Prevent / Care
Clinical red-flag detection and safe escalation
A patient mentions the same side-effect for the third week running — the agent recognizes it is not routine and hands the clinical team a clean summary, immediately.
What it does
Patients mention the things that matter in passing — a side-effect dropped into a coaching chat, a dose question in a support thread — not in the structured forms built to catch them. Mentioned once, a symptom is routine; the same one three weeks running, or nausea plus fatigue plus a dose query spread across separate conversations, is a trajectory, and missed signals cost more as the patient base matures. Instead of sending the patient off to a form, the agent captures the mention in the conversation, logs it against their history, recognizes when the picture is not routine, and escalates safely: a clean summary into the clinical team's queue, or an immediate clinician handover when the signal is acute. Intent-based triage keeps the routing honest — chest pain reaches a clinician now, "I'm hungry" goes to the coach.
How it works
- 1Trigger. a symptom or side-effect mention in any conversation, or a risk pattern surfacing across the patient's logged history — no extra form, no separate intake.
- 2Decision. the agent logs the mention against the patient's persistent memory and asks the only question that matters: one-off, trajectory, or composite? Intent-based triage classifies severity against the program's clinical policy, with conservative defaults — when unsure, escalate.
- 3Action. routine mentions are captured and acknowledged in the flow of conversation; not-routine patterns become a clean, sourced summary handed to the clinical team; acute red flags route to a clinician immediately, and automated replies stand down on that thread.
- 4Follow-through. every escalation carries the full picture so the patient never repeats themselves; the clinician's outcome writes back to memory; the agent follows up later to close the loop on whether the symptom actually resolved.
Configuration
How the agent is wired for this use case.
- Messaging channel · capture and acknowledge routine mentions in the flow of conversation
- Memory store · log each mention against the patient's persistent history, write the clinician's outcome back
- Care platform · file a clean, sourced summary into the clinical team's queue for not-routine patterns
- Care platform · route acute red flags to a clinician immediately and stand automated replies down on that thread
What you need
The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.
Signals
in-conversation symptom and side-effect mentions, dose and program-stage events, the patient's own message history
Data
patient history and medication/program stage, prior symptom reports, persistent patient memory across support, coaching, and medical threads, consent state
Guardrails
clinical triage policy with conservative defaults; no medical advice in any automated reply; judge gating on every message; automated replies stand down once a clinician owns the thread; full audit trail of every escalation decision
Metrics it moves
- safe-escalation-rateup, as symptoms mentioned in passing reliably reach clinical eyes instead of dying in a chat log
- time-to-resolutiondown, because acute signals route to a clinician in the moment rather than waiting for a form or a follow-up appointment
- csatup, since patients feel watched over by the program, not processed by it
Related use cases
Adherence guardian for medication programs
the retention sibling that leans on this safety rail
Clinician copilot — approve instead of writing
what the clinical team does with the clean summary
Test-result interpretation agent
the same clinical-safety posture applied to results
See it on your own customer journey
Bring one drop-off, one churn cliff, or one silent segment. We will show you what a proactive agent with memory and judgment does with it.
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