out by means of a field review and the indicators were analyzed through the Best Fit Method.MethodsThe five-step approach of Arksey and O’Malley was used as follows: selection of the research question; search for related studies; selection and refinement of the studies; synthesis and tabulation of key information; derivation of the related summary and report. Applying the Best Fit Framework Synthesis Method, the initial themes and subthemes were created and a model of public hospitals performance evaluation finally generated.ResultsForty-nine studies were considered eligible to form part of the synthesis. The final model included the efficiency/productivity, effectiveness and financial themes. The efficiency/productivity sub-themes incorporated human resources indicators, hospital beds, costs, operating room productivity, emergency rooms, ICU, radiology, labs, technology and equipment productivity. Other sub-themes relate to general indicators such as BOR, ALS, number of outpatients and hospitalized patients. Financial themes included profit, revenue, cash flow, cost, investment, assets, debt and liquidity. Concerning effectiveness, the indicators were categorized in terms of access (equity), safety, quality and responsiveness. The accountability indicators were classified into patient-centeredness, staff orientation, and social responsibility.ConclusionHospital performance management is a multi-dimensional issue, each dimension having its own significance. Based on the evidence, indicators are dependent on the evaluation model employed, the evaluation objective, and the views of executive managers and participants in the study. Selection of the most appropriate indicators is therefore key to a comprehensive performance evaluation system.

BackgroundSufficient and sustainable financing of the health system is essential for improving the health of the community. The health systems financing of the EMR countries is facing the challenge. Assessment and ranking of healthcare financing can help identify and resolve some challenges of health systems. So, the aim of this study is to evaluate and rank the condition of the health sector financing in the EMR countries.MethodsThis study was a cross-sectional study. The data was of secondary type, extracted from the official WHO and World Bank data. The six healthcare financing indicators in a 10-year interval (2005–2014) in 19 EMR countries analyzed using Grey Relation Analysis and Shannon Entropy.ResultsOn average, the countries in the EMR region spent 4.87% of their GDP on the health sector. Jordan and Qatar allocated the highest (8.313) and the lowest (2.293) percentages of their GDP to the health sector, respectively. The results showed That Qatar was in a better condition than other EMR countries during 2005–2014 in terms of the health system financing and earned the first rank. After that, the UAE and Kuwait were ranked second and third.ConclusionsThere is a lot of inequality among the EMR countries in terms of health financing. However, our findings confirmed that only increasing the total health expenditure in a country would not improve its financing status compared to other countries, but it also depends on financing methods.Electronic supplementary materialThe online version of this article (10.1186/s12962-018-0151-6) contains supplementary material, which is available to authorized users.

Background: The hospital is a significant part of health systems that presents a complex and vital services. Therefore, performance management of hospitals should be considered especially. BSC model is so helpful and popular for performance management. In using BSC, cause and effect relations is very important, since it helps to apply non-financial to forecast financial performance. Objectives: This study aims to analysis systematic relations between key indicators of hospital performance evaluation, identifying causal relations and prioritizing indicators. Methods: Based on the 4 perspectives described by the balanced scorecard (BSC), the evaluation indicators of hospital performance and key performance indicators (KPIs) were adopted from the related literature and selected by experts' panel, respectively. Then, the decision making trial and evaluation laboratory (DEMATEL) method was employed for the determination of the cause-and-effect relationships between the indicators, differentiation of the effective and significant factors, and construction of the strategy map to ameliorate hospital performance. Results: According to the BSC perspectives, 21 KPIs were selected for evaluation of hospital performance. The highest relationship was found between bed occupancy having the largest R + D value and other indicators, thus illustrating its fundamental role among the indicators. Clinical errors with the greatest value of R-D showed the strongest impacts on the other indicators and was thus named as the "main cause factor" among the indicators. In contrast, the percentage of patient satisfaction with the smallest R-D value was most strongly influenced by the other indicators and therefore, it was known as the "main effect factor" among the indicators. Conclusions: Assessment and improvement of the hospital performance is a complex and multi-dimensional activity. In order to have a powerful assessment system and success in improving hospital performance, instead of a single-dimension, it should be paying attention to all dimensions of performance.