Safety-by-Construction Agentic AI for Territorial Pre-Triage: A Proof-of-Concept Case Study for Rural and Inner Areas of Calabria
Abstract
\textbf{Background:} Rural and inner areas combine geographic distance, demographic ageing, small municipalities, and fragmented access to health services. These conditions are especially relevant in Calabria, where a large proportion of municipalities have fewer than 5,000 residents and several officially designated inner areas show long travel times to reference service poles. Digital pre-triage may provide an additional access and orientation layer, but the use of generative artificial intelligence in health care raises concerns about hallucination, non-determinism, privacy, and under-triage.\textbf{Methods:} We designed a modular agentic-AI framework for territorial pre-triage according to a safety-by-construction principle. The architecture separates conversational elicitation (workflow W01) from clinical interpretation and priority assignment (workflow W02) through a pseudonymized JSON contract. W02 combines symptom normalization, red-flag detection, four function-specific retrieval-augmented generation collections, a panel of three role-diversified classifiers, and a deterministic reconciliation node based on majority or median voting with a hard safety override for confirmed red flags. The framework produces two outputs: practical care-pathway guidance for the citizen and a structured, auditable dossier for health professionals. Evaluation included 28 synthetic Italian-language cases processed directly by W02, nine end-to-end conversational cases, and 11 official…
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