Health Care Management Science

, Volume 21, Issue 1, pp 52–75 | Cite as

Forecasting the medical workforce: a stochastic agent-based simulation approach

  • Mário Amorim Lopes
  • Álvaro Santos Almeida
  • Bernardo Almada-Lobo


Starting in the 50s, healthcare workforce planning became a major concern for researchers and policy makers, since an imbalance of health professionals may create a serious insufficiency in the health system, and eventually lead to avoidable patient deaths. As such, methodologies and techniques have evolved significantly throughout the years, and simulation, in particular system dynamics, has been used broadly. However, tools such as stochastic agent-based simulation offer additional advantages for conducting forecasts, making it straightforward to incorporate microeconomic foundations and behavior rules into the agents. Surprisingly, we found no application of agent-based simulation to healthcare workforce planning above the hospital level. In this paper we develop a stochastic agent-based simulation model to forecast the supply of physicians and apply it to the Portuguese physician workforce. Moreover, we study the effect of variability in key input parameters using Monte Carlo simulation, concluding that small deviations in emigration or dropout rates may originate disparate forecasts. We also present different scenarios reflecting opposing policy directions and quantify their effect using the model. Finally, we perform an analysis of the impact of existing demographic projections on the demand for healthcare services. Results suggest that despite a declining population there may not be enough physicians to deliver all the care an ageing population may require. Such conclusion challenges anecdotal evidence of a surplus of physicians, supported mainly by the observation that Portugal has more physicians than the EU average.


Healthcare workforce planning Agent-based simulation Health economics Monte Carlos analysis 



The authors acknowledge Grant No SFRH/BD/102853/2014 and Grant No PTDC/IIMGES/4770/2014 from FCT - Fundação para a Ciência e Tecnologia that funded part of the research. Also, the authors would like to thank the anonymous reviewers, who made extremely valuable suggestions, helping to improve the paper considerably. Remaining errors are our sole responsibility.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Mário Amorim Lopes
    • 1
  • Álvaro Santos Almeida
    • 2
  • Bernardo Almada-Lobo
    • 1
  1. 1.INESC-TEC Porto, Faculdade de Engenharia da Universidade do PortoPortoPortugal
  2. 2.CEF-UP, Faculdade de Economia da Universidade do PortoPortoPortugal

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