Evidence map›Paper›PMID 34330796›Full record

ArticleJournal of medical ethics2023

Data for sale: trust, confidence and sharing health data with commercial companies.

Mackenzie Graham

Open access · hybridAbstract read
In one paragraph

Article in Journal of medical ethics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 35 citations in OpenAlex.

  1. Expanding the boundaries of previously obtained informed consent in research: Views from participants in the Personalised Risk-based Mammascreening study.Health expectations : an international journal of public participation in health care and health policy · 2023
    Trial
  2. Article
  3. Review
  4. Review
  5. Article
  6. The need for clear medical data ownership laws.Journal of translational medicine · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. A Taxonomy for Health Information Systems.Journal of medical Internet research · 2024
    Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

1 author at 1 institution in 1 country.

Mackenzie GrahamWellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK mackenzie.graham@philosophy.ox.ac.uk.ORCID http://orcid.org/0000-0001-6870-1370
University of Oxford · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Powered by 'big health data' and enormous gains in computing power, artificial intelligence and related technologies are already changing the healthcare landscape. Harnessing the potential of these technologies will necessitate partnerships between health institutions and commercial companies, particularly as it relates to sharing health data. The need for commercial companies to be trustworthy users of data has been argued to be critical to the success of this endeavour. I argue that this approach is mistaken. Our interactions with commercial companies need not, and should not, be based on trust. Rather, they should be based on confidence. I begin by elucidating the differences between trust, reliability, and confidence, and argue that trust is not the appropriate attitude to adopt when it comes to sharing data with commercial companies. I argue that what we really should want is confidence in a system of data sharing. I then provide an outline of what a confidence-worthy system of data sharing with commercial companies might look like, and conclude with some remarks about the role of trust within this system.

Indexed as

ConfidentialityPrivacyArtificial IntelligenceHumansReproducibility of ResultsTrustconfidentiality/privacydatabases- geneticethicsethics- researchinformation technology

Identifiers

PMID34330796
PMCPMC10359563
OpenAlexW3184999087

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.