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Going beyond the means: Exploring the role of bias from digital determinants of health in technologies

BACKGROUND: In light of recent retrospective studies revealing evidence of disparities in access to medical technology and of bias in measurements, this narrative review assesses digital determinants of health (DDoH) in both technologies and medical formulae that demonstrate either evidence of bias...

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Autores principales: Charpignon, Marie-Laure, Carrel, Adrien, Jiang, Yihang, Kwaga, Teddy, Cantada, Beatriz, Hyslop, Terry, Cox, Christopher E., Haines, Krista, Koomson, Valencia, Dumas, Guillaume, Morley, Michael, Dunn, Jessilyn, Ian Wong, An-Kwok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569586/
https://www.ncbi.nlm.nih.gov/pubmed/37824494
http://dx.doi.org/10.1371/journal.pdig.0000244
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author Charpignon, Marie-Laure
Carrel, Adrien
Jiang, Yihang
Kwaga, Teddy
Cantada, Beatriz
Hyslop, Terry
Cox, Christopher E.
Haines, Krista
Koomson, Valencia
Dumas, Guillaume
Morley, Michael
Dunn, Jessilyn
Ian Wong, An-Kwok
author_facet Charpignon, Marie-Laure
Carrel, Adrien
Jiang, Yihang
Kwaga, Teddy
Cantada, Beatriz
Hyslop, Terry
Cox, Christopher E.
Haines, Krista
Koomson, Valencia
Dumas, Guillaume
Morley, Michael
Dunn, Jessilyn
Ian Wong, An-Kwok
author_sort Charpignon, Marie-Laure
collection PubMed
description BACKGROUND: In light of recent retrospective studies revealing evidence of disparities in access to medical technology and of bias in measurements, this narrative review assesses digital determinants of health (DDoH) in both technologies and medical formulae that demonstrate either evidence of bias or suboptimal performance, identifies potential mechanisms behind such bias, and proposes potential methods or avenues that can guide future efforts to address these disparities. APPROACH: Mechanisms are broadly grouped into physical and biological biases (e.g., pulse oximetry, non-contact infrared thermometry [NCIT]), interaction of human factors and cultural practices (e.g., electroencephalography [EEG]), and interpretation bias (e.g, pulmonary function tests [PFT], optical coherence tomography [OCT], and Humphrey visual field [HVF] testing). This review scope specifically excludes technologies incorporating artificial intelligence and machine learning. For each technology, we identify both clinical and research recommendations. CONCLUSIONS: Many of the DDoH mechanisms encountered in medical technologies and formulae result in lower accuracy or lower validity when applied to patients outside the initial scope of development or validation. Our clinical recommendations caution clinical users in completely trusting result validity and suggest correlating with other measurement modalities robust to the DDoH mechanism (e.g., arterial blood gas for pulse oximetry, core temperatures for NCIT). Our research recommendations suggest not only increasing diversity in development and validation, but also awareness in the modalities of diversity required (e.g., skin pigmentation for pulse oximetry but skin pigmentation and sex/hormonal variation for NCIT). By increasing diversity that better reflects patients in all scenarios of use, we can mitigate DDoH mechanisms and increase trust and validity in clinical practice and research.
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spelling pubmed-105695862023-10-13 Going beyond the means: Exploring the role of bias from digital determinants of health in technologies Charpignon, Marie-Laure Carrel, Adrien Jiang, Yihang Kwaga, Teddy Cantada, Beatriz Hyslop, Terry Cox, Christopher E. Haines, Krista Koomson, Valencia Dumas, Guillaume Morley, Michael Dunn, Jessilyn Ian Wong, An-Kwok PLOS Digit Health Review BACKGROUND: In light of recent retrospective studies revealing evidence of disparities in access to medical technology and of bias in measurements, this narrative review assesses digital determinants of health (DDoH) in both technologies and medical formulae that demonstrate either evidence of bias or suboptimal performance, identifies potential mechanisms behind such bias, and proposes potential methods or avenues that can guide future efforts to address these disparities. APPROACH: Mechanisms are broadly grouped into physical and biological biases (e.g., pulse oximetry, non-contact infrared thermometry [NCIT]), interaction of human factors and cultural practices (e.g., electroencephalography [EEG]), and interpretation bias (e.g, pulmonary function tests [PFT], optical coherence tomography [OCT], and Humphrey visual field [HVF] testing). This review scope specifically excludes technologies incorporating artificial intelligence and machine learning. For each technology, we identify both clinical and research recommendations. CONCLUSIONS: Many of the DDoH mechanisms encountered in medical technologies and formulae result in lower accuracy or lower validity when applied to patients outside the initial scope of development or validation. Our clinical recommendations caution clinical users in completely trusting result validity and suggest correlating with other measurement modalities robust to the DDoH mechanism (e.g., arterial blood gas for pulse oximetry, core temperatures for NCIT). Our research recommendations suggest not only increasing diversity in development and validation, but also awareness in the modalities of diversity required (e.g., skin pigmentation for pulse oximetry but skin pigmentation and sex/hormonal variation for NCIT). By increasing diversity that better reflects patients in all scenarios of use, we can mitigate DDoH mechanisms and increase trust and validity in clinical practice and research. Public Library of Science 2023-10-12 /pmc/articles/PMC10569586/ /pubmed/37824494 http://dx.doi.org/10.1371/journal.pdig.0000244 Text en © 2023 Charpignon et al 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 author and source are credited.
spellingShingle Review
Charpignon, Marie-Laure
Carrel, Adrien
Jiang, Yihang
Kwaga, Teddy
Cantada, Beatriz
Hyslop, Terry
Cox, Christopher E.
Haines, Krista
Koomson, Valencia
Dumas, Guillaume
Morley, Michael
Dunn, Jessilyn
Ian Wong, An-Kwok
Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title_full Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title_fullStr Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title_full_unstemmed Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title_short Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
title_sort going beyond the means: exploring the role of bias from digital determinants of health in technologies
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569586/
https://www.ncbi.nlm.nih.gov/pubmed/37824494
http://dx.doi.org/10.1371/journal.pdig.0000244
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