Introduction:
This study aims to develop a demand forecasting model for the admission of specialized medical assistants in Iran, grounded in the analysis of healthcare workforce planning in selected OECD countries
Method:
Due to the multidisciplinary and multidimensional nature of the existing literature, this study employed the seven-step meta-synthesis method of Sandelowski and Barroso. A systematic search was conducted to identify projects and articles published in English between 2010 and 2024 in the Scopus, Web of Science, Cochrane, PubMed Central, and OECD databases. Fifteen studies were selected for qualitative synthesis based on inclusion and exclusion criteria in the field of human resource planning models for health systems in selected OECD countries.
Results:
The results of this study led to the identification of 21 open codes and 5 axial codes. The most frequent open codes in demand modeling were respectively the age structure of the population and the future population growth rate. The axial codes in the main category of demand-based forecasting were classified into the following concepts: demographic transition, epidemiological transition, health expenditures and economic growth, universal health insurance coverage, and utilization of medical services.
Conclusion:
The model presented in this study is an evidence-based theoretical model that integrates many of the effective components in physician demand, which have been addressed in models worldwide, with the conditions prevailing in the context of Iran. This allows the model to be used for many different health professions, especially in the clinical field.