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Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research
With one million people treated every 36 hours, routinely collected UK National Health Service (NHS) health data has huge potential for medical research. Advances in data acquisition from electronic patient records (EPRs) means such data are increasingly digital and can be anonymised for research pu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Gunther Eysenbach
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319083/ https://www.ncbi.nlm.nih.gov/pubmed/25586934 http://dx.doi.org/10.2196/medinform.3525 |
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author | Williams, Hawys Spencer, Karen Sanders, Caroline Lund, David Whitley, Edgar A Kaye, Jane Dixon, William G |
author_facet | Williams, Hawys Spencer, Karen Sanders, Caroline Lund, David Whitley, Edgar A Kaye, Jane Dixon, William G |
author_sort | Williams, Hawys |
collection | PubMed |
description | With one million people treated every 36 hours, routinely collected UK National Health Service (NHS) health data has huge potential for medical research. Advances in data acquisition from electronic patient records (EPRs) means such data are increasingly digital and can be anonymised for research purposes. NHS England’s care.data initiative recently sought to increase the amount and availability of such data. However, controversy and uncertainty following the care.data public awareness campaign led to a delay in rollout, indicating that the success of EPR data for medical research may be threatened by a loss of patient and public trust. The sharing of sensitive health care data can only be done through maintaining such trust in a constantly evolving ethicolegal and political landscape. We propose that a dynamic consent model, whereby patients can electronically control consent through time and receive information about the uses of their data, provides a transparent, flexible, and user-friendly means to maintain public trust. This could leverage the huge potential of the EPR for medical research and, ultimately, patient and societal benefit. |
format | Online Article Text |
id | pubmed-4319083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Gunther Eysenbach |
record_format | MEDLINE/PubMed |
spelling | pubmed-43190832015-02-13 Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research Williams, Hawys Spencer, Karen Sanders, Caroline Lund, David Whitley, Edgar A Kaye, Jane Dixon, William G JMIR Med Inform Viewpoint With one million people treated every 36 hours, routinely collected UK National Health Service (NHS) health data has huge potential for medical research. Advances in data acquisition from electronic patient records (EPRs) means such data are increasingly digital and can be anonymised for research purposes. NHS England’s care.data initiative recently sought to increase the amount and availability of such data. However, controversy and uncertainty following the care.data public awareness campaign led to a delay in rollout, indicating that the success of EPR data for medical research may be threatened by a loss of patient and public trust. The sharing of sensitive health care data can only be done through maintaining such trust in a constantly evolving ethicolegal and political landscape. We propose that a dynamic consent model, whereby patients can electronically control consent through time and receive information about the uses of their data, provides a transparent, flexible, and user-friendly means to maintain public trust. This could leverage the huge potential of the EPR for medical research and, ultimately, patient and societal benefit. Gunther Eysenbach 2015-01-13 /pmc/articles/PMC4319083/ /pubmed/25586934 http://dx.doi.org/10.2196/medinform.3525 Text en ©Hawys Williams, Karen Spencer, Caroline Sanders, David Lund, Edgar A Whitley, Jane Kaye, William G Dixon. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 13.01.2015. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Viewpoint Williams, Hawys Spencer, Karen Sanders, Caroline Lund, David Whitley, Edgar A Kaye, Jane Dixon, William G Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title | Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title_full | Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title_fullStr | Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title_full_unstemmed | Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title_short | Dynamic Consent: A Possible Solution to Improve Patient Confidence and Trust in How Electronic Patient Records Are Used in Medical Research |
title_sort | dynamic consent: a possible solution to improve patient confidence and trust in how electronic patient records are used in medical research |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319083/ https://www.ncbi.nlm.nih.gov/pubmed/25586934 http://dx.doi.org/10.2196/medinform.3525 |
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