Document Type : Original Article
Authors
1
Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Vienna, Austria
2
Complexity Science Hub Vienna, Vienna, Austria
3
Austrian National Public Health Institute,Vienna, Austria
4
Department for Public Health, Health Services Research and HTA, UMIT – Private University for Health Sciences, Medical Informatics and Technology, Vienna, Austria
5
IIASA, Laxenburg, Austria
6
Santa Fe Institute, Santa Fe, NM, USA
Abstract
Background
Many countries faced health workforce challenges even before the pandemic, such as impending retirements, negative population growth, or sub-optimal allocation of resources across health sectors. Current quantitative models are often of limited use, either because they require extensive individual-level data to be properly calibrated, or (in the absence of such data) because they are too simplistic to capture important demographic changes or disruptive epidemiological shocks such as the SARS-CoV-2 pandemic.
Method
We propose a population-dynamic and stock-flow-consistent approach to physician supply forecasting that is complex enough to account for dynamically changing behaviour, while requiring only publicly available time-series data for full calibration. We demonstrate the utility of this model by applying it to 21 European countries to forecast the supply of generalist and specialist physicians to 2040, and the impact of increased health care utilisation due to Covid on this supply.
Results
Compared with the workforce needed to maintain physician density at 2019 levels, we find that in many countries there is indeed a significant trend towards decreasing generalist density at the expense of increasing specialist density. The trends for specialists are exacerbated by expectations of negative population growth in many Southern and Eastern European countries. Compared to the expected demographic changes in the population and the health workforce, we expect a limited impact of Covid on these trends, even under conservative modelling assumptions. Finally, we generalise the approach to a multiprofessional, multi-regional and multi-sectoral model for Austria, where we find an additional suboptimal distribution in the supply of contracted versus non-contracted (private) physicians.
Conclusion
It is therefore vital to develop tools for decision-makers to influence the allocation and supply of doctors across specialties and sectors to address these imbalances.
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