ArticleGlobal & regional health technology assessment
Use of artificial intelligence to draft a mini-HTA report on a new medical device belonging to class IIb-III.
Article in Global & regional health technology assessment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Comments on: Use of artificial intelligence to draft a mini-HTA report on a new medical device belonging to class IIb-III.Global & regional health technology assessmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid evolution of artificial intelligence (AI) in the pharmaceutical and medical device (MD) sectors has prompted interest in its potential role in supporting health technology assessment (HTA). This editorial presents an innovative project aimed at facilitating and expanding HTA activities for high-risk MDs (Class IIb-III) in Italy, where structured HTA processes for MDs are inconsistently implemented. The project centers on a freely accessible AI-based web tool designed to generate preliminary mini-HTA reports. The tool operates through two steps: users provide essential device information via an online form, and ChatGPT produces a structured draft report, including PICO statements, coverage of the nine EUnetHTA domains, and a preliminary summary of relevant PubMed evidence. Although these AI-generated reports are imperfect and require expert verification and refinement, they offer substantial practical advantages by reducing the initial workload and enabling rapid production of a first draft-within minutes rather than hours. The project includes detailed operational instructions and real application examples, such as an artificial iris device, presented in supplementary appendices. Future developments include the release of an English-language version to support broader international use. While AI cannot replace expert judgment, the editorial highlights its value as an accelerative tool that can streamline early HTA steps and promote more systematic evaluation of MDs across Italian regions. Continued iterative use is expected to improve system performance and enhance integration into HTA workflows.
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What OpenQuestion holds
Registered trials
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.