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Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint
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 modal...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185357/ https://www.ncbi.nlm.nih.gov/pubmed/35617003 http://dx.doi.org/10.2196/35951 |
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author | Clay, Ieuan Cormack, Francesca Fedor, Szymon Foschini, Luca Gentile, Giovanni van Hoof, Chris Kumar, Priya Lipsmeier, Florian Sano, Akane Smarr, Benjamin Vandendriessche, Benjamin De Luca, Valeria |
author_facet | Clay, Ieuan Cormack, Francesca Fedor, Szymon Foschini, Luca Gentile, Giovanni van Hoof, Chris Kumar, Priya Lipsmeier, Florian Sano, Akane Smarr, Benjamin Vandendriessche, Benjamin De Luca, Valeria |
author_sort | Clay, Ieuan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9185357 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-91853572022-06-11 Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint Clay, Ieuan Cormack, Francesca Fedor, Szymon Foschini, Luca Gentile, Giovanni van Hoof, Chris Kumar, Priya Lipsmeier, Florian Sano, Akane Smarr, Benjamin Vandendriessche, Benjamin De Luca, Valeria J Med Internet Res Viewpoint 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. JMIR Publications 2022-05-26 /pmc/articles/PMC9185357/ /pubmed/35617003 http://dx.doi.org/10.2196/35951 Text en ©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. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Clay, Ieuan Cormack, Francesca Fedor, Szymon Foschini, Luca Gentile, Giovanni van Hoof, Chris Kumar, Priya Lipsmeier, Florian Sano, Akane Smarr, Benjamin Vandendriessche, Benjamin De Luca, Valeria Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title | Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title_full | Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title_fullStr | Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title_full_unstemmed | Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title_short | Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint |
title_sort | measuring health-related quality of life with multimodal data: viewpoint |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185357/ https://www.ncbi.nlm.nih.gov/pubmed/35617003 http://dx.doi.org/10.2196/35951 |
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