Smarter referrals: why AI-assisted triage should begin in primary care

Abstract

Every day, general practitioners (GPs) are asked to decide: does this patient need acute care?To which specialty and with what information?These questions, often made under time pressure and with limited access to diagnostics or specialist input, shape patient care trajectories.Chronic care decisions with uncertainty such as strange semi-vertiginous episodes falling between neurology and otolaryngology also lack structured support.If artificial intelligence (AI) is to fulfil its promise of transforming triage and acute care, its most impactful point of entry is not the emergency department or outpatient clinic; it is primary care.We argue that AI-based decision support should be piloted in general practice, where the gains in efficiency, effectiveness and positive patient impact are highest. Rethinking triage: start where decisions beginAI conversations on triage largely focus on hospital settings.Studies show models like GPT-4 (a Large Language Model from OpenAI) outperform junior doctors in triage accuracy and can efficiently summarise clinical presentations. [1][2]2][3] However, these capabilities are often applied after referral decisions, too late to influence the most critical point of uncertainty.That uncertainty lies in the community: the urgent care centre, the after-hours general practice clinic, the rural general practice.An overstretched medical system has also increased the number of acutely ill people presenting to general practice rather than urgent care clinics.This is where decisions are made under constrained time and limited resources.Integrating AI in this space would reduce emergency department work and enhance the quality of early care decisions.

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