Evidence map›Paper›PMID 41782364›Full record

ArticleInternational journal of technology assessment in health care2026

Trust, validation, and accountability: implementing uses of generative artificial intelligence into Health Technology Assessment practice.

Rachael Fleurence, Jagpreet Chhatwal

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. From HTA to the Bedside: Aligning GenAI Validation with Clinical Reality.International journal of technology assessment in health care · 2026
    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

2 authors.

Rachael FleurenceApodeixis Strategies LLC, USA.ORCID https://orcid.org/0000-0002-3526-1732
Jagpreet ChhatwalCenter for Health Technology Assessment, https://ror.org/042nb2s44Mass General Brigham, Harvard Medical School, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 2025 HTAi Global Policy Forum (GPF) report offers a timely and thoughtful synthesis of the opportunities and challenges associated with the use of artificial intelligence (AI), and particularly generative AI (GenAI), in Health Technology Assessment (HTA) (1). Its emphasis on trust, human agency, and risk-based approaches reflects both the maturity of the discussion within the HTA community and a shared recognition that technical capability alone is insufficient for responsible adoption. The report succeeds in articulating a common set of principles and a broadly aligned vision across HTA bodies, life sciences, and other interest holders.

Indexed as

Artificial IntelligenceGenerative Artificial IntelligenceSocial ResponsibilityTechnology Assessment, BiomedicalTrustHumansartificial intelligenceevidence synthesisGenAIgenerative artificial intelligenceHTAmethodssystematic literature reviews

Identifiers

PMID41782364
PMCPMC13125768

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.