ArticleBMC health services research2015
The use of electronic patient records for medical research: conflicts and contradictions.
Article in BMC health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 6 of them syntheses that pooled it.
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
15 citing papers in PubMed, 6 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Ethical issues in biomedical research using electronic health records: a systematic review.Medicine, health care, and philosophy · 2021Pooled it
- Application of normalisation process theory in understanding implementation processes in primary care settings in the UK: a systematic review.BMC family practice · 2020Pooled it
- Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review.Implementation science : IS · 2018Pooled it
- "Giving something back": A systematic review and ethical enquiry into public views on the use of patient data for research in the United Kingdom and the Republic of Ireland.Wellcome open research · 2018Pooled it
- Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.BMC medical informatics and decision making · 2017Pooled it
- Trial
- Accessing medical records for research in South African public hospitals: a reflective narrative.BMC health services research · 2025Article
- Understanding the challenges of identifying, supporting, and signposting patients with alcohol use disorder in secondary care hospitals, post COVID-19: a qualitative analysis from the North East and North Cumbria, England.BMC health services research · 2024Article
- Applying Structural Equation Modelling to Understand the Implementation of Social Distancing in the Professional Lives of Healthcare Workers.International journal of environmental research and public health · 2023Article
- Using Normalisation Process Theory (NPT) to develop an intervention to improve referral and uptake rates for self-management education for patients with type 2 diabetes in UK primary care.BMC health services research · 2022Article
- Identifying primary care datasets and perspectives on their secondary use: a survey of Australian data users and custodians.BMC medical informatics and decision making · 2022Article
- Consumer-Mediated Data Exchange for Research: Current State of US Law, Technology, and Trust.JMIR medical informatics · 2019Article
- Perceptions of the uses of routine general practice data beyond individual care in England: a qualitative study.BMJ open · 2018Article
- Factors affecting willingness to share electronic health data among California consumers.BMC medical ethics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe use of electronic patient records for medical research is extremely topical. The Clinical Practice Research Datalink (CRPD), the English NHS observational data and interventional research service, was launched in April 2012. The CPRD has access to, and facilities to link, many healthcare related datasets. The CPRD is partially based on learning from the Health Research Support Service (HRSS), which was used to test the technical and practical aspects of downloading and linking electronic patient records for research. Questions around the feasibility and acceptability of implementing and integrating the processes necessary to enable electronic patient records to be used for the purposes of research remain.
methodsFocus groups and interviews were conducted with a total of 50 patients and 7 staff from the two English GP practices involved in piloting the HRSS, supplemented with 11 interviews with key stakeholders. Emergent themes were mapped on to the constructs of normalization process theory (NPT) to consider the ways in which sense was made of the work of implementing and integrating the HRSS.
resultsThe NPT analysis demonstrated a lack of commitment to, and engagement with, the HRSS on the part of patients, whilst the commitment of doctors and practice staff was to some extent mitigated by concerns about issues of governance and consent, particularly in relation to downloading electronic patient records with associated identifiers.
conclusionsAlthough the CPRD is presented as a benign, bureaucratic process, perceptions by patients and staff of inherent contradictions with centrally held values of information governance and consent in downloading and linking electronic patient records for research remains a barrier to implementation. It is likely that conclusions reached about the problems of balancing the contradictions inherent in sharing what can be perceived as a private resource for the public good are globally transferrable.
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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.