Strides in Development of Medical Education

Document Type : Original Article


1 Research Center for Modelling in Health, Institute for Future Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

2 Research Center for Health Services Management, Institute for Future Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

3 Iran Healthcare Info. Observatory, Ministry of Health and Education of Iran, Tehran, Iran

4 Budget and Performance Monitoring, Ministry of Health and Education of Iran, Tehran, Iran

5 Center of Budgeting and Performance Evaluation, Ministry of Health and Education of Iran, Tehran, Iran


Background Because of resources deficiency, a well-funded budget system is very important for achieving organizational goals. Hence, providing a specific pattern for performance analysis is important to allocate funds to medical universities Objectives In this study, econometric method and linear regression estimation were used to investigate the economic behaviour of the budget allocation process. Methods Data used in the present study were panel data from medical universities obtained during an eight-year period. The explanatory variables in this model included the numbers of faculty members and students. Also, separate linear regression was estimated as a dependent variable for the levels of expenditure budget and total budget. Results Our findings showed that if budgeting is done solely based on faculty members, allocation of public budget for each faculty member is 113.7 million Tomans, and if it is performed based on students, the allocated budgets are 9.8, 2.2, and 25.9 million Tomans for each undergraduate, professional doctorate (medicine, pharmacy, and dentistry) and postgraduate student, respectively. Conclusions In general, budget allocation for university education sector had a strong relationship with faculty members and students. However, the place of budget consumption and performance quality indicators still remain unclear. The results of this study can be applied for quantitative modelling to predict and allocate budget to medical universities.


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