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Retain / Save

Adherence guardian for chronic-condition programs

A member managing hypertension stops logging readings the week the numbers wobble — the agent reaches out with a steady, safe touch before a quiet lapse becomes a dropped program.

Get aheadRisk triggerBehavioral triggerTime-based triggerIn-appPushChatSMSHealth & TelehealthSubscriptionGLP-1 & Peptides

What it does

Chronic-condition programs — diabetes, hypertension, mental health — lose members in quiet, predictable windows, and most never raise their hand first; they simply stop logging and drift. A plateau that feels like failure, a stretch of skipped readings, a side-effect mention buried in a check-in: each is a drop-off risk the program's own data can see before any cancel intent appears. The agent watches those signals and reaches out with a safe, condition-appropriate coaching touch that keeps the member engaged, with anything clinically serious escalated to a clinician rather than answered in chat.

How it works

  1. 1
    Trigger. a server-side risk signal fires — missed logs against the member's own cadence, a metric plateau or out-of-range reading, engagement decay across the app, or a side-effect mentioned in a check-in.
  2. 2
    Decision. the agent weighs the signal against the member's memory (condition program, what has already been said, prior outreach and how it landed) and the program's condition-specific safety policy; every unprompted message is judge-gated for clinical safety and tone before it sends.
  3. 3
    Action. a supportive message in-app, by push, chat, or SMS that normalizes the moment and offers what helps within scope — encouragement and practical next steps, never a dosage change or medical advice.
  4. 4
    Follow-through. red flags (an out-of-range reading that needs review, concerning language) escalate to a clinician with context attached; the reply is written back to memory; if the member re-engages on their own first, the stale outreach is cancelled. Impact is measured against a holdout so the program sees what the guardian actually retained.
Example
AgentI noticed your blood-pressure logs have been quiet this week, and the last couple of readings ran a little high. That happens, and it does not mean you are off track. Are you managing okay with the routine, or is something getting in the way?
MemberHonestly I have been skipping it, the numbers stress me out.
AgentThat is really common, and avoiding the readings is understandable. Logging even a few times a week helps your care team spot patterns early. If those high numbers keep up, I can have a clinician review them with you — want me to set that up?

Configuration

How the agent is wired for this use case.

Triggera missed_log, reading_out_of_range, engagement_decay, or side_effect_logged event from the program's care-tracking backend.
Tools & actions
  • Care-tracking backend · read logging cadence, metric readings, plateau and engagement-decay signals
  • Member profile / memory store · read condition program, history, consent, prior coaching outreach
  • Condition-specific safety policy and judge · gate every unprompted message for clinical safety and tone before send
  • In-app messaging / push / SMS surface · deliver the coaching touch on the member's active channel
  • Clinician escalation queue · route red-flag readings and concerning language to a human clinician with context attached
Autonomyjudge-gated and unattended for the coaching touch; any clinical judgment is a handoff, not an agent action — the agent detects and escalates to a clinician under a clinical-safety policy class and never gives dosage or medical advice.
Channelsin-app · push · chat · sms
Escalationan out-of-range reading needing clinical review, a red-flag or crisis signal, or concerning language hands off to a clinician immediately.

What you need

The inputs this use case runs on. Your channels stay yours; the agent supplies the judgment.

Signals

logging-cadence events, metric readings and out-of-range thresholds, engagement-decay events, side-effect mentions

Data

member condition program, reading and outcome history, consent state, memory of prior coaching conversations and outreach

Guardrails

condition-specific clinical red-flag detection with clinician escalation; detect-and-escalate only, no proactive dosage or medical advice from the agent; judge gating on every unprompted message; frequency caps; holdout measurement so claimed retention is proven, not assumed

Metrics it moves

  • adherenceup, as members caught inside the risk window stay engaged with the program instead of quietly lapsing
  • churndown, because chronic-program drop-off concentrates in exactly the windows the guardian covers
  • ticket-deflectionup, since the proactive touch answers the worry before it becomes a support contact, measured against the holdout
  • ltvup, as every retained month of a chronic-care program compounds on already-spent acquisition cost

Related use cases

Retain / Save

Adherence guardian for medication programs

the GLP-1 parent this chronic-condition variant generalizes

Prevent / Care

Clinical red-flag detection and safe escalation

the safety rail every guardian message leans on

Engage / Lifecycle

Proactive health-coach companion

the ongoing engagement companion alongside the risk-driven guardian

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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