Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity

Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and efficiency of care and services and to build learning and value-based health systems. Many studies have examined the technical performance of AI within an experimental context. These studies provide...

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Main Authors: Alami, Hassane, Lehoux, Pascale, Auclair, Yannick, de Guise, Michèle, Gagnon, Marie-Pierre, Shaw, James, Roy, Denis, Fleet, Richard, Ag Ahmed, Mohamed Ali, Fortin, Jean-Paul
Format: Article
Language:English
Published: JMIR Publications 2020-07-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2020/7/e17707
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spelling doaj-ce6511aff21246f998aa9d78b34a436e2021-04-02T21:36:38ZengJMIR PublicationsJournal of Medical Internet Research1438-88712020-07-01227e1770710.2196/17707Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of ComplexityAlami, HassaneLehoux, PascaleAuclair, Yannickde Guise, MichèleGagnon, Marie-PierreShaw, JamesRoy, DenisFleet, RichardAg Ahmed, Mohamed AliFortin, Jean-Paul Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and efficiency of care and services and to build learning and value-based health systems. Many studies have examined the technical performance of AI within an experimental context. These studies provide limited insights into the issues that its use in a real-world context of care and services raises. To help decision makers address these issues in a systemic and holistic manner, this viewpoint paper relies on the health technology assessment core model to contrast the expectations of the health sector toward the use of AI with the risks that should be mitigated for its responsible deployment. The analysis adopts the perspective of payers (ie, health system organizations and agencies) because of their central role in regulating, financing, and reimbursing novel technologies. This paper suggests that AI-based systems should be seen as a health system transformation lever, rather than a discrete set of technological devices. Their use could bring significant changes and impacts at several levels: technological, clinical, human and cognitive (patient and clinician), professional and organizational, economic, legal, and ethical. The assessment of AI’s value proposition should thus go beyond technical performance and cost logic by performing a holistic analysis of its value in a real-world context of care and services. To guide AI development, generate knowledge, and draw lessons that can be translated into action, the right political, regulatory, organizational, clinical, and technological conditions for innovation should be created as a first step.https://www.jmir.org/2020/7/e17707
collection DOAJ
language English
format Article
sources DOAJ
author Alami, Hassane
Lehoux, Pascale
Auclair, Yannick
de Guise, Michèle
Gagnon, Marie-Pierre
Shaw, James
Roy, Denis
Fleet, Richard
Ag Ahmed, Mohamed Ali
Fortin, Jean-Paul
spellingShingle Alami, Hassane
Lehoux, Pascale
Auclair, Yannick
de Guise, Michèle
Gagnon, Marie-Pierre
Shaw, James
Roy, Denis
Fleet, Richard
Ag Ahmed, Mohamed Ali
Fortin, Jean-Paul
Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
Journal of Medical Internet Research
author_facet Alami, Hassane
Lehoux, Pascale
Auclair, Yannick
de Guise, Michèle
Gagnon, Marie-Pierre
Shaw, James
Roy, Denis
Fleet, Richard
Ag Ahmed, Mohamed Ali
Fortin, Jean-Paul
author_sort Alami, Hassane
title Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
title_short Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
title_full Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
title_fullStr Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
title_full_unstemmed Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity
title_sort artificial intelligence and health technology assessment: anticipating a new level of complexity
publisher JMIR Publications
series Journal of Medical Internet Research
issn 1438-8871
publishDate 2020-07-01
description Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and efficiency of care and services and to build learning and value-based health systems. Many studies have examined the technical performance of AI within an experimental context. These studies provide limited insights into the issues that its use in a real-world context of care and services raises. To help decision makers address these issues in a systemic and holistic manner, this viewpoint paper relies on the health technology assessment core model to contrast the expectations of the health sector toward the use of AI with the risks that should be mitigated for its responsible deployment. The analysis adopts the perspective of payers (ie, health system organizations and agencies) because of their central role in regulating, financing, and reimbursing novel technologies. This paper suggests that AI-based systems should be seen as a health system transformation lever, rather than a discrete set of technological devices. Their use could bring significant changes and impacts at several levels: technological, clinical, human and cognitive (patient and clinician), professional and organizational, economic, legal, and ethical. The assessment of AI’s value proposition should thus go beyond technical performance and cost logic by performing a holistic analysis of its value in a real-world context of care and services. To guide AI development, generate knowledge, and draw lessons that can be translated into action, the right political, regulatory, organizational, clinical, and technological conditions for innovation should be created as a first step.
url https://www.jmir.org/2020/7/e17707
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