| Title: | Evolutionary game theory use in healthcare : a synthetic knowledge synthesis |
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| Authors: | ID Kokol, Peter (Author)
ID Završnik, Jernej (Author)
ID Blažun Vošner, Helena (Author)
ID Žlahtič, Bojan (Author) |
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| Files: |  information-16-00874-v2.pdf (587,94 KB)
MD5: 6A6F4DC7ABB342594CC8016A07A08395
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.02 - Review Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | Background: Evolutionary game theory (EGT), originating from Darwinian competition studies, offers a powerful framework for understanding complex healthcare interactions where multiple stakeholders with conflicting interests evolve strategies over time. Unlike traditional game theory, EGT accounts for bounded rationality and strategic evolution through imitation and selection. Aims and objectives: In our study, we use Synthetic Knowledge Synthesis (SKS) that integrates descriptive bibliometrics and bibliometric mapping to systematically analyze the application of EGT in healthcare. The SKS aimed to identify prolific research topics, suitable publishing venues, and productive institutions/countries for collaboration and funding. Data was harvested from the Scopus bibliographic database, encompassing 539 publications from 2000 to June 2025, Results: Production dynamics is revealing an exponential growth in scholarly output since 2019, with peak productivity in 2024. Descriptive bibliometrics showed China as the most prolific country (376 publications), followed by the United States and the United Kingdom. Key institutions are predominantly Chinese, and top journals include PLoS One and Frontiers in Public Health. Funding is primarily from Chinese entities like the National Natural Science Foundation of China. Bibliometric mapping identified five key research themes: game theory in cancer research, evolution game-based simulation of supply management, evolutionary game theory in epidemics, evolutionary games in trustworthy connected public health, and evolutionary games in collaborative governance. Conclusions: Despite EGT’s utility, significant research gaps exist in methodological robustness, data availability, contextual modelling, and interdisciplinary translation. Future research should focus on integrating machine learning, longitudinal data, and explicit ethical frameworks to enhance EGT’s practical application in adaptive, patient-centred healthcare systems |
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| Keywords: | evolutionary games theory, healthcare, complex healthcare systems, synthetic knowledge synthesis, thematic analysis |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 29.07.2025 |
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| Article acceptance date: | 06.10.2025 |
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| Publication date: | 08.10.2025 |
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| Publisher: | MDPI |
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| Year of publishing: | 2025 |
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| Number of pages: | 16 str. |
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| Numbering: | Vol. 16, issue 10, [article no.] 874 |
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| PID: | 20.500.12556/DKUM-95837  |
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| UDC: | 004.8 |
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| ISSN on article: | 2078-2489 |
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| COBISS.SI-ID: | 254115075 |
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| DOI: | 10.3390/info16100874 |
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| Copyright: |
© 2025 by the authors |
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| Publication date in DKUM: | 29.10.2025 |
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| Views: | 193 |
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| Downloads: | 11 |
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| Metadata: |    |
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| Categories: | Misc.
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