Bibliographic Details
| Title: |
Artificial Intelligence and Health Technology Assessment: Anticipating a New Level of Complexity |
| 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 |
| Source: |
Journal of Medical Internet Research, Vol 22, Iss 7, p e17707 (2020) |
| Publisher Information: |
JMIR Publications, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Computer applications to medicine. Medical informatics
LCC:Public aspects of medicine |
| Subject Terms: |
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1438-8871 |
| Relation: |
https://www.jmir.org/2020/7/e17707; https://doaj.org/toc/1438-8871 |
| DOI: |
10.2196/17707 |
| Access URL: |
https://doaj.org/article/ce6511aff21246f998aa9d78b34a436e |
| Accession Number: |
edsdoj.6511aff21246f998aa9d78b34a436e |
| Database: |
Directory of Open Access Journals |
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