Artificial Intelligence for Triage in Primary Care: A Scoping Review of Clinical Applicability.

AIM: To map artificial intelligence (AI) systems developed for triage in primary care and describe their characteristics, performance and clinical applicability.

METHODS

A scoping review was conducted in accordance with PRISMA-ScR. PubMed, MEDLINE (via Ovid), Embase, Web of Science, CINAHL (via EBSCOhost), IEEE Xplore and the ACM Digital Library were searched until March 14th 2026. Two reviewers independently screened studies and extracted data on system characteristics, triage function, performance, validation, safety, equity and implementation. Each system was charted by triage function and by whether it was patient-facing, clinician-facing or fully automated.

RESULTS

Seventeen studies were included, published between 2013 and 2026 across 12 countries (14/17 high-income). Most were clinician-facing decision support (14/17), three had a patient-facing component and none were autonomous. Diagnostic or screening triage was the most common function (n = 7), followed by prioritisation (n = 4) and referral routing (n = 4). Only two performed urgency classification or self-triage. As a clinician aid, AI improved performance (fundus accuracy 82.8 % to 91.1 %; dermoscopy management sensitivity 72.9 % to 94.2 %), but standalone models sometimes fell below clinicians. Reported accuracy ranged from 41.2 % to 98.28 % and AUROC from 0.65 to 0.90, on heterogeneous outcomes. Validation was mostly internal (11/17), external in four. None reported a prospective randomised comparison or measured patient outcomes.

CONCLUSION

AI triage in primary care is concentrated on clinician-facing diagnostic and referral tasks and is most valuable for augmenting clinician workflows, particularly non-specialists. The evidence base remains immature, constrained by internal validation, unreliable reference standards, sparse equity assessment and absent prospective outcome data. Future work should prioritise prospective, outcome-anchored evaluation, with attention to safety and equity.