Evidence map›Paper›PMID 39347259›Full record

ArticleCureus2024

Artificial Intelligence-Powered Surgical Consent: Patient Insights.

Alex Teasdale, Laura Mills, Rhodri Costello

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. The ACPGBI AI taskforce report: A mixed-methods roadmap for AI in colorectal surgery.Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland · 2025
    Article
  5. Article
  6. Article
  7. Review
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

3 authors.

Alex TeasdaleEar Nose Throat, Morriston Hospital, Swansea, GBR.
Laura MillsGeneral Practice, Dyfed Road Surgery, Swansea, GBR.
Rhodri CostelloEar Nose Throat, Morriston Hospital, Swansea, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction The integration of artificial intelligence (AI) in healthcare has revolutionized patient interactions and service delivery. AI's role extends from supporting clinical diagnostics and enhancing operational efficiencies to potentially improving informed consent processes in surgical settings. This study investigates the application of AI, particularly large language models like OpenAI's ChatGPT, in facilitating surgical consent, focusing on patient understanding, satisfaction, and trust. Methods We employed a mixed-methods approach involving 86 participants, including laypeople and medical staff, who engaged in a simulated AI-driven consent process for a tonsillectomy. Participants interacted with ChatGPT-4, which provided detailed procedure explanations, risks, and benefits. Post-interaction, participants completed a survey assessing their experience through quantitative and qualitative measures. Results Participants had a cautiously optimistic response to AI in the surgical consent process. Notably, 71% felt adequately informed, 86% found the information clear, and 71% felt they could make informed decisions. Overall, 71% were satisfied, 57% felt respected and confident, and 57% would recommend it, indicating areas needing refinement. However, concerns about data privacy and the lack of personal interaction were significant, with only 42% reassured about the security of their data. The standardization of information provided by AI was appreciated for potentially reducing human error, but the absence of empathetic human interaction was noted as a drawback. Discussion While AI shows promise in enhancing the consistency and comprehensiveness of information delivered during the consent process, significant challenges remain. These include addressing data privacy concerns and bridging the gap in personal interaction. The potential for AI to misinform due to system "hallucinations" or inherent biases also needs consideration. Future research should focus on refining AI interactions to support more nuanced and empathetic engagements, ensuring that AI supplements rather than replacing human elements in healthcare. Conclusion The integration of AI into surgical consent processes could standardize and potentially improve the delivery of information but must be balanced with efforts to maintain the critical human elements of care. Collaborative efforts between developers, clinicians, and ethicists are essential to optimize AI use, ensuring it complements the traditional consent process while enhancing patient satisfaction and trust.

Indexed as

ai in healthcareartificial intelligencechatgptconsent processdata privacyhealthcare innovationmedical ethicspatient autonomypatient engagementsurgical consent

Identifiers

PMID39347259
PMCPMC11438496

What OpenQuestion holds

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LicenceCC BY
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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.