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Pathways to Good Healthcare Services and Patient Satisfaction: An Evolutionary Game Theoretical Approach

Author

Listed:
  • Zainab Alalawi
  • The Anh Han
  • Yifeng Zeng
  • Aiman Elragig

Abstract

Spending by the UK's National Health Service (NHS) on independent healthcare treatment has been increased in recent years and is predicted to sustain its upward trend with the forecast of population growth. Some have viewed this increase as an attempt not to expand the patients' choices but to privatize public healthcare. This debate poses a social dilemma whether the NHS should stop cooperating with Private providers. This paper contributes to healthcare economic modelling by investigating the evolution of cooperation among three proposed populations: Public Healthcare Providers, Private Healthcare Providers and Patients. The Patient population is included as a main player in the decision-making process by expanding patient's choices of treatment. We develop a generic basic model that measures the cost of healthcare provision based on given parameters, such as NHS and private healthcare providers' cost of investments in both sectors, cost of treatments and gained benefits. A patient's costly punishment is introduced as a mechanism to enhance cooperation among the three populations. Our findings show that cooperation can be improved with the introduction of punishment (patient's punishment) against defecting providers. Although punishment increases cooperation, it is very costly considering the small improvement in cooperation in comparison to the basic model.

Suggested Citation

  • Zainab Alalawi & The Anh Han & Yifeng Zeng & Aiman Elragig, 2019. "Pathways to Good Healthcare Services and Patient Satisfaction: An Evolutionary Game Theoretical Approach," Papers 1907.07132, arXiv.org.
  • Handle: RePEc:arx:papers:1907.07132
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    File URL: http://arxiv.org/pdf/1907.07132
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    References listed on IDEAS

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    Cited by:

    1. Zhao, Yuntong & Du, Yushen, 2021. "Technical standard competition: An ecosystem-view analysis based on stochastic evolutionary game theory," Technology in Society, Elsevier, vol. 67(C).

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