Abstract
Challenges in the healthcare system, attributed to factors like populationgrowth, pandemics, and budget reductions, can lead to unfortunate
outcomes in this complex sector. To address these challenges, the
application of mathematical modelling, particularly Evolutionary Game
Theory (EGT), proves promising.
In this thesis, our contributions are threefold: (i) creating a baseline
healthcare model incorporating key actors in a healthcare system, namely
Public and Private healthcare providers, and Patients; (ii) extending the
baseline model to study the effects of peer-punishment, utilising EGT
for a comprehensive examination of different decision-making strategies
and cooperation mechanisms; and (iii) exploring the impact of variation
in provider population sizes compared to the patient population.
Through thorough mathematical analysis and extensive agent-based
simulations, we find that defection is predominant among healthcare
providers in most settings. It is evident that providers should intensify
efforts to enhance cooperation and patient satisfaction, especially when
maintaining a high level of reputation benefit. The introduction of
patient-initiated punishment imposed on defecting providers leads to
prevailing cooperation when the patient’s benefit is sufficiently high.
Even with a modest reputation benefit, cooperation remains viable,
showing a significant increase when both reputation and patient benefit
are sufficiently high. Higher mutation rates introduce more randomness in agent behaviour, resulting in scenarios with high cooperation exhibiting
more instances of defection under larger mutation rates, while defectiondominated
scenarios showcase elevated cooperation.
Our findings uncover clear behavioural patterns: Private cooperation
rises with reduced provider and patient benefits, public cooperation
aligns with higher reputation benefits, and Patient behaviour fluctuates
with health benefits. Achieving patient cooperation becomes challenging
when Public and Private capacities fall below Patient demands or expectations,
underscoring the necessity for additional support mechanisms,
like incentives. The analysis reveals that higher mutation rates introduce
an additional layer of randomness to cooperative behaviour, affecting
the overall prevalence of cooperation.
Overall, the significance of the thesis findings lies in their contribution
to understanding the sustainability of cooperative behaviour within the
healthcare system and its implications for cost-effectiveness. The presented
models provide valuable insights into how various strategies and
parameters influence cooperation dynamics among healthcare providers
and patients, aiding in a deeper comprehension of the complex interactions
within healthcare scenarios. Our findings emphasize crucial factors
that highlight the centrality of balancing patients’ and providers’ benefits
to foster cooperation, understanding the necessity for substantial
provider benefits. Lastly, exploring different population sizes reveals that
patients are likely to lose interest (i.e., cooperate less) when healthcare
providers effectively meet patient demands.
| Date of Award | 21 Jun 2024 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | Yifeng Zeng (Supervisor) & The Anh Han (Supervisor) |