Document Type : Research Paper
Authors
1
Department of Educational Administration and Planning, Allameh Tabataba'i University, Tehran, Iran
2
Department of Educational Sciences and Psychology, Allameh Tabatabai University of Tehran, Tehran, Iran
3
Kerman University of Medical Sciences, Department of Management, Policymaking and Health Economics, Kerman University of Medical Sciences, Kerman, Iran
4
Allameh Tabataba'i University, Department of Educational Administration and Planning, Allameh Tabataba'i University, Tehran, Iran
10.22038/mjms.2025.89011.5051
Abstract
Abstract
Introduction
The purpose of this study is to present a model for predicting the supply of the Iranian Medical Assistant Admission Test based on an analysis of physician supply in selected OECD countries.
Material and Method
A systematic search was conducted to identify projects and articles published in English between 2010 and 2024 in Scopus, Web of Science, Cochrane, PubMed Central, and OECD databases. 16 studies were selected for qualitative synthesis based on inclusion and exclusion criteria in the field of human resource planning models of health systems of selected OECD countries.
Results: The results of this study led to the identification of 18 open codes and 5 axial codes. The most frequent open codes in supply modeling include the rate of domestic graduates in medical fields by gender, age, and field, the current stock of doctors in medical specialties by gender, age, and field, the retirement rate of doctors, and the rate of doctor migration from inside the country to outside the country, respectively. The pivot codes were categorized into the main supply-based forecasting category including (physician inventory module by average working hours, physician attrition module, graduates module, physician migration module, and domestic student module).
Results
Conclusion
The model presented in this study is an evidence-based theoretical model that combines many of the factors influencing physician supply that have been addressed in models around the world with the conditions prevailing in the Iranian context. Key words
Human resource planning, Health workforce forecasting, Health service delivery, Modeling, OECD
Keywords
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