1- Associate Professor, Department of Resource Economics, Economics Research Institute, Tarbiat Modares University, Tehran, Iran , aghelik@modares.ac.ir
2- PhD Student in Health Economics, Faculty of Economics and Management, Islamic Azad University, SR.C., Tehran, Iran.
3- Assistant professor, Department of Health Services Management, SR.C., Islamic Azad University, Tehran, Iran
2- PhD Student in Health Economics, Faculty of Economics and Management, Islamic Azad University, SR.C., Tehran, Iran.
3- Assistant professor, Department of Health Services Management, SR.C., Islamic Azad University, Tehran, Iran
Keywords: Game theory, health insurance, policy-making, adverse selection, moral hazard, social equity
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Extended Abstract
Health insurance, as a core instrument of public policy, plays a vital role in promoting equity, improving access, and managing financial risk [1,2]. Designing effective policies, however, requires analyzing strategic interactions among insurers, beneficiaries, and providers [3]. Game theory has increasingly become a powerful framework for examining competition, cooperation, and conflicts of interest in health insurance systems [4], with applications in optimal contract design [5], fraud and moral hazard analysis [6,7], insurer competition [8], insurer–provider cooperation [9], and big‑data analytics [10].
In Iran, research has largely focused on qualitative and macro‑level policy analyses, while quantitative modeling remains underutilized [11]. Yet evidence shows that game theory can predict stakeholder behavior, reduce moral hazard, optimize contracts, and enhance equity and efficiency in health insurance systems [5,6,12].
Empirical studies highlight its relevance across key domains: moral hazard and welfare loss [6]; resource allocation and patient access [12]; insurer–provider cooperation [9]; information asymmetry reduction through big data [10]; patient–provider interaction optimization [13,14]; competitive strategy design [8,15,16]; fraud dynamics [7,6]; and adverse selection mechanisms [17-19]. Research on optimal contracts further underscores the importance of Pareto‑efficient multi‑insurer markets, strategic regulation, and advanced risk‑management structures [5,18,20,21].
Against this backdrop, this article conducts a systematic review of game‑theoretic applications in health insurance policy‑making, synthesizing existing evidence and identifying pathways for improving policy design and insurance mechanisms. Given the growing relevance of game‑theoretic approaches and the need for more rigorous analytical frameworks in Iran, this review provides a robust scientific foundation for policy decisions and future research.
Methods:
This study employed a systematic review methodology to examine the application of game theory in health insurance policymaking. The review process included the following stages: search strategy and identification of relevant articles, inclusion and exclusion criteria, screening and selection of studies, data extraction, and synthesis of findings.
Search Strategy A comprehensive search was conducted across reputable academic databases including Scopus, ScienceDirect, Web of Science, PubMed, IEEE, and other credible national repositories. The search terms were constructed using logical operators (AND, OR) and combined keywords related to game theory, health insurance, and insurance behavior: (“game theory” OR “evolutionary game” OR “game-theoretic”) AND (“health insurance” OR “social security” OR “healthcare financing” OR “public insurance”) AND (“moral hazard” OR “adverse selection” OR “insurance behavior”)
Health insurance, as a core instrument of public policy, plays a vital role in promoting equity, improving access, and managing financial risk [1,2]. Designing effective policies, however, requires analyzing strategic interactions among insurers, beneficiaries, and providers [3]. Game theory has increasingly become a powerful framework for examining competition, cooperation, and conflicts of interest in health insurance systems [4], with applications in optimal contract design [5], fraud and moral hazard analysis [6,7], insurer competition [8], insurer–provider cooperation [9], and big‑data analytics [10].
In Iran, research has largely focused on qualitative and macro‑level policy analyses, while quantitative modeling remains underutilized [11]. Yet evidence shows that game theory can predict stakeholder behavior, reduce moral hazard, optimize contracts, and enhance equity and efficiency in health insurance systems [5,6,12].
Empirical studies highlight its relevance across key domains: moral hazard and welfare loss [6]; resource allocation and patient access [12]; insurer–provider cooperation [9]; information asymmetry reduction through big data [10]; patient–provider interaction optimization [13,14]; competitive strategy design [8,15,16]; fraud dynamics [7,6]; and adverse selection mechanisms [17-19]. Research on optimal contracts further underscores the importance of Pareto‑efficient multi‑insurer markets, strategic regulation, and advanced risk‑management structures [5,18,20,21].
Against this backdrop, this article conducts a systematic review of game‑theoretic applications in health insurance policy‑making, synthesizing existing evidence and identifying pathways for improving policy design and insurance mechanisms. Given the growing relevance of game‑theoretic approaches and the need for more rigorous analytical frameworks in Iran, this review provides a robust scientific foundation for policy decisions and future research.
Methods:
This study employed a systematic review methodology to examine the application of game theory in health insurance policymaking. The review process included the following stages: search strategy and identification of relevant articles, inclusion and exclusion criteria, screening and selection of studies, data extraction, and synthesis of findings.
Search Strategy A comprehensive search was conducted across reputable academic databases including Scopus, ScienceDirect, Web of Science, PubMed, IEEE, and other credible national repositories. The search terms were constructed using logical operators (AND, OR) and combined keywords related to game theory, health insurance, and insurance behavior: (“game theory” OR “evolutionary game” OR “game-theoretic”) AND (“health insurance” OR “social security” OR “healthcare financing” OR “public insurance”) AND (“moral hazard” OR “adverse selection” OR “insurance behavior”)
- Inclusion Criteria All rigorous scientific studies published in Persian and English since 2011 that examined the application of game theory in the context of health insurance.
- Exclusion Criteria Books,Theses and letters to the editor, non-scientific reports, duplicate articles, and studies lacking direct relevance to the topic.
- Following the search strategy, duplicate records were removed. Titles and abstracts were screened based on the inclusion and exclusion criteria, and irrelevant studies were excluded. Full texts of potentially eligible articles were then assessed, and non‑compliant studies were removed. Study quality was evaluated using the JBI checklist. All screening steps were performed independently by two reviewers, with disagreements resolved by a third expert. Due to methodological heterogeneity, heterogeneity analysis and meta‑analysis were not feasible, and the findings were synthesized narratively.
- After selecting the relevant studies and assessing their quality, key data were extracted and organized to form a coherent analytical framework. Studies were categorized by research objectives, game model type, target groups, analytical tools, and reported outcomes. A comparative analysis was conducted to identify major patterns, trends, and gaps, enabling a concise synthesis of strengths and limitations across the literature. All steps were carried out carefully by the research team to ensure a rigorous and goal‑oriented systematic review.
This approach facilitated a transparent and evidence-based analysis of the role of game theory in insurer and insured behavior, moral hazard management, adverse selection, and the design of optimal health insurance policies.
Results:
The study selection process is illustrated in Figure 1. Initially, 138,143 articles were identified. After removing 137,920 irrelevant and duplicate records, 223 articles were screened based on their titles and abstracts. Of these, 167 were excluded due to the absence of key analytical tools. The full texts of the remaining 56 articles were thoroughly reviewed in terms of methodology and research instruments, resulting in the selection of 24 relevant and high-quality studies for systematic analysis. (Figure 1(
.PNG)
Game theory offers a powerful framework for analyzing strategic dynamics in health insurance. From cooperative and evolutionary models to competitive market strategies and contract design tools, its applications reveal strong potential. The findings highlight the need for integrated incentives, big data, and attention to socio-economic and geographic factors to support equitable and sustainable policy development.
1. Asymmetric Information, Adverse Selection, and Moral Hazard
One of the fundamental challenges in the health insurance market is the presence of asymmetric information between insurers and the insured, which gives rise to phenomena such as adverse selection and moral hazard. This situation can be modeled within the framework of game theory as a game with incomplete information—where the insured individual has full knowledge of their true health status, while the insurer operates under informational constraints.
A. Evidence from Iran The study by Nobahar et al.[22] in Iran’s health insurance sector revealed significant evidence of adverse selection. Individuals with higher health risks were more likely to purchase insurance, thereby shifting the risk pool composition to the disadvantage of insurers. From a game-theoretic perspective, this situation leads to an inefficient equilibrium: insurers, facing higher-risk enrollees, are compelled to raise premiums, which in turn drives low-risk individuals out of the market. The resulting equilibrium increases insurer costs, disrupts the financial balance of insurance funds, and reduces the overall efficiency of the health insurance system.
B. International Evidence Nuscheler and Grunow [23], in their study of Germany’s health insurance system, examined risk selection between public and private insurers. Their findings showed that private insurers benefit from shifting high-risk individuals to the public system, while public insurers bear a heavier financial burden. This scenario exemplifies a non-cooperative game that leads to suboptimal equilibrium and unfair competition. The study recommends implementing risk adjustment mechanisms between public and private insurers to align incentives and promote a more efficient and equitable balance.
2. Equity and Universal Health Coverage in Insurance Policy
Achieving universal health coverage (UHC) and equitable access to healthcare is a core objective of health insurance policy. Game theory offers a robust analytical framework to model strategic interactions among governments, insurers, providers, and beneficiaries toward this goal.
Comparative evidence from the UK and Germany illustrates two successful models: the UK's NHS, based on tax-funded solidarity, ensures equal access through centralized financing and regulation; Germany’s social insurance system combines solidarity, self-governance, and regulated competition. Both systems align individual incentives with collective goals, using strategic mechanisms to prevent adverse selection and promote financial sustainability [24,25].
For Iran, these experiences suggest that achieving equity and UHC requires:
Results:
The study selection process is illustrated in Figure 1. Initially, 138,143 articles were identified. After removing 137,920 irrelevant and duplicate records, 223 articles were screened based on their titles and abstracts. Of these, 167 were excluded due to the absence of key analytical tools. The full texts of the remaining 56 articles were thoroughly reviewed in terms of methodology and research instruments, resulting in the selection of 24 relevant and high-quality studies for systematic analysis. (Figure 1(
Game theory offers a powerful framework for analyzing strategic dynamics in health insurance. From cooperative and evolutionary models to competitive market strategies and contract design tools, its applications reveal strong potential. The findings highlight the need for integrated incentives, big data, and attention to socio-economic and geographic factors to support equitable and sustainable policy development.
1. Asymmetric Information, Adverse Selection, and Moral Hazard
One of the fundamental challenges in the health insurance market is the presence of asymmetric information between insurers and the insured, which gives rise to phenomena such as adverse selection and moral hazard. This situation can be modeled within the framework of game theory as a game with incomplete information—where the insured individual has full knowledge of their true health status, while the insurer operates under informational constraints.
A. Evidence from Iran The study by Nobahar et al.[22] in Iran’s health insurance sector revealed significant evidence of adverse selection. Individuals with higher health risks were more likely to purchase insurance, thereby shifting the risk pool composition to the disadvantage of insurers. From a game-theoretic perspective, this situation leads to an inefficient equilibrium: insurers, facing higher-risk enrollees, are compelled to raise premiums, which in turn drives low-risk individuals out of the market. The resulting equilibrium increases insurer costs, disrupts the financial balance of insurance funds, and reduces the overall efficiency of the health insurance system.
B. International Evidence Nuscheler and Grunow [23], in their study of Germany’s health insurance system, examined risk selection between public and private insurers. Their findings showed that private insurers benefit from shifting high-risk individuals to the public system, while public insurers bear a heavier financial burden. This scenario exemplifies a non-cooperative game that leads to suboptimal equilibrium and unfair competition. The study recommends implementing risk adjustment mechanisms between public and private insurers to align incentives and promote a more efficient and equitable balance.
2. Equity and Universal Health Coverage in Insurance Policy
Achieving universal health coverage (UHC) and equitable access to healthcare is a core objective of health insurance policy. Game theory offers a robust analytical framework to model strategic interactions among governments, insurers, providers, and beneficiaries toward this goal.
Comparative evidence from the UK and Germany illustrates two successful models: the UK's NHS, based on tax-funded solidarity, ensures equal access through centralized financing and regulation; Germany’s social insurance system combines solidarity, self-governance, and regulated competition. Both systems align individual incentives with collective goals, using strategic mechanisms to prevent adverse selection and promote financial sustainability [24,25].
For Iran, these experiences suggest that achieving equity and UHC requires:
- Designing sustainable financing mechanisms (via taxation or social contributions),
- Implementing risk adjustment systems to protect high-risk groups,
- Aligning stakeholder incentives through game-theoretic policy frameworks.
3. Contract Design and Incentive Mechanisms in Health Insurance
Game theory plays a critical role in designing insurance contracts and incentive structures that guide strategic behavior among insurers, insured individuals, and intermediaries toward efficient and sustainable outcomes.
Studies such as Boonen and Han [21] highlight that multi-tier contracts, co-payment schemes, and risk adjustment mechanisms can address both adverse selection and moral hazard, promoting financial stability and equitable access. Similarly, Mirzaei et al. [26] show that in Iran’s life insurance market, unbalanced commission structures lead to conflicts of interest and reduced trust. Aligning incentives through transparent and performance-based payment models can enhance market efficiency.
These insights suggest that for Iran’s health insurance system, carefully designed contracts and incentive mechanisms—grounded in game-theoretic principles—are essential to prevent opportunistic behavior and ensure long-term sustainability.
4. Comparative Experiences and International Frameworks
Cross-country comparisons reveal that the structure and financing of health insurance systems play a critical role in promoting efficiency and equity. International studies emphasize the importance of designing interaction mechanisms among key actors—insurers, insured individuals, governments, and providers—to achieve stable and cooperative equilibria.
Radeic et al. [27] found that weak government oversight and dominance of private insurers in the U.S. led to inefficient outcomes, high costs, and unequal access, whereas Germany and Canada benefited from socially cohesive frameworks that fostered fairness and efficiency. Boyle [25] highlighted the UK's NHS as a model where strategic government contracts with providers helped align stakeholder interests and prevent opportunistic behavior. The WHO’s Madrid Framework advocates for integrated services, stronger governance, accountability, and technological innovation—reflecting a shift toward cooperative game dynamics and win-win outcomes [28]. Busse [25] emphasized that Germany’s blend of competition and solidarity, supported by risk adjustment mechanisms and regulatory oversight, effectively mitigates risk selection and protects vulnerable groups.
These experiences suggest that well-designed game-theoretic policies can guide actors toward collaboration, reduce inefficiencies, and enhance equity in health insurance systems.
Discussion:
This systematic review highlights the strong potential of game theory in addressing complex challenges in health insurance policymaking. Health systems worldwide face issues such as asymmetric information, adverse selection, moral hazard, financial constraints, and the need to balance efficiency with equity. Game theory provides a structured framework to analyze strategic interactions among key stakeholders insurers, insured individuals, providers, and governments and to anticipate policy outcomes.
Evidence shows that asymmetric information drives adverse selection and raises insurer costs. Studies indicate that, without regulatory controls, high‑risk individuals disproportionately enter insurance pools, destabilizing the market[22,23]. Game‑theoretic models highlight that risk‑based contracts, regulatory mechanisms, and improved information exchange can move insurer–insured interactions toward a more stable equilibrium and support more equitable, risk‑sensitive insurance policies.
Studies by Boonen and Han[21] and Mirzaei et al.[26] show that incentive‑based insurance contracts are essential for reducing opportunistic behavior. Game‑theoretic models demonstrate how adjustments in contract design, participation, or information can realign stakeholder behavior, helping policymakers develop mechanisms that curb moral hazard, improve risk management, and enhance the performance of health insurance systems.
Studies by Boyle[24] and Busse[25] emphasize that the sustainability of health insurance systems depends on balancing equitable access with financial stability. Game‑theoretic models help analyze how insurers’ and governments’ strategic decisions shape equity and efficiency, allowing scenarios such as insurer competition, high‑risk enrolment, and supportive policies to be evaluated. These insights guide the design of regulatory and redistributive mechanisms that protect vulnerable groups and strengthen fairness in access to health services.
International evidence shows that clear rules and strong government oversight are essential for sustainable and equitable health insurance systems. Countries with cooperative regulatory frameworks—such as Germany, Canada, and the UK—achieve more stable, equitable, and cost‑controlled outcomes than market‑driven models like the United States[27,28]. Game‑theoretic analysis helps evaluate strategic behavior among insurers, governments, and providers, guiding the design of regulatory and redistributive mechanisms that prevent non‑cooperative outcomes and strengthen fairness and efficiency.
In Iran, game‑theoretic applications remain mostly conceptual due to fragmented insurers, weak data systems, and the absence of incentive‑based contracts. Using game‑theoretic frameworks can help predict stakeholder behavior and show how changes in contracts, information, or oversight may reduce moral hazard, improve coordination, and support more equitable health insurance reforms.
Limitations
a. Limited Access to National Data and Iran’s Insurance Market: Detailed information regarding the behavior of insurers, insured individuals, and healthcare providers in Iran is often restricted or confidential. This limitation hinders precise analysis of strategic interactions and the full application of game-theoretic models in health insurance policymaking.
b. Complexity of Real-World Behavior: Game theory models typically simulate strategic behavior based on defined assumptions, while actual decision-making by insurers and insured individuals is influenced by complex economic, social, and psychological factors. Therefore, model outcomes may serve as theoretical frameworks and policy guides rather than fully reflecting market realities.
c. Limited Generalizability of International Experience: Findings from countries such as Germany, the UK, and the United States may not be directly applicable to Iran due to structural, economic, and cultural differences. This reduces the practical relevance of analytical models and policy recommendations.
d. Limited Attention to Social Dimensions of Equity: Game-theoretic models focus primarily on strategic interactions and may underrepresent social, geographic, and cultural aspects of equity in access to health insurance services.
e. Market Dynamics and Policy Shifts: Health insurance markets and policies evolve rapidly, and some model assumptions may require revision or adaptation over time to remain relevant.
Conclusion This study demonstrates that game theory is an effective analytical tool for examining strategic behaviors among insurers, insured individuals, and other stakeholders in the health system. Evidence from both domestic and international research suggests that game-theoretic approaches can enhance understanding of fundamental challenges such as asymmetric information, adverse selection, moral hazard, optimal contract design, and equity in insurance coverage. Experiences from countries like Germany and the UK show that combining regulatory mechanisms, incentive-based contracts, and socially cohesive policies can lead to stable equilibria among insurance actors.
In Iran, although initial efforts have been made to apply game-theoretic frameworks, several challenges—including fragmented insurance institutions, weak data infrastructure, lack of risk adjustment mechanisms, and limited implementation of incentive-based contracts—have hindered full utilization of this approach. Therefore, health insurance policymakers must consider institutional, cultural, and operational contexts alongside theoretical models when designing policies.
Overall, game theory offers a valuable framework for developing more efficient, equitable, and sustainable health insurance policies. However, realizing its full potential requires future research to focus on localized modeling, field studies, and the integration of data-driven technologies. Bridging the gap between theory and practice is essential to transforming health insurance into a powerful instrument for promoting social justice and system sustainability.
Strategic Recommendations for Future Research and Policy Development:
Game theory plays a critical role in designing insurance contracts and incentive structures that guide strategic behavior among insurers, insured individuals, and intermediaries toward efficient and sustainable outcomes.
Studies such as Boonen and Han [21] highlight that multi-tier contracts, co-payment schemes, and risk adjustment mechanisms can address both adverse selection and moral hazard, promoting financial stability and equitable access. Similarly, Mirzaei et al. [26] show that in Iran’s life insurance market, unbalanced commission structures lead to conflicts of interest and reduced trust. Aligning incentives through transparent and performance-based payment models can enhance market efficiency.
These insights suggest that for Iran’s health insurance system, carefully designed contracts and incentive mechanisms—grounded in game-theoretic principles—are essential to prevent opportunistic behavior and ensure long-term sustainability.
4. Comparative Experiences and International Frameworks
Cross-country comparisons reveal that the structure and financing of health insurance systems play a critical role in promoting efficiency and equity. International studies emphasize the importance of designing interaction mechanisms among key actors—insurers, insured individuals, governments, and providers—to achieve stable and cooperative equilibria.
Radeic et al. [27] found that weak government oversight and dominance of private insurers in the U.S. led to inefficient outcomes, high costs, and unequal access, whereas Germany and Canada benefited from socially cohesive frameworks that fostered fairness and efficiency. Boyle [25] highlighted the UK's NHS as a model where strategic government contracts with providers helped align stakeholder interests and prevent opportunistic behavior. The WHO’s Madrid Framework advocates for integrated services, stronger governance, accountability, and technological innovation—reflecting a shift toward cooperative game dynamics and win-win outcomes [28]. Busse [25] emphasized that Germany’s blend of competition and solidarity, supported by risk adjustment mechanisms and regulatory oversight, effectively mitigates risk selection and protects vulnerable groups.
These experiences suggest that well-designed game-theoretic policies can guide actors toward collaboration, reduce inefficiencies, and enhance equity in health insurance systems.
Discussion:
This systematic review highlights the strong potential of game theory in addressing complex challenges in health insurance policymaking. Health systems worldwide face issues such as asymmetric information, adverse selection, moral hazard, financial constraints, and the need to balance efficiency with equity. Game theory provides a structured framework to analyze strategic interactions among key stakeholders insurers, insured individuals, providers, and governments and to anticipate policy outcomes.
Evidence shows that asymmetric information drives adverse selection and raises insurer costs. Studies indicate that, without regulatory controls, high‑risk individuals disproportionately enter insurance pools, destabilizing the market[22,23]. Game‑theoretic models highlight that risk‑based contracts, regulatory mechanisms, and improved information exchange can move insurer–insured interactions toward a more stable equilibrium and support more equitable, risk‑sensitive insurance policies.
Studies by Boonen and Han[21] and Mirzaei et al.[26] show that incentive‑based insurance contracts are essential for reducing opportunistic behavior. Game‑theoretic models demonstrate how adjustments in contract design, participation, or information can realign stakeholder behavior, helping policymakers develop mechanisms that curb moral hazard, improve risk management, and enhance the performance of health insurance systems.
Studies by Boyle[24] and Busse[25] emphasize that the sustainability of health insurance systems depends on balancing equitable access with financial stability. Game‑theoretic models help analyze how insurers’ and governments’ strategic decisions shape equity and efficiency, allowing scenarios such as insurer competition, high‑risk enrolment, and supportive policies to be evaluated. These insights guide the design of regulatory and redistributive mechanisms that protect vulnerable groups and strengthen fairness in access to health services.
International evidence shows that clear rules and strong government oversight are essential for sustainable and equitable health insurance systems. Countries with cooperative regulatory frameworks—such as Germany, Canada, and the UK—achieve more stable, equitable, and cost‑controlled outcomes than market‑driven models like the United States[27,28]. Game‑theoretic analysis helps evaluate strategic behavior among insurers, governments, and providers, guiding the design of regulatory and redistributive mechanisms that prevent non‑cooperative outcomes and strengthen fairness and efficiency.
In Iran, game‑theoretic applications remain mostly conceptual due to fragmented insurers, weak data systems, and the absence of incentive‑based contracts. Using game‑theoretic frameworks can help predict stakeholder behavior and show how changes in contracts, information, or oversight may reduce moral hazard, improve coordination, and support more equitable health insurance reforms.
Limitations
a. Limited Access to National Data and Iran’s Insurance Market: Detailed information regarding the behavior of insurers, insured individuals, and healthcare providers in Iran is often restricted or confidential. This limitation hinders precise analysis of strategic interactions and the full application of game-theoretic models in health insurance policymaking.
b. Complexity of Real-World Behavior: Game theory models typically simulate strategic behavior based on defined assumptions, while actual decision-making by insurers and insured individuals is influenced by complex economic, social, and psychological factors. Therefore, model outcomes may serve as theoretical frameworks and policy guides rather than fully reflecting market realities.
c. Limited Generalizability of International Experience: Findings from countries such as Germany, the UK, and the United States may not be directly applicable to Iran due to structural, economic, and cultural differences. This reduces the practical relevance of analytical models and policy recommendations.
d. Limited Attention to Social Dimensions of Equity: Game-theoretic models focus primarily on strategic interactions and may underrepresent social, geographic, and cultural aspects of equity in access to health insurance services.
e. Market Dynamics and Policy Shifts: Health insurance markets and policies evolve rapidly, and some model assumptions may require revision or adaptation over time to remain relevant.
Conclusion This study demonstrates that game theory is an effective analytical tool for examining strategic behaviors among insurers, insured individuals, and other stakeholders in the health system. Evidence from both domestic and international research suggests that game-theoretic approaches can enhance understanding of fundamental challenges such as asymmetric information, adverse selection, moral hazard, optimal contract design, and equity in insurance coverage. Experiences from countries like Germany and the UK show that combining regulatory mechanisms, incentive-based contracts, and socially cohesive policies can lead to stable equilibria among insurance actors.
In Iran, although initial efforts have been made to apply game-theoretic frameworks, several challenges—including fragmented insurance institutions, weak data infrastructure, lack of risk adjustment mechanisms, and limited implementation of incentive-based contracts—have hindered full utilization of this approach. Therefore, health insurance policymakers must consider institutional, cultural, and operational contexts alongside theoretical models when designing policies.
Overall, game theory offers a valuable framework for developing more efficient, equitable, and sustainable health insurance policies. However, realizing its full potential requires future research to focus on localized modeling, field studies, and the integration of data-driven technologies. Bridging the gap between theory and practice is essential to transforming health insurance into a powerful instrument for promoting social justice and system sustainability.
Strategic Recommendations for Future Research and Policy Development:
- Develop localized models tailored to the structure of Iran’s health insurance market.
- Utilize advanced technologies such as big data and artificial intelligence to reduce information asymmetry.
- Design and pilot incentive-based contracts in real-world settings.
- Conduct comparative analyses of successful international policies to identify transferable models.
Declarations
Ethical considerations: This article is part of a doctoral dissertation conducted in full compliance with research ethics, registered under ID 162969369 at Islamic Azad University.
Funding:This research was conducted without any financial support.
Conflict of interest: The authors declare that there is no conflict of interest.
Authors’ contribution:
Ethical considerations: This article is part of a doctoral dissertation conducted in full compliance with research ethics, registered under ID 162969369 at Islamic Azad University.
Funding:This research was conducted without any financial support.
Conflict of interest: The authors declare that there is no conflict of interest.
Authors’ contribution:
- M.P: Study design, Data curation, Data analysis, Writing– original draft.
- L.A: Methodology, Supervision, Writing– review & editing, Project administration (corresponding author for journal communication), Final approval.
- L.N: Supervision, Validation.
Consent for publication: Not applicable.
Data availability: Access to the data is available through the corresponding author upon reasonable request.
AI deceleration:
Artificial intelligence (Copilot) was used for editing the English section of this manuscript. All AI‑assisted content was reviewed and approved by the authors.
Acknowledgments: The authors gratefully acknowledge the valuable input and scientific feedback provided by professors, colleagues, and experts throughout the research process.
Data availability: Access to the data is available through the corresponding author upon reasonable request.
AI deceleration:
Artificial intelligence (Copilot) was used for editing the English section of this manuscript. All AI‑assisted content was reviewed and approved by the authors.
Acknowledgments: The authors gratefully acknowledge the valuable input and scientific feedback provided by professors, colleagues, and experts throughout the research process.
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