Evidence map›Paper›PMID 36653763›Full record

ArticleBMC public health2023

Sharing real-world data for public benefit: a qualitative exploration of stakeholder views and perceptions.

Susan Baxter, Matthew Franklin, Annette Haywood, Tony Stone, Monica Jones, Suzanne Mason, Kamil Sterniczuk

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
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

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Attitudes towards data access and sharing health data for research: a case study of Australian data custodian perspectives.Health information management : journal of the Health Information Management Association of Australia · 2026
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  3. Review
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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 at 2 institutions in 1 country.

Susan BaxterSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK. s.k.baxter@sheffield.ac.uk.ORCID 0000-0002-6034-5495
Matthew FranklinSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK.ORCID 0000-0002-2774-9439
Annette HaywoodSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK.ORCID 0000-0002-5824-3043
Tony StoneSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK.ORCID 0000-0002-0167-3800
Monica JonesProfessional Services, University of Leeds, Woodhouse Lane, LS29JT, Leeds, England.ORCID 0000-0001-7929-2808
Suzanne MasonSchool of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK.ORCID 0000-0002-1701-0577
Kamil SterniczukPublic advisor, Sheffield, England.
University of Sheffield · GBUniversity of Leeds · GB

Funding

National Institute for Health and Care Research 133634
6 · The paper itself

Abstract

backgroundThere has been an increasing interest in the use of "real-world" data to inform care decision making that could lead to public health benefit. Routinely collected service and activity data associated with the administration of care services and service-users (such as electronic health records or electronic social care records), hold potential to better inform effective and responsive decision-making about health and care services provided to national and local populations. This study sought to gain an in-depth understanding regarding the potential to unlock real world data that was held in individual organisations, to better inform public health decision-making. This included sharing data between and within health service providers and local governing authorities, but also with university researchers to inform the evidence base.

methodsWe used qualitative methods and carried out a series of online workshops and interviews with stakeholders (senior-level decision-makers and service leads, researchers, data analysts, those with a legal and governance role, and members of the public). We identified recurring themes in initial workshops, and explored these with participants in subsequent workshops. By this iterative process we further refined the themes identified, compared views and perceptions amongst different stakeholder groups, and developed recommendations for action.

resultsOur study identified key elements of context and timing, the need for a different approach, and obstacles including governmental and legal, organisational features, and process factors which adversely affect the sharing of real world data. The findings also highlighted a need for improved communication about data for secondary uses to members of the public.

conclusionThe Covid-19 pandemic context and changes to organisational structures in the health service in England have provided opportunities to address data sharing challenges. Change at national and local level is required, within current job roles and generating new jobs roles focused on the use and sharing of real-world data. The study suggests that actions can be taken to unlock the potential of real-world data for public health benefit, and provides a series of recommendations at a national level, for organisational leaders, those in data roles and those in public engagement roles.

Indexed as

COVID-19PandemicsCommunicationEnglandHumansInformation DisseminationData sharingInformation governanceIntegrated carePublic healthQualitativeReal world dataRoutine data

Identifiers

PMID36653763
PMCPMC9849106
OpenAlexW4317372231

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.