Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.
care delivery
data integration
digital health
digital measures
digital product
digital therapeutics
digital therapy
digital wellness
drug development
machine learning
multimodal technology
quality of life
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
26 05 2022
26 05 2022
Historique:
received:
23
12
2021
accepted:
25
04
2022
revised:
14
02
2022
entrez:
26
5
2022
pubmed:
27
5
2022
medline:
31
5
2022
Statut:
epublish
Résumé
The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.
Identifiants
pubmed: 35617003
pii: v24i5e35951
doi: 10.2196/35951
pmc: PMC9185357
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e35951Informations de copyright
©Ieuan Clay, Francesca Cormack, Szymon Fedor, Luca Foschini, Giovanni Gentile, Chris van Hoof, Priya Kumar, Florian Lipsmeier, Akane Sano, Benjamin Smarr, Benjamin Vandendriessche, Valeria De Luca. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.05.2022.
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