Dossier n. 239/2014 [Abstract] Health workforce: towards a forecasting model for Emilia-Romagna

Italian regional health authorities negotiate annually the number of residency grants to be financed by the National government and the number and mix of supplementary grants to be funded by the regional budget. This study provides regional decision-makers with a requirement-model to forecast future demand of specialists at regional level. We carried out a literature review on forecasting models (supply, requirement and needs-based) outlining their key assumptions and limitations. Subsequently we presented an in depth analysis of available databases at regional level to understand the medical labor force market. However, the core of this Dossier is a System dynamics model which projects the evolution of the supply of medical specialists and three demand scenarios across the planning horizon (2030). Demand scenarios account for different drivers: demography, service utilization rates (ambulatory care and hospital discharges) and hospital beds. Based on the System Dynamics outputs (occupational and training gaps), an allocation model computes potentially effective assignments of medical specialty grants for each year of the projection. When simulating the allocation of grants we compare how regional and national grants can be managed in order to reduce future gaps with respect to current training patterns. The allocation of supplementary grants to close expected occupational gaps appears not as effective as the re-modulation of the overall medical regional training system according to projected needs.

The model presented is the result of a virtuous research and planning circle began by the Regional agency for health and social care in cooperation with the Regional health department of Emilia-Romagna and a multidisciplinary expert group. The ‘extended’ expert group played a major role providing strategic and methodological insights at different stages of the research. Even though its intrinsic limitations, mainly due to data availability issues, the model presented is not only a quantitative assessment based on explicit assumptions regarding the future of medical workforce in Emilia-Romagna, but most noticeably it showed to be a useful tool to discuss regional training policies.

As research team we hope that the publication of this research will represent the beginning of its analytical review and continuous improvement.