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H2020Individual fellowship2015–2017

BIMEDA · Big Medical Data Use in Primary Care: an ethnographic, socio-technical, investigation of challenges and opportunities

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2015-08-01 → 2017-08-31
EU contribution
€195,455
Participants
1
Scheme
MSCA-IF-EF-ST

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Results in brief

Big Medical Data Use in Primary Care: an ethnographic, socio-technical, investigation of challenges and opportunities

Big medical data analytics is a new and unique opportunity for national health systems to reduce costs and improve population health management. Processing and analysis of vast amounts of medical histories from electronic health records can provide researchers, clinicians, policy makers and private health companies with invaluable insights into health and illness. New treatments, medication regimens and medical technologies can then be developed based on more accurate cost/benefit analyses. Importantly, it constitutes national health systems’ engines of economic growth. However, there are also social, legal and ethical concerns about personal health information, around issues of informed consent, data security and algorithmic healthcare provision. BIMEDA aimed to elaborate a theoretical framework for critically analysing big data analytics social, technical and ethical challenges in primary care, via mapping of the controversy about the care.data initiative by NHS England in the UK, qualitative study of organisations conducting big primary care data analytics, GPs who obtain informed consent and citizens who opt out from such big data initiatives. The three main objectives were: 1. Map controversy around open primary care data and informed consent of care.data 2. Identify challenges in: Technical maintenance of big primary care datasets Anonymisation of electronic patient records for big data analytics Analysis of big primary care datasets Integration of primary care datasets with national healthcare databases Obtaining informed consent by GPs for individual patients to upload their health record to big primary care databases 3. Identify why individual patients opt out from big primary care databases

Data: CORDIS, © European Union

Project objective

Big medical data analytics is a new and unique opportunity for national health systems to reduce costs and improve population health management. The processing of vast amounts of medical histories from electronic patient records can provide researchers, clinicians, policy makers and private health companies with invaluable insights into all aspects of health and illness. New treatments, medication regimens and medical technologies can then be developed based on more accurate cost/benefit analyses. Importantly, it constitutes national health systems engines of economic growth. The European Commission is actively promoting a ‘Digital Agenda for Europe’, where more ‘Open (Government) Data’ will support and accelerate the development of ‘A Thriving Data-Driven Economy’. However, the European Agency for Fundamental Rights is working to address social, legal and ethical implications from surveillance activities and data protection mishaps, particularly for personal health information. The aim of the BIMEDA project is to elaborate a theoretical framework for critically analysing social, technical and ethical challenges from big medical data analytics, through the mapping of the data protection controversy of the Care.data programme in England and the ethnographic study of an academic and a private organisation that collaborate to collect and analyse big primary care data analytics. It brings together a talented researcher with background in qualitative research of clinical information systems’ implementation and use from a Science and Technology Studies perspective to work with an internationally renowned host institution (University of Nottingham) in big primary care data analytics and, healthcare organisations and (Horizon) Digital Economy research in order to identify and clarify, for policy-makers and the public, possibilities, limitations, assumptions and biases in research, knowledge production and ethical conduct.

Original text from CORDIS.

Participants

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Data: CORDIS, © European Union