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Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond

The last 6 years have seen sustained investment in health data science in the United Kingdom and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and well‐being. How...

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Autores principales: Ford, Elizabeth, Boyd, Andy, Bowles, Juliana K.F., Havard, Alys, Aldridge, Robert W., Curcin, Vasa, Greiver, Michelle, Harron, Katie, Katikireddi, Vittal, Rodgers, Sarah E., Sperrin, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628981/
https://www.ncbi.nlm.nih.gov/pubmed/31317072
http://dx.doi.org/10.1002/lrh2.10191
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author Ford, Elizabeth
Boyd, Andy
Bowles, Juliana K.F.
Havard, Alys
Aldridge, Robert W.
Curcin, Vasa
Greiver, Michelle
Harron, Katie
Katikireddi, Vittal
Rodgers, Sarah E.
Sperrin, Matthew
author_facet Ford, Elizabeth
Boyd, Andy
Bowles, Juliana K.F.
Havard, Alys
Aldridge, Robert W.
Curcin, Vasa
Greiver, Michelle
Harron, Katie
Katikireddi, Vittal
Rodgers, Sarah E.
Sperrin, Matthew
author_sort Ford, Elizabeth
collection PubMed
description The last 6 years have seen sustained investment in health data science in the United Kingdom and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and well‐being. However, opportunities made possible through the innovative use of data are still not being fully realised, resulting in research inefficiencies and avoidable health harms. In this paper, we identify the most important barriers to achieving higher productivity in health data science. We then draw on previous research, domain expertise, and theory to outline how to go about overcoming these barriers, applying our core values of inclusivity and transparency. We believe a step change can be achieved through meaningful stakeholder involvement at every stage of research planning, design, and execution and team‐based data science, as well as harnessing novel and secure data technologies. Applying these values to health data science will safeguard a social licence for health data research and ensure transparent and secure data usage for public benefit.
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spelling pubmed-66289812019-07-17 Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond Ford, Elizabeth Boyd, Andy Bowles, Juliana K.F. Havard, Alys Aldridge, Robert W. Curcin, Vasa Greiver, Michelle Harron, Katie Katikireddi, Vittal Rodgers, Sarah E. Sperrin, Matthew Learn Health Syst Commentary The last 6 years have seen sustained investment in health data science in the United Kingdom and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and well‐being. However, opportunities made possible through the innovative use of data are still not being fully realised, resulting in research inefficiencies and avoidable health harms. In this paper, we identify the most important barriers to achieving higher productivity in health data science. We then draw on previous research, domain expertise, and theory to outline how to go about overcoming these barriers, applying our core values of inclusivity and transparency. We believe a step change can be achieved through meaningful stakeholder involvement at every stage of research planning, design, and execution and team‐based data science, as well as harnessing novel and secure data technologies. Applying these values to health data science will safeguard a social licence for health data research and ensure transparent and secure data usage for public benefit. John Wiley and Sons Inc. 2019-03-25 /pmc/articles/PMC6628981/ /pubmed/31317072 http://dx.doi.org/10.1002/lrh2.10191 Text en © 2019 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Commentary
Ford, Elizabeth
Boyd, Andy
Bowles, Juliana K.F.
Havard, Alys
Aldridge, Robert W.
Curcin, Vasa
Greiver, Michelle
Harron, Katie
Katikireddi, Vittal
Rodgers, Sarah E.
Sperrin, Matthew
Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title_full Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title_fullStr Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title_full_unstemmed Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title_short Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond
title_sort our data, our society, our health: a vision for inclusive and transparent health data science in the united kingdom and beyond
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628981/
https://www.ncbi.nlm.nih.gov/pubmed/31317072
http://dx.doi.org/10.1002/lrh2.10191
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