
Research Article
Toward Understanding the Interplay between Public and Private Healthcare Providers and Patients: An Agent-based Simulation Approach
@ARTICLE{10.4108/eai.21-10-2020.166668, author={Zainab Alalawi and Yifeng Zeng and The Anh Han}, title={Toward Understanding the Interplay between Public and Private Healthcare Providers and Patients: An Agent-based Simulation Approach}, journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}, volume={7}, number={24}, publisher={EAI}, journal_a={INIS}, year={2020}, month={10}, keywords={Healthcare Behaviour Modelling, Agent-based simulation, Evolutionary Game Theory, Collective Behaviour}, doi={10.4108/eai.21-10-2020.166668} }
- Zainab Alalawi
Yifeng Zeng
The Anh Han
Year: 2020
Toward Understanding the Interplay between Public and Private Healthcare Providers and Patients: An Agent-based Simulation Approach
INIS
EAI
DOI: 10.4108/eai.21-10-2020.166668
Abstract
Few modelling studies have been carried out to investigate patients’ involvement in the decision-making process in a healthcare system. Here we perform theoretical and simulation analysis of a healthcare business model involving three populations: Public Healthcare Providers, Private Healthcare Providers and Patients. The analysis contributes to healthcare economic modelling by analyzing the dynamics and emergence of cooperative behavior of agents within the three populations. Resorting to agent-based simulations, we examine the effect of increasing behavioural mutation and providers’ capacity on patients’ cooperative behaviour. We show that the former introduces more randomness in agents’ behaviors enabling cooperation to emerge in more difficult conditions. Moreover, when the providers’ capacity to meet patients’ demand is limited, patients exhibit low levels of cooperation, implying a more difficult cooperation dilemma in a healthcare system that needs addressing.
Copyright © 2020 Zainab Alalawi et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.