{"title":"Analysing the Suitability of Artificial Intelligence in Healthcare and the Role of AI Governance.","authors":"Zhenwei You, Yahui Wang, Yineng Xiao","doi":"10.1007/s10728-025-00514-5","DOIUrl":null,"url":null,"abstract":"<p><p>In recent years, artificial intelligence (AI) has become more important in healthcare. It has the ability to completely change how patients are diagnosed, treated, and cared for. To make sure AI is properly supervised in healthcare, many problems need to be solved. This calls for a broad approach that includes policy, technology, and involving important people. This study investigates the governance of AI within healthcare, highlighting the importance of policy, technology, and stakeholder engagement. Adopting a mixed-methods research design, the study encompasses surveys, interviews, and document analysis to comprehensively explore diverse perspectives on AI governance. Purposive sampling techniques were employed to gather 897 valid samples, ensuring diversity across stakeholder groups. Surveys gathered quantitative data on demographic characteristics and attitudes toward AI governance, while interviews provided deeper insights into stakeholders' experiences and recommendations. Document analysis supplemented data collection by reviewing policy documents, guidelines, and academic literature related to AI governance. This study merges quantitative and qualitative data to thoroughly investigate AI governance, enabling the identification of policy implications and actionable recommendations. This study contributes novel insights by adopting a comprehensive approach to AI governance in healthcare, integrating policy, technology, and stakeholder engagement perspectives. Unlike previous studies focusing solely on individual aspects of AI governance, this research provides a holistic understanding of the complex dynamics involved. This research offers important insights into AI governance by investigating the impact of stakeholder engagement, ethical considerations, digital health disparities, governance structures, and health communication strategies on AI integration in healthcare, ultimately aiding in policy development and implementation.</p>","PeriodicalId":46740,"journal":{"name":"Health Care Analysis","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Care Analysis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10728-025-00514-5","RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ETHICS","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, artificial intelligence (AI) has become more important in healthcare. It has the ability to completely change how patients are diagnosed, treated, and cared for. To make sure AI is properly supervised in healthcare, many problems need to be solved. This calls for a broad approach that includes policy, technology, and involving important people. This study investigates the governance of AI within healthcare, highlighting the importance of policy, technology, and stakeholder engagement. Adopting a mixed-methods research design, the study encompasses surveys, interviews, and document analysis to comprehensively explore diverse perspectives on AI governance. Purposive sampling techniques were employed to gather 897 valid samples, ensuring diversity across stakeholder groups. Surveys gathered quantitative data on demographic characteristics and attitudes toward AI governance, while interviews provided deeper insights into stakeholders' experiences and recommendations. Document analysis supplemented data collection by reviewing policy documents, guidelines, and academic literature related to AI governance. This study merges quantitative and qualitative data to thoroughly investigate AI governance, enabling the identification of policy implications and actionable recommendations. This study contributes novel insights by adopting a comprehensive approach to AI governance in healthcare, integrating policy, technology, and stakeholder engagement perspectives. Unlike previous studies focusing solely on individual aspects of AI governance, this research provides a holistic understanding of the complex dynamics involved. This research offers important insights into AI governance by investigating the impact of stakeholder engagement, ethical considerations, digital health disparities, governance structures, and health communication strategies on AI integration in healthcare, ultimately aiding in policy development and implementation.
期刊介绍：
Health Care Analysis is a journal that promotes dialogue and debate about conceptual and normative issues related to health and health care, including health systems, healthcare provision, health law, public policy and health, professional health practice, health services organization and decision-making, and health-related education at all levels of clinical medicine, public health and global health. Health Care Analysis seeks to support the conversation between philosophy and policy, in particular illustrating the importance of conceptual and normative analysis to health policy, practice and research. As such, papers accepted for publication are likely to analyse philosophical questions related to health, health care or health policy that focus on one or more of the following: aims or ends, theories, frameworks, concepts, principles, values or ideology. All styles of theoretical analysis are welcome providing that they illuminate conceptual or normative issues and encourage debate between those interested in health, philosophy and policy. Papers must be rigorous, but should strive for accessibility – with care being taken to ensure that their arguments and implications are plain to a broad academic and international audience. In addition to purely theoretical papers, papers grounded in empirical research or case-studies are very welcome so long as they explore the conceptual or normative implications of such work. Authors are encouraged, where possible, to have regard to the social contexts of the issues they are discussing, and all authors should ensure that they indicate the ‘real world’ implications of their work. Health Care Analysis publishes contributions from philosophers, lawyers, social scientists, healthcare educators, healthcare professionals and administrators, and other health-related academics and policy analysts.
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