Health production and determinants of health systems performance in WHO Eastern Mediterranean Region

This descriptive-analytical study used data envelopment analysis to evaluated the technical efficiency [TE] of health systems in Member States of the World Health Organization Eastern Mediterranean Region during 2004-2011. Life expectancy and infant mortality were used as outputs. Per capita total expenditure on health, and number of physicians, nurses and midwives and hospital beds per 1000 people were used as inputs. The determinants of TE of the health systems were examined using a regression model. United Arab Emirates and Somalia had the most efficient health systems with a TE score of 1. Djibouti and Libya had the most inefficient health systems, with TE scores of 0.346 and 0.435, respectively. The most important determinants of TE were the level of education and gross domestic product per capita. The relationship between unemployment and out-of-pocket health expenditure was not significantly associated with TE of the health systems. To improve TE of the health systems, countries should focus on individuals' empowerment in education and income level, rather than only on providing healthcare services

[Cost analysis of hemodialysis in Iran: cost of hemodialysis in referring patients to Bu Ali Sina hospital of Qazvin University Of Medical Sciences, 2008-2009]

Objective [s]: The purpose of this study was to assess the health service cost of hemodialysis delivered at. Bu Ali Sina hospital in 2008-2009

Methods: This cross-sectional study was conducted in 2008-2009.hemodialysis service costs were categorized in three groups: direct [overhead] costs, indirect costs and capital costs.our community research was consist of all referring patients to hemodialysis department in 2008-2009. Needed data was collected with standard costing information sheets and cost per session of hemodialysis service for EM and chronic patients was calculated

Results: The cost per hemodialysis session for EM and chronic patients was calculated as 462466 RLs and 781986 RLs respectively. Direct costs, indirect costs and capital costs contributed to 89.21%, 5.16 % and 5.37 of the total cost respectively fixed and variable costs related to hemodialysis was 10.53% and 89.21% of total cost. Nonoptimal financial variance per session for EM and chronic patients was 12966 RLs and 15916 RLs respectively

Conclusion: Th findings are important to financial and human resources allocation for hemodialysis services provision in hospitals. Use of economic analyses for hemodialysis services provision and for designing and development of programs is recommended