ArticlePharmacoEconomics - open2026
Cost-Effectiveness of an Artificial Intelligence as a Medical Device (AIaMD) for Triaging Patients Presenting to Primary Care with Concerns that They Have a Skin Cancer: A Modelling Study.
Article in PharmacoEconomics - open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHealth services are struggling to cope with the growing numbers of people coming with skin lesions they are worried could be cancer. Using artificial intelligence (AI) to assist in the triage process is one potential approach. Deep Ensemble for the Recognition of Melanoma (DERM) is one such AI device which has achieved Conformité Européene (CE) Class III regulatory approval in the UK and Europe. The effectiveness and cost-effectiveness of DERM have already been carefully examined post-referral. This study examines the cost-effectiveness of DERM pre-referral in the community setting.
methodsWe modified a decision-analytic model developed for post-referral evaluation of DERM to the community setting. The model compared standard care (SC) with two DERM-based strategies: with second reading (2R) when discharge was recommended (DERM_2R) and without it (DERM_autonomous). The outputs were numbers of diagnostic outcomes, numbers of key events (GP appointments, DERM assessments, hospital referrals), costs and quality-adjusted life-years (QALY). The cost-effectiveness metrics were incremental cost per QALY gained. Analysis was conducted in the UK from an NHS and personal social services perspective, with a life-time horizon up to a maximum of 100 years, with uncertainty assessed mainly using deterministic sensitivity analyses.
resultsWe report three base-case results on the basis of different assumptions regarding GP diagnostic sensitivity and specificity. When GPs operate with maximised sensitivity as suggested by the literature, SC is the most cost-effective option. SC dominates DERM_autonomous and DERM_2R has an incremental cost-effectiveness ratio (ICER) relative to SC of £30,370. If GPs operate with maximised specificity, DERM_autonomous dominates SC and DERM_2R has an ICER of £397. If GPs diagnose cancer with a performance back calculated from NHS routine data, the cost-effectiveness of both DERM options dominate SC.
conclusionsThe priority should be for better estimates of GP accuracy to be obtained to reduce uncertainty in the estimates of cost-effectiveness. The results presented do, however, show that it is plausible that DERM could be cost-effective justifying use in practice with further data collection.
Identifiers
42611421What 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.