Forecasting the Early Impact of COVID-19 on Physician Supply in EU Countries

Document Type : Original Article

Authors

1 Institute of the Science of Complex Systems, CeDAS, Medical University of Vienna, Vienna, Austria

2 Complexity Science Hub Vienna, Vienna, Austria

3 Supply Chain Intelligence Institute Austria, Vienna, Austria

4 Division of Insurance Medicine, Karolinska Institutet, Stockholm, Sweden

5 Austrian National Public Health Institute, Vienna, Austria

6 Department for Public Health, Health Services Research and HTA, UMIT – Private University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria

7 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.
 
Methods 
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 healthcare utilisation due to COVID-19 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-19 on these trends, even under conservative modelling assumptions. Finally, we generalise the approach to a multi-professional, 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.

Keywords

Main Subjects


  1. World Health Organization (WHO). Models and Tools for Health Workforce Planning and Projections. Geneva, Switzerland: WHO; 2010.
  2. Kroezen M, Van Hoegaerden M, Batenburg R. The Joint Action on Health Workforce Planning and Forecasting: results of a European programme to improve health workforce policies. Health Policy. 2018;122(2):87-93. doi:1016/j.healthpol.2017.12.002
  3. Folland S, Goodman AC, Stano M. The Economics of Health and Health Care. Upper Saddle River, NJ: Pearson Prentice Hall; 2007.
  4. Van Greuningen M, Batenburg RS, Van der Velden LF. Ten years of health workforce planning in the Netherlands: a tentative evaluation of GP planning as an example. Hum Resour Health. 2012;10:21. doi:1186/1478-4491-10-21
  5. Silver MP, Hamilton AD, Biswas A, Warrick NI. A systematic review of physician retirement planning. Hum Resour Health. 2016;14(1):67. doi:1186/s12960-016-0166-z
  6. World Health Organization (WHO). Global Strategy on Human Resources for Health: Workforce 2030. Geneva: WHO; 2016.
  7. Lopes MA, Almeida ÁS, Almada-Lobo B. Handling healthcare workforce planning with care: where do we stand? Hum Resour Health. 2015;13:38. doi:1186/s12960-015-0028-0
  8. Chopra M, Munro S, Lavis JN, Vist G, Bennett S. Effects of policy options for human resources for health: an analysis of systematic reviews. Lancet. 2008;371(9613):668-674. doi:1016/s0140-6736(08)60305-0
  9. Organisation for Economic Co-operation and Development (OECD). The Looming Crisis in the Health Workforce: How Can OECD Countries Respond? Paris: OECD; 2008.
  10. England K, Azzopardi-Muscat N. Demographic trends and public health in Europe. Eur J Public Health. 2017;27(suppl_4):9-13. doi:1093/eurpub/ckx159
  11. Wismar M, Maier CB, Glinos IA, Dussault G, Figueras J, World Health Organization. Health professional mobility and health systems: evidence from 17 European countries. World Health Organization, Regional Office for Europe; 2011
  12. Al-Aly Z, Xie Y, Bowe B. High-dimensional characterization of post-acute sequelae of COVID-19. Nature. 2021;594(7862):259-264. doi:1038/s41586-021-03553-9
  13. Poustchi H, Darvishian M, Mohammadi Z, et al. SARS-CoV-2 antibody seroprevalence in the general population and high-risk occupational groups across 18 cities in Iran: a population-based cross-sectional study. Lancet Infect Dis. 2021;21(4):473-481. doi:1016/s1473-3099(20)30858-6
  14. Hodgson CL, Higgins AM, Bailey MJ, et al. The impact of COVID-19 critical illness on new disability, functional outcomes and return to work at 6 months: a prospective cohort study. Crit Care. 2021;25(1):382. doi:1186/s13054-021-03794-0
  15. Liu JX, Goryakin Y, Maeda A, Bruckner T, Scheffler R. Global health workforce labor market projections for 2030. Hum Resour Health. 2017;15(1):11. doi:1186/s12960-017-0187-2
  16. Rafiei S, Mohebbifar R, Hashemi F, Ranjbar Ezzatabadi M, Farzianpour F. Approaches in health human resource forecasting: a roadmap for improvement. Electron Physician. 2016;8(9):2911-2917. doi:19082/2911
  17. Roberfroid D, Leonard C, Stordeur S. Physician supply forecast: better than peering in a crystal ball? Hum Resour Health. 2009;7:10. doi:1186/1478-4491-7-10
  18. Santésuisse. Ambulante Versorgungsstruktur und Bedarfsanalyse Schweiz. Solothurn: Santésuisse; 2018.
  19. O'Brien-Pallas L, Baumann A, Donner G, Murphy GT, Lochhaas-Gerlach J, Luba M. Forecasting models for human resources in health care. J Adv Nurs. 2001;33(1):120-129. doi:1046/j.1365-2648.2001.01645.x
  20. Persaud DD, Cockerill R, Pink G, Trope G. Determining Ontario's supply and requirements for ophthalmologists in 2000 and 2005: 1. Methods. Can J Ophthalmol. 1999;34(2):74-81.
  21. van Greuningen M. Health Workforce Planning in the Netherlands. Utrecht: Nivel; 2016.
  22. Willis G, Cave S, Kunc M. Strategic workforce planning in healthcare: a multi-methodology approach. Eur J Oper Res. 2018;267(1):250-263. doi:1016/j.ejor.2017.11.008
  23. Kovacs E, Girasek E, Eke E, Szocsk M. Strengthening data for planning a sustainable health workforce: what data to collect for health workforce development and why. Public Health Panor. 2017;3(3):497-504.
  24. IHS Markit Ltd. The Complexities of Physician Supply and Demand: Projections from 2019 to 2034. Washington, DC: Association of American Medical Colleges (AAMC); 2021.
  25. Hofbauer J, Sigmund K. Evolutionary Games and Population Dynamics. Cambridge: Cambridge University Press; 1998.
  26. May RM. Stability and Complexity in Model Ecosystems. Princeton: Princeton University Press; 2019.
  27. Thurner S, Hanel R, Klimek P. Introduction to the Theory of Complex Systems. Oxford: Oxford University Press; 2018.
  28. Mathieu E, Ritchie H, Rodés-Guirao L, et al. Coronavirus Pandemic (COVID-19). Our World in Data; 2020. https://ourworldindata.org/coronavirus. Accessed May 2023.
  29. Our World in Data. Population (Historical Estimates). Our World in Data. https://ourworldindata.org/grapher/population. Accessed May 2023.
  30. Antonelli M, Pujol JC, Spector TD, Ourselin S, Steves CJ. Risk of long COVID associated with delta versus omicron variants of SARS-CoV-2. Lancet. 2022;399(10343):2263-2264. doi:1016/s0140-6736(22)00941-2
  31. Ayers JW, Poliak A, Dredze M, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. 2023;183(6):589-596. doi:1001/jamainternmed.2023.1838
  32. OECD, European Observatory on Health Systems and Policies. Bulgaria: Country Health Profile 2017, State of Health in the EU. Paris: OECD Publishing; 2017. doi:1787/9789264283305-en
  33. OECD, European Observatory on Health Systems and Policies. Romania: Country Health Profile 2017, State of Health in the EU. Paris: OECD Publishing; 2017. doi:1787/9789264283534-en
  34. OECD, European Observatory on Health Systems and Policies. Slovenia: Country Health Profile 2017, State of Health in the EU. Paris: OECD Publishing; 2017. doi:1787/9789264283558-en
  35. Omerzu M. Health-workforce projection. In: 11th European Public Health Conference; 2018; Ljubljana.
  36. Stordeur S, Léonard C. Challenges in physician supply planning: the case of Belgium. Hum Resour Health. 2010;8:28. doi:1186/1478-4491-8-28
  37. van Steenbergen E, Spijkerman C. Eindelijk Arts, Heb Je Geen Werk. NRC; 2014.
  38. OECD, European Observatory on Health Systems and Policies. Austria: Country Health Profile 2017, State of Health in the EU. Paris: OECD Publishing; 2017. doi:1787/9789264283268-en

Articles in Press, Corrected Proof
Available Online from 27 February 2024
  • Receive Date: 08 September 2022
  • Revise Date: 22 August 2023
  • Accept Date: 24 February 2024
  • First Publish Date: 27 February 2024