ReviewBMC medical ethics2023
Data-driven research and healthcare: public trust, data governance and the NHS.
Review in BMC medical ethics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 28 citations in OpenAlex.
- Blockchain for Digital Health Governance: Evidence Gap Map and Scoping Review.Journal of medical Internet research · 2026Article
- Attitudes of Longitudinal Study Participants and Members of the Public Towards Data Sharing for Secondary Research: A Survey Based Approach.Journal of empirical research on human research ethics : JERHRE · 2026Article
- The 'Ghost in the Shell' of NHS Patient Data Policies: News Media on care.data's Haunting of the General Practice Data for Planning and Research.Sociology of health & illness · 2026Article
- Operationalizing transparency regarding the use of health data for research: a cross-sectional survey of citizens' perspectives.BMC public health · 2026Article
- Perspectives of young people on the use of neonatal data in the UK national neonatal research database: a patient and public involvement project.BMJ paediatrics open · 2026Article
- Review
- Multi-heterogeneous data fusion for enterprise data asset valuation in public health policy context.Frontiers in public health · 2026Article
- Mapping Non-Monetary Values in Data Sharing: Development and Validation of an SSH Framework Across Sectors.Open research Europe · 2026Article
- Perceptions and Awareness of Healthcare Professionals Regarding FAIR Data Principles and Health Data Sharing in Saudi Arabia.Healthcare (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Digital Self-Diagnosis Tools: A Narrative Overview of Reviews.Mayo Clinic proceedings. Digital health · 2025Review
- The value of large-scale programmes in human genomics.European journal of human genetics : EJHG · 2025Article
- Improving transparency in data access processes: Developing best practice standards and promoting system-wide change through a competitive funding call.International journal of population data science · 2025Article
- Population health management through human phenotype ontology with policy for ecosystem improvement.Frontiers in artificial intelligence · 2025Article
- Challenges in understanding inequities in help-seeking for possible cancer symptoms.BMC global and public health · 2024Review
- Secondary Use of Health Data for Medical AI: A Cross-Regional Examination of Taiwan and the EU.Asian bioethics review · 2024Article
- Ethical and social implications of public-private partnerships in the context of genomic/big health data collection.European journal of human genetics : EJHG · 2024Article
- Economic Rationality in Decision-Making Regarding Newborn Screening: A Case Study in Quebec.International journal of neonatal screening · 2024Article
- Awareness, Attitudes and Willingness to Donate Biological Samples to a Biobank: A Survey of a Representative Sample of Polish Citizens.Healthcare (Basel, Switzerland) · 2023Article
- Correction to: Data-driven research and healthcare: public trust, data governance and the NHS.BMC medical ethics · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been introduced in recent years. In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader 'health and wealth' agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.