Dietitian client follow-up
Exceptions back. Not another inbox.
Clients ask questions, swap meals, rate meals, and check in through one shared thread. Lumo handles routine support inside the care plan and raises alerts when practitioner attention is needed.
What should come back?
The alert layer is the practitioner workload filter. It turns everyday activity into a smaller set of reviewable exceptions.
Eaten, skipped, and modified meals update adherence and nutrition read models.
Repeated swaps or unstable replacements can trigger review rather than stay hidden.
Questions or generated meals that drift outside the harness become alerts.
The practitioner can join the same client-AI thread when correction or clinical guidance is needed.
Useful signal is human-sized.
A practitioner should see severity, category, and context: nutrient drift, engagement risk, care-rule conflict, or a thread moment that needs a human response.
Routine support should stay light.
- AI responds by default to meal questions, swaps, and clarification requests.
- Care-team notes can guide AI behavior without being shown to the client.
- Practitioners acknowledge, resolve, or update the care plan when alerts need action.
Make follow-up easier to act on.
Join the waitlist if your practice wants between-visit visibility with less manual workload.
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