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Patients, primary care, and policy: Agent-based simulation modeling for health care decision support
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Patients, primary care, and policy: Agent-based simulation modeling for health care decision support

Author

Listed:
  • Martin Comis

    (RWTH Aachen University)

  • Catherine Cleophas

    (Christian-Albrechts-Universität zu Kiel)

  • Christina Büsing

    (RWTH Aachen University)

Abstract

Primary care systems are a cornerstone of universally accessible health care. The planning, analysis, and adaptation of primary care systems is a highly non-trivial problem due to the systems’ inherent complexity, unforeseen future events, and scarcity of data. To support the search for solutions, this paper introduces the hybrid agent-based simulation model SiM-Care. SiM-Care models and tracks the micro-interactions of patients and primary care physicians on an individual level. At the same time, it models the progression of time via the discrete-event paradigm. Thereby, it enables modelers to analyze multiple key indicators such as patient waiting times and physician utilization to assess and compare primary care systems. Moreover, SiM-Care can evaluate changes in the infrastructure, patient behavior, and service design. To showcase SiM-Care and its validation through expert input and empirical data, we present a case study for a primary care system in Germany. Specifically, we study the immanent implications of demographic change on rural primary care and investigate the effects of an aging population and a decrease in the number of physicians, as well as their combined effects.

Suggested Citation

  • Martin Comis & Catherine Cleophas & Christina Büsing, 2021. "Patients, primary care, and policy: Agent-based simulation modeling for health care decision support," Health Care Management Science, Springer, vol. 24(4), pages 799-826, December.
    • Handle: RePEc:kap:hcarem:v:24:y:2021:i:4:d:10.1007_s10729-021-09556-2
    DOI: 10.1007/s10729-021-09556-2
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