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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

Author

Listed:
  • Williams, Hawys
  • Spencer, Karen
  • Sanders, Caroline
  • Lund, David
  • Whitley, Edgar A.
  • Kaye, Jane
  • Dixon, William G.

Abstract

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.

Suggested Citation

  • Williams, Hawys & Spencer, Karen & Sanders, Caroline & Lund, David & Whitley, Edgar A. & Kaye, Jane & Dixon, William G., 2015. "Dynamic consent: a possible solution to improve patient confidence and trust in how electronic patient records are used in medical research," LSE Research Online Documents on Economics 60754, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:60754
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    Cited by:

    1. Martínez-Caro, Eva & Cegarra-Navarro, Juan Gabriel & García-Pérez, Alexeis & Fait, Monica, 2018. "Healthcare service evolution towards the Internet of Things: An end-user perspective," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 268-276.
    2. Videsh Desingh & Baskaran R, 2022. "Internet of Things adoption barriers in the Indian healthcare supply chain: An ISM‐fuzzy MICMAC approach," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 318-351, January.

    More about this item

    Keywords

    dynamic consent; electronic patient record (EPR); medical research; confidentiality; privacy; governance; NHS; data linkage; care.data;
    All these keywords.

    JEL classification:

    • J50 - Labor and Demographic Economics - - Labor-Management Relations, Trade Unions, and Collective Bargaining - - - General

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