Mapping and evaluating national data flows: transparency, privacy, and guiding infrastructural transformation.

Autor:	Zhang J; Institute of Global Health Innovation, Imperial College London, London, UK; Department of Critical Care, Guy's and St Thomas' NHS Foundation Trust, London, UK. Electronic address: joe.zhang@imperial.ac.uk., Morley J; Oxford Internet Institute, University of Oxford, Oxford, UK., Gallifant J; Department of Intensive Care, Imperial College Healthcare NHS Trust, London, UK; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, MA, USA., Oddy C; Department of Anaesthesia, Critical Care and Pain, St George's Healthcare NHS Trust, London, UK., Teo JT; London Medical Imaging and AI Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK; Department of Neurology, King's College Hospital NHS Foundation Trust, London, UK., Ashrafian H; Institute of Global Health Innovation, Imperial College London, London, UK; Leeds University Business School, Leeds, UK., Delaney B; Institute of Global Health Innovation, Imperial College London, London, UK., Darzi A; Institute of Global Health Innovation, Imperial College London, London, UK.
Jazyk:	angličtina
Zdroj:	The Lancet. Digital health [Lancet Digit Health] 2023 Oct; Vol. 5 (10), pp. e737-e748.
DOI:	10.1016/S2589-7500(23)00157-7
Abstrakt:	The importance of big health data is recognised worldwide. Most UK National Health Service (NHS) care interactions are recorded in electronic health records, resulting in an unmatched potential for population-level datasets. However, policy reviews have highlighted challenges from a complex data-sharing landscape relating to transparency, privacy, and analysis capabilities. In response, we used public information sources to map all electronic patient data flows across England, from providers to more than 460 subsequent academic, commercial, and public data consumers. Although NHS data support a global research ecosystem, we found that multistage data flow chains limit transparency and risk public trust, most data interactions do not fulfil recommended best practices for safe data access, and existing infrastructure produces aggregation of duplicate data assets, thus limiting diversity of data and added value to end users. We provide recommendations to support data infrastructure transformation and have produced a website (https://DataInsights.uk) to promote transparency and showcase NHS data assets. Competing Interests: Declaration of interests HA is Chief Scientific Officer of Preemptive Health and Medicine and Flagship Pioneering. JM was paid directly for giving a lecture at Health Education England on the topic of artificial intelligence in the NHS. JM has been a member of the INSIGHT DataTAB for HDR UK. This paper references the Goldacre Review, for which JM was a coauthor. All other authors declare no competing interests. (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Databáze:	MEDLINE
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