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

Zainab Alalawi, The Anh Han, Yifeng Zeng, Aiman Elragig

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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.
Original languageEnglish
Title of host publicationALIFE 2019
Subtitle of host publicationThe 2019 Conference on Artificial Life
EditorsHarold Fellermann, Jaume Bacardit, Ángel Goñi-Moreno, Rudolf M. Füchslin
Place of PublicationCambridge
PublisherThe MIT Press
Number of pages8
Publication statusPublished - Jul 2019
Externally publishedYes
EventThe 2019 Conference on Artificial Life - Newcastle University, Newcastle upon Tyne, United Kingdom
Duration: 29 Jul 20192 Aug 2019


ConferenceThe 2019 Conference on Artificial Life
Abbreviated titleALIFE 2019
Country/TerritoryUnited Kingdom
CityNewcastle upon Tyne
Internet address


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