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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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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. |
format | Online Article Text |
id | pubmed-6628981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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