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

Elizabeth Ford*, Andy Boyd, Juliana K.F. Bowles, Alys Havard, Robert W. Aldridge, Vasa Curcin, Michelle Greiver, Katie Harron, Vittal Katikireddi, Sarah E. Rodgers, Matthew Sperrin

*Corresponding author for this work

Research output: Contribution to journalComment/debate

19 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article numbere10191
JournalLearning Health Systems
Volume3
Issue number3
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes

Bibliographical note

Funding Information:
This paper is the work of the first cohort of the Farr Institute's ?Future Leaders? scheme. We thank Catherine Goddard, Colin McCowan, George Moulton, Paul Taylor, Athanasios Anastasiou, and Wing-Chau Tung for running the Future Leaders programme and the support of the Farr Institute Directors in providing leadership insights. The Future Leaders programme was funded by the Farr Institute and was financially supported by the authors' institutions or grants. All authors contributed to this paper: with all contributing to the design and framing of this position statement; with E.F., A.B., J.B., A.H., and V.C. editing the paper; all authors contributing substantial sections of the draft, approving the final version, and taking accountability for all aspects of this work.

Funding Information:
This paper is the work of the first cohort of the Farr Institute's “Future Leaders” scheme. We thank Catherine Goddard, Colin McCowan, George Moulton, Paul Taylor, Athanasios Anastasiou, and Wing‐Chau Tung for running the Future Leaders programme and the support of the Farr Institute Directors in providing leadership insights. The Future Leaders programme was funded by the Farr Institute and was financially supported by the authors' institutions or grants. All authors contributed to this paper: with all contributing to the design and framing of this position statement; with E.F., A.B., J.B., A.H., and V.C. editing the paper; all authors contributing substantial sections of the draft, approving the final version, and taking accountability for all aspects of this work.

Publisher Copyright:
© 2019 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan

Keywords

  • citizen-driven science
  • data flows
  • health data science
  • health systems
  • stakeholder involvement
  • transparency

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