Adaptive Symptom Check-In Programs with Condition Templates

Summary

Add scheduled, adaptive symptom check-in programs (e.g., migraine, anxiety, post-op recovery) that guide users through structured questions over time and produce comparable trend scores.

Problem / Opportunity

Free-form logging is flexible but inconsistent, making long-term trend analysis noisy and harder to compare across weeks. Structured check-ins improve data quality, reduce cognitive load, and make symptom trajectories more clinically useful.

Proposed Feature

Introduce configurable check-in programs:

• Users can enroll in a condition template (or a custom template later).
• The app schedules recurring check-ins with reminder nudges.
• Each check-in captures standardized responses and computes template-specific scores.
• Trends are visualized alongside existing health logs and medication events.

Scope

1. Check-in template and response model

• Add template definitions (question sets, scoring rules, cadence).
• Add response storage with timestamps and completion state.
• Version templates so historical responses remain interpretable.

2. Scheduling and reminders

• Add check-in reminder scheduling integrated with current reminder infrastructure.
• Support missed-check-in handling (grace period + catch-up prompt).

3. Guided UI flow

• Add a dedicated check-in page with progress UI, autosave, and resume.
• Surface "due now" check-ins on dashboard and notifications.

4. Analytics integration

• Add trend charts for check-in scores over time.
• Overlay check-in scores with key events (med changes, appointment dates).

5. AI context enrichment

• Expose latest check-in signals to chatbot context for more grounded guidance.

Acceptance Criteria

• User can enroll in at least one template program and see upcoming check-ins.
• Scheduled reminders fire for due check-ins and deep-link into the form.
• Completed check-ins generate a normalized score and appear in trends.
• Missed check-ins are tracked and surfaced with clear status.
• Template versioning preserves interpretation for old responses.
• Tests cover scoring logic, reminder scheduling, and analytics rendering.

Non-Goals

• Clinical diagnosis or medical-grade screening claims.
• Dynamic adaptive branching powered by external clinical engines in MVP.
• Provider-side authoring portal in initial release.

Dependencies / Risks

• New scheduling dimension may increase notification volume if not tuned.
• Requires careful UX to avoid survey fatigue and drop-off.
• Cross-table analytics joins may impact dashboard performance at scale.

Open Questions

• Which initial template set should ship first (e.g., migraine/anxiety/post-op)?
• Should partial check-ins contribute to trend scores or be excluded?
• How should check-in scores be explained to users to avoid overinterpretation?