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Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance

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 replac...

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Autores principales: Ho, Calvin W L, Ali, Joseph, Caals, Karel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: World Health Organization 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7133481/
https://www.ncbi.nlm.nih.gov/pubmed/32284650
http://dx.doi.org/10.2471/BLT.19.234732
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author Ho, Calvin W L
Ali, Joseph
Caals, Karel
author_facet Ho, Calvin W L
Ali, Joseph
Caals, Karel
author_sort Ho, Calvin W L
collection PubMed
description 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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spelling pubmed-71334812020-04-13 Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance Ho, Calvin W L Ali, Joseph Caals, Karel Bull World Health Organ Policy & Practice 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. World Health Organization 2020-04-01 2020-02-25 /pmc/articles/PMC7133481/ /pubmed/32284650 http://dx.doi.org/10.2471/BLT.19.234732 Text en (c) 2020 The authors; licensee World Health Organization. This is an open access article distributed under the terms of the Creative Commons Attribution IGO License (http://creativecommons.org/licenses/by/3.0/igo/legalcode), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In any reproduction of this article there should not be any suggestion that WHO or this article endorse any specific organization or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article's original URL.
spellingShingle Policy & Practice
Ho, Calvin W L
Ali, Joseph
Caals, Karel
Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title_full Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title_fullStr Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title_full_unstemmed Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title_short Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
title_sort ensuring trustworthy use of artificial intelligence and big data analytics in health insurance
topic Policy & Practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7133481/
https://www.ncbi.nlm.nih.gov/pubmed/32284650
http://dx.doi.org/10.2471/BLT.19.234732
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