ArticleBulletin of the World Health Organization2020
Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance.
Article in Bulletin of the World Health Organization, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Configurations of human-centered AI at work: seven actor-structure engagements in organizations.Frontiers in artificial intelligence · 2023Pooled it
- The ethical and legal landscape of brain data governance.PloS one · 2022Pooled it
- Is Gamification the New Panacea for Health Behavioral Changes? Implications for the Health and Life Insurance Industry.JMIR serious games · 2026Article
- Paying for hospital care in seven central and Eastern European countries - a comparative analysis.Health economics review · 2026Article
- Artificial intelligence applications in health insurances: a scoping review.Cost effectiveness and resource allocation : C/E · 2025Review
- Simulated misuse of large language models and clinical credit systems.NPJ digital medicine · 2024Review
- Simulated Misuse of Large Language Models and Clinical Credit Systems.medRxiv : the preprint server for health sciences · 2024Article
- Machine learning in health financing: benefits, risks and regulatory needs.Bulletin of the World Health Organization · 2024Article
- Exploring the effects of digital technologies in health financing for universal health coverage: a synthesis of country experiences and lessons.Oxford open digital health · 2024Review
- Article
- The Role of Artificial Intelligence Model Documentation in Translational Science: Scoping Review.Interactive journal of medical research · 2023Article
- Personal Health Record for Personalizing Research and Care Trajectories: A Proof of Concept Pilot with Diet in Inflammatory Bowel Diseases.Journal of personalized medicine · 2023Article
- Using artificial intelligence for diabetic retinopathy screening: Policy implications.Indian journal of ophthalmology · 2021Review
- Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China.Journal of medical systems · 2021Review
- Heralding the Digitalization of Life in Post-Pandemic East Asian Societies.Journal of bioethical inquiry · 2020Article
- Emerging Targeted Therapeutics for Genetic Subtypes of Parkinsonism.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2020Review
- Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.Scandinavian journal of trauma, resuscitation and emergency medicine · 2020Article
- Balancing risks and benefits of artificial intelligence in the health sector.Bulletin of the World Health Organization · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological advances in big data (large amounts of highly varied data from many different sources that may be processed rapidly), data sciences and artificial intelligence can improve health-system functions and promote personalized care and public good. However, these technologies will not replace the fundamental components of the health system, such as ethical leadership and governance, or avoid the need for a robust ethical and regulatory environment. In this paper, we discuss what a robust ethical and regulatory environment might look like for big data analytics in health insurance, and describe examples of safeguards and participatory mechanisms that should be established. First, a clear and effective data governance framework is critical. Legal standards need to be enacted and insurers should be encouraged and given incentives to adopt a human-centred approach in the design and use of big data analytics and artificial intelligence. Second, a clear and accountable process is necessary to explain what information can be used and how it can be used. Third, people whose data may be used should be empowered through their active involvement in determining how their personal data may be managed and governed. Fourth, insurers and governance bodies, including regulators and policy-makers, need to work together to ensure that the big data analytics based on artificial intelligence that are developed are transparent and accurate. Unless an enabling ethical environment is in place, the use of such analytics will likely contribute to the proliferation of unconnected data systems, worsen existing inequalities, and erode trustworthiness and trust.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.