Evidence map›Paper›PMID 38438199›Full record

ArticleBJGP open2024

NHS national data opt-outs: trends and potential consequences for health data research.

John Tazare, Alasdair D Henderson, Jessica Morley, Helen A Blake, Helen I McDonald, Elizabeth J Williamson, Helen Strongman

Abstract read
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Article in BJGP open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

John TazareFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID https://orcid.org/0000-0002-7194-2615
Alasdair D HendersonFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Jessica MorleyOxford Internet Institute, University of Oxford, Oxford, United Kingdom.
Helen A BlakeFaculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Helen I McDonaldDepartment of Life Sciences, University of Bath, Bath, United Kingdom.
Elizabeth J WilliamsonFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Helen StrongmanFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom helen.strongman@lshtm.ac.uk.ORCID https://orcid.org/0000-0001-8739-4601

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe English NHS data opt-out allows people to prevent use of their health data for purposes other than direct care. In 2021, the number of opt-outs increased in response to government-led proposals to create a centralised pseudonymised primary care record database.

aimTo describe the potential impact of NHS national data opt-outs in 2021 on health data research. DESIGN &

settingWe conducted a descriptive analysis of opt-outs using publicly available data and the potential consequences on research are discussed.

methodTrends in opt-outs in England were described by age, sex, and region. Using a hypothetical study, we explored statistical and epidemiological implications of opt-outs.

resultsDuring the lead up to a key government-led deadline for registering opt-outs (from 31 May 2021-30 June 2021), 1 339 862 national data opt-outs were recorded; increasing the percentage of opt-outs in England from 2.77% to 4.97% of the population. Among females, percentage opt-outs increased by 83% (from 3.02% to 5.53%) compared with 76% in males (from 2.51% to 4.41%). Across age groups, the highest relative increase was among people aged 40-49 years, which rose from 2.89% to 6.04%. Considerable geographical variation was not clearly related to deprivation. Key research consequences of opt-outs include reductions in sample size and unpredictable distortion of observed measures of the frequency of health events or associations between these events.

conclusionOpt-out rates varied by age, sex, and place. The impact of this and variation by other characteristics on research is not quantifiable. Potential effects of opt-outs on research and consequences for health policies based on this research must be considered when creating future opt-out solutions.

Indexed as

databaseepidemiologylarge database researchprimary health care

Identifiers

PMID38438199
PMCPMC11523503

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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.