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A parameter-free population-dynamical approach to health workforce supply forecasting of EU countries

Many countries face challenges like impending retirement waves, negative population growth, or a suboptimal distribution of resources across medical sectors and fields in supplying their healthcare systems with adequate staffing. An increasing number of countries therefore employs quantitative approaches in health workforce supply forecasting. However, these models are often of limited usability as they either require extensive individual-level data or become too simplistic to capture key demographic or epidemiological factors.

We propose a novel population-dynamical and stock-flow-consistent approach to health workforce supply forecasting complex enough to address dynamically changing behaviors while requiring only publicly available timeseries data for complete calibration.

We apply the model to 21 European countries to forecast the supply of generalist and specialist physicians until 2040. Compared to staffing levels required to keep the physician density constant at 2016 levels, in many countries we find a significant trend toward decreasing density for generalist physicians at the expense of increasing densities for specialists. These trends are exacerbated in many Southern and Eastern European countries by expectations of negative population growth.

For the example of Austria we generalize our approach to a multi-professional, multi-regional and multi-sectoral model and find a suboptimal distribution in the supply of contracted versus non-contracted physicians. It is of the utmost importance to devise tools for decision makers to influence the allocation and supply of physicians across fields and sectors to combat imbalances.

P. Klimek, M. Gyimesi, H. Ostermann, S. Thurner, A parameter-free population-dynamical approach to health workforce supply forecasting of EU countries, European Journal of Public Health 30 (2020) ckaa165.527.

Peter Klimek, Faculty member at the Complexity Science Hub

Peter Klimek

Stefan Thurner @ Franziska Liehl, President of the Complexity Science Hub

Stefan Thurner

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