Patient perceptions on data sharing and applying artificial intelligence to healthcare data: a cross sectional survey
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Published version
Author(s)
Aggarwal, Ravi
Farag, Soma
Martin, guy
Ashrafian, hutan
Darzi, ara
Type
Journal Article
Abstract
Background:
Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to healthcare. However, for it to be successful, large amounts of health data are required for the training and testing of algorithms. Data sharing for this purpose is controversial, therefore it is imperative to understand patient perceptions on this.
Objective:
To understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.
Methods:
A cross-sectional survey with patients was conducted at a large multi-site teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.
Results:
A total of 408 participants completed the survey. Respondents had low levels of prior knowledge of AI in general. Most were comfortable with sharing health data with the NHS (77·9%) or universities (65·7%), but far fewer with commercial organisations such as technology companies (26·4%). The majority endorsed AI research on healthcare data (76·8%) and healthcare imaging (76·4%) in a university setting, providing that concerns about privacy, re-identification of anonymised health care data and consent processes were addressed.
Conclusions:
There is significant variance in patient perceptions, levels of support, and understanding of health data research and AI. There is a need for greater public engagement and debate to ensure the acceptability of AI research and its successful integration into clinical practice in the future.
Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to healthcare. However, for it to be successful, large amounts of health data are required for the training and testing of algorithms. Data sharing for this purpose is controversial, therefore it is imperative to understand patient perceptions on this.
Objective:
To understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.
Methods:
A cross-sectional survey with patients was conducted at a large multi-site teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.
Results:
A total of 408 participants completed the survey. Respondents had low levels of prior knowledge of AI in general. Most were comfortable with sharing health data with the NHS (77·9%) or universities (65·7%), but far fewer with commercial organisations such as technology companies (26·4%). The majority endorsed AI research on healthcare data (76·8%) and healthcare imaging (76·4%) in a university setting, providing that concerns about privacy, re-identification of anonymised health care data and consent processes were addressed.
Conclusions:
There is significant variance in patient perceptions, levels of support, and understanding of health data research and AI. There is a need for greater public engagement and debate to ensure the acceptability of AI research and its successful integration into clinical practice in the future.
Date Issued
2021-07-08
Date Acceptance
2021-07-05
Citation
Journal of Medical Internet Research, 2021, 23 (8), pp.1-12
ISSN
1438-8871
Publisher
JMIR Publications
Start Page
1
End Page
12
Journal / Book Title
Journal of Medical Internet Research
Volume
23
Issue
8
Copyright Statement
©Ravi Aggarwal, Soma Farag, Guy Martin, Hutan Ashrafian, Ara Darzi. Originally published in the Journal of Medical Internet
Research (https://www.jmir.org), 26.08.2021. 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.
Research (https://www.jmir.org), 26.08.2021. 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.
License URL
Identifier
https://www.jmir.org/2021/8/e26162
Subjects
artificial intelligence
data sharing
health data
patient perception
privacy
08 Information and Computing Sciences
11 Medical and Health Sciences
17 Psychology and Cognitive Sciences
Medical Informatics
Publication Status
Published
Date Publish Online
2021-07-08