Efat Mohamadi; Zhila Najafpour; Mohammad Mehdi Kiani; Morteza Mohammadzadeh; Amirhossein Takian; Alireza Olyaeemanesh
Abstract
Background: There are substantial differences in the health outcomes across countries. Then, assessment of the status of health indicators can give us a valuable information to adjust policies to improve the health status in the world. This paper examines differences and relationships of health status ...
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Background: There are substantial differences in the health outcomes across countries. Then, assessment of the status of health indicators can give us a valuable information to adjust policies to improve the health status in the world. This paper examines differences and relationships of health status and contextual factors.Methods: This is a multi-country cross-sectional study performed using secondary data of different sources in 2019. We identified indicators that revealed the relationships of health status and health coverage and also contextual factors by expert panel which consist of two categories of indicators: (1) producing health indicators as dependent variables (Life expectancy, Healthy life expectancy, Maternal mortality ratio, Under-five mortality rate and Universal Health Coverage (UHC) service coverage indicator); (2) contextual indicators as independent variables (Current Health Expenditure, Skilled health professionals density, Population density and Government Type). Also, countries were categorized based on the income level and six regions of World Health Organization (WHO). We used SPSS 20 software for a descriptive analysis and R 2018 software for statistical analysis and also drawing of scatter charts.Results: Results showed a considerable gap between the average of life expectancy (84.2 vs. 53 years) and healthy life expectancy rate (72-63.3 years). This disparity was observed in the Maternal mortality and Under-5 mortality rate (from 882 to 3 per 100000 live births), (5 is 2.1 and the highest is 127.3). Although there was a marginal correlation between population density indicator and life expectancy, healthy life expectancy, and under-5 mortality rate indicators (±0.2), there was no correlation between population density and maternal mortality rate with UHC (P>0.05).Conclusion: There is a considerable difference between countries in producing health indicators based on contextual indicators; a comprehensive health system approach that can result in improvement in the health outcome.
Efat Mohamadi; Amirhossein Takian; Alireza Olyaee Manesh; Reza Majdzadeh; Farhad Hosseinzadeh Lotfi; Hamid Sharafi; Leila Hosseini Qavam Abad; Mohammad Mehdi Kiani; Haniye Sadat Sajadi; Zahra Goodarzi; Hasan Yusefzadeh Yusefzadeh; Elham Ehsani-Chimeh; Somayeh Noori Hekmat; Hakimeh Mostafavi; Jalal Arabloo
Abstract
Background: In pursuing improving healthcare quality and enhancing efficiency, public hospitals in Iran have undergone numerous reforms over the past two decades. This study aimed to assess the efficiency of all public hospitals in Iran from 2012 to 2016.Methods: This study was conducted as a quantitative ...
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Background: In pursuing improving healthcare quality and enhancing efficiency, public hospitals in Iran have undergone numerous reforms over the past two decades. This study aimed to assess the efficiency of all public hospitals in Iran from 2012 to 2016.Methods: This study was conducted as a quantitative and descriptive-analytical research project. The authors employed an innovative approach called Extended Data Envelopment Analysis (Extended-DEA), a modification of conventional DEA, to assess the technical efficiency and productivity of 568 public hospitals. They obtained nationally representative data from official annual health reports. The data were analyzed using GAMS software version 24.3.Results: The study found that the average efficiency score for all hospitals was 0.733. Among all the hospitals, 10.1% were deemed efficient, while 2.68% had low-efficiency scores below 0.2. The Malmquist Productivity Index (MPI) showed improvement in 49.3% of hospitals and remained unchanged at 2.3%. In comparison, 48.2% of hospitals experienced a regression in productivity from 2015 to 2016. On average, the MPI was 1.07 throughout the analysis.Conclusion: The findings of this study suggest that there is a need for increased efforts to improve the efficient utilization of resources in public hospitals. It highlights the importance of developing appropriate policy solutions and tools to address these efficiency challenges. In particular, one proposed strategy is the merger of small-sized district hospitals to establish larger and more efficient hospitals in different geographical regions across the country.
