Evidence map›Paper›PMID 37422629›Full record

ArticleBMC medical ethics2023

Artificial intelligence and medical research databases: ethical review by data access committees.

Francis McKay, Bethany J Williams, Graham Prestwich, Daljeet Bansal, Darren Treanor, Nina Hallowell

Open access · goldAbstract read
In one paragraph

Article in BMC medical ethics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

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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

6 authors at 5 institutions in 2 countries.

Francis McKayPopulation Health Sciences Institute, University of Newcastle, NE2 4AX, Newcastle Upon Tyne, UK. francis.mckay@newcastle.ac.uk.ORCID 0000-0002-3177-9446
Bethany J WilliamsNational Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF, UK.
Graham PrestwichYorkshire and Humber Academic Health Science Network, Unit 1, Calder Close, Calder Park, Wakefield, WF4 3BA, UK.
Daljeet BansalNational Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF, UK.
Darren TreanorNational Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF, UK.
Nina HallowellThe Ethox Centre and the Wellcome Centre for Ethics and Humanities, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK.
Leeds Teaching Hospitals NHS Trust · GBLinköping University · SENewcastle University · GBUniversity of Oxford · GBYorkshire & Humber Academic Health Science Network · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt has been argued that ethics review committees-e.g., Research Ethics Committees, Institutional Review Boards, etc.- have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data. MAIN BODY: Focusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work.

conclusionData access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise.

Indexed as

Artificial IntelligenceBiomedical ResearchEthical ReviewEthics CommitteesEthics Committees, ResearchHumansInformation DisseminationArtificial intelligenceData access committeesEthical expertiseEthical reviewHealth data repositoriesMedical research databasesPublic involvementResearch ethics committees

Identifiers

PMID37422629
PMCPMC10329342
OpenAlexW4383621779

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.