Mission Run
Hospital Discharge Planning Cockpit (Next.js) — Workflow Coordination + Safe, Explainable AI Summaries
Build a hospital discharge planning cockpit that coordinates patient readiness, follow-up tasks, medication review, insurance blockers, care-team notes, and AI-generated discharge summaries.
Created: 14 Jun 2026, 11:36 am
Updated: 14 Jun 2026, 11:36 am
Repository Context
Greenfield Next.js healthcare operations prototype with task workflows, timeline views, local persistence, care-team dashboards, and document-generation surfaces.
Constraints
Use synthetic patient data only. Emphasize workflow coordination, safety checks, privacy posture, and explainable recommendations.
AI Software Execution Operating System
Primary users
Founders, product leads, architects, delivery teams, and AI-native engineering teams that need a system of record between idea and execution.
Problem solved
It transforms mission intelligence into PRDs, technical designs, engineering plans, AI execution packs, architecture maps, risk models, and traceable workflows.
Product Flow Diagram
Idea to execution intelligence
User
Submits a software idea and constraints
Mission Plan
Tasks, dependencies, owners, risks
Document Studio
PRD, TDD, engineering plan, AI pack
Mission Memory
Reusable organizational knowledge
Architecture Diagram
System components for this idea
Users
Founders + product teams
Edge
Route 53 / CDN / WAF boundary
Application VPC
Web App
Next.js App Router
API Server
TypeScript
Worker
Mission/document generation jobs
Cache
Saved docs + fast reloads
Data Plane
Primary DB
Local JSON for prototype, SQLite/PostgreSQL for production knowledge storage.
Object Storage
Generated docs, exports, artifacts
AI + Operations
OpenAI API
PRD, TDD, plan, AI pack
Observability
Logs, risks, decision trail
IAM / Secrets
Server-side keys + access control
Alerts
Execution and risk signals
Cloud Diagram
Deployment-ready shape
Browser
User session
Mission UI
Dashboard + document studio
API Routes
Validate + orchestrate
Storage
Missions + cached docs
AI Client
Codex / external tools
AI Pack
Portable execution context
Doc Engine
Timeout + local fallback
OpenAI
Optional enrichment
Security posture
Keep API keys server-side, validate payloads, and preserve audit logs.
3 risk signals
Risks become visible before execution moves to tools.
Mission Document Studio
Export mission intelligence
Turn the mission into production-ready documents for executives, engineers, delivery teams, and external AI execution tools.
Choose a document type to generate an export-ready artifact.
Traceability Map
Why every task exists
This replaces vague “AI said so” planning. Each path shows which goal, requirement, task, architecture choice, or risk explains the work.
goal
Build a hospital discharge planning cockpit that coordinates patient readiness, follow-up tasks, medication review, insurance blockers, care-team notes, and AI-generated discharge summaries.
requirement
Define scope, user roles, and discharge workflow blueprint
task
Define scope, user roles, and discharge workflow blueprint
requirement
Data model + synthetic dataset strategy
task
Data model + synthetic dataset strategy
requirement
Privacy & safety posture baseline (demo constraints, audit, disclaimers)
task
Privacy & safety posture baseline (demo constraints, audit, disclaimers)
requirement
Next.js app scaffolding and UI foundations
task
Next.js app scaffolding and UI foundations
requirement
Local persistence layer + state management
task
Local persistence layer + state management
requirement
Discharge readiness cockpit view (single-pane coordination)
task
Discharge readiness cockpit view (single-pane coordination)
requirement
Task workflows: assignment, dependencies, escalation, and handoffs
Trace paths
Kept because traceability is the product moat; renamed from relationships for clarity.
Mission Decision Log
Explain the important choices
Use Mission Control as the documentation system of record
The mission needs traceable planning artifacts before execution moves into external tools.
Tradeoffs
Improves clarity and handoff quality, but requires users to maintain mission context.
Alternatives
Unstructured chat logs, standalone docs, tickets, or ad hoc planning notes.
Mission Memory
Reuse organizational knowledge
Mission Steps
Task Timeline
8 tasks
Mission Steps
Task Timeline
Task 1
Define scope, user roles, and discharge workflow blueprint
queued
Task 1
Define scope, user roles, and discharge workflow blueprint
Align on target users (RN case manager, hospitalist, pharmacist, social worker, utilization review, unit clerk), key entities (patient, encounter, discharge plan, tasks, meds, insurance issues, notes, documents), and the end-to-end discharge workflow states (Admit → Inpatient → Discharge Planning → Ready Pending Items → Discharged). Produce a lightweight spec with acceptance criteria for cockpit views: readiness checklist, follow-up tasks, medication review, insurance blockers, care-team notes, and discharge summary generation.
Task 2
Data model + synthetic dataset strategy
queued
Task 2
Data model + synthetic dataset strategy
Design TypeScript domain models and JSON fixtures for synthetic patients/encounters, including demographics, diagnoses/problems, labs/vitals (synthetic), medication list (home/inpatient/discharge), follow-up tasks, insurance prior-auth blocks, notes, and audit events. Establish a synthetic data policy: no real PHI, generate deterministic synthetic IDs, and include a clear banner in-app indicating synthetic/demo mode.
Task 3
Privacy & safety posture baseline (demo constraints, audit, disclaimers)
queued
Task 3
Privacy & safety posture baseline (demo constraints, audit, disclaimers)
Implement a privacy posture checklist for the prototype: synthetic-only guardrails, no external telemetry by default, redact/avoid free-text PHI patterns, and add in-app disclaimers that outputs are assistive and require clinician review. Add an audit log model for key actions (task completion, med reconciliation changes, summary generation) to support traceability.
Task 4
Next.js app scaffolding and UI foundations
queued
Task 4
Next.js app scaffolding and UI foundations
Set up route structure and layout for cockpit: /dashboard, /patients/[id], /patients/[id]/timeline, /patients/[id]/discharge. Add shared components (patient header, status chips, task list, note composer, blockers panel). Ensure accessibility basics (keyboard navigation, ARIA for key controls) and consistent visual language for safety-critical alerts.
Task 5
Local persistence layer + state management
queued
Task 5
Local persistence layer + state management
Implement local persistence (IndexedDB or localStorage via a thin repository layer) for synthetic data edits: tasks, notes, med review decisions, blocker resolutions, and generated documents. Provide migration/versioning for stored schema, and add reset-to-fixtures capability for demos/testing.
Task 6
Discharge readiness cockpit view (single-pane coordination)
queued
Task 6
Discharge readiness cockpit view (single-pane coordination)
Build the primary discharge cockpit panel: readiness checklist (clinical stability, pending tests, mobility/OT, patient education, transportation), follow-up tasks (assigned owner + due date), medication review status, insurance blockers, and care-team notes. Include clear “not ready” reasons, required next actions, and a timeline snippet of recent events.
Task 7
Task workflows: assignment, dependencies, escalation, and handoffs
queued
Task 7
Task workflows: assignment, dependencies, escalation, and handoffs
Implement task creation and routing with owners, due times, status, and dependencies (e.g., prior auth must resolve before discharge). Add escalation rules (overdue/high-risk), quick handoff between roles, and a “today view” for care-team workload. Ensure tasks are explainable: show why a task exists and what evidence triggered it.
Task 8
Medication reconciliation & safety checks
queued
Task 8
Medication reconciliation & safety checks
Create medication review surface: compare home vs inpatient vs proposed discharge meds, highlight deltas, duplications, dose changes, and allergy/interaction flags (rule-based on synthetic data). Add structured decisions (continue/stop/change) with rationale and required co-sign prompts. Gate discharge readiness on unresolved high-severity medication issues.
Audit Trail
Execution Log
1 logs
Audit Trail
Execution Log
Mission plan generated successfully.
success
14 Jun 2026, 11:36 am
Mission Outputs
Artifacts
1 artifacts
Mission Outputs
Artifacts
Mission Plan
plan
plan
This execution plan builds a practical discharge planning cockpit on a greenfield Next.js healthcare operations prototype with workflow-first coordination, explicit safety checks, and a synthetic-data-only privacy posture. 1) First, lock workflow scope and roles so the cockpit reflects real discharge operations (case management, pharmacy, UR, social work, nursing, and physicians). 2) Establish a typed domain model and deterministic synthetic fixtures so all UI and AI features remain safely non-PHI. 3) Implement baseline privacy/safety guardrails early—disclaimers, redaction posture, and an audit log—so every downstream feature is traceable and demo-safe. 4–6) Build the app skeleton, local persistence, and the core cockpit view as the single source of truth for patient readiness, tasks, meds, blockers, and notes. 7–10) Layer in operational workflows: task routing with dependencies and escalation, medication reconciliation with rule-based safety flags, insurance blocker resolution, structured care-team notes, and a timeline that makes every recommendation explainable via evidence links. 11–12) Add AI-assisted discharge summaries only after structured data, notes, and timeline evidence exist. The AI output is constrained to available data, cites sources, highlights missing information, and requires clinician review. Safety gating then enforces readiness rules and hard stops (or documented overrides) to prevent premature discharge actions. 13–14) Close with tests, scenario-based demo playbooks, performance tuning, and operational guardrails (feature flags, local-only logs, synthetic-mode indicators). The end result is an execution-oriented cockpit that coordinates discharge work across disciplines, surfaces blockers early, makes safety-critical decisions transparent, and keeps the prototype aligned with privacy-by-design using synthetic data exclusively.