# 🏥 SwarmCare v5.0 — World-Class Patient Journey Specification ## Patient: Mogli Patel | LangGraph + Neo4j + Multi-Agent AI + 13 Ontologies > **"Of the Patient, To the Patient, By the Patient"** --- **Specification Version:** 5.0 — Production-Grade AI Implementation Blueprint **Generated:** February 22, 2026 **Platform:** SwarmCare v5.0 + LangGraph + Neo4j + 13 Ontologies + 20 AI Agents **Patient:** Mogli Patel (PAT-MOGLI-001) **Journey Stages:** 60 (expanded from 22 in v2) **Total Features:** 500+ **Researched:** 100+ global healthcare platforms (Epic, Cerner, Viz.ai, Abridge, Navina, Sully.ai, Ada Health, Buoy Health, Clearstep, Biofourmis, K Health, Sword Health, Sensely, Infermedica, Woebot, CodaMetrix, Augmedix, RapidAI, Enlitic, and 80+ more) --- ## HOW TO USE THIS DOCUMENT (FOR AI CODING AGENTS) This document is structured for **direct implementation** by AI coding agents (Cursor, Windsurf, Claude Code, GitHub Copilot). Each stage contains: 1. **LangGraph Node** — Python function signature with typed state input/output 2. **Mogli's Data** — Complete example data with all fields populated 3. **Neo4j Cypher** — Copy-paste graph queries for node/edge creation 4. **API Endpoint** — REST endpoint specification 5. **Kafka Event** — Async event topic for real-time processing 6. **Agent Assignment** — Which of the 20 AI agents handles this stage **Implementation Order:** Stages 1-4 are GATED (must pass to proceed). Stages 5-60 are a LINEAR CHAIN. Each stage reads from and writes to `SwarmCareState`. --- ## TABLE OF CONTENTS **PART 1: ARCHITECTURE & CORE JOURNEY (Stages 1-4)** - Architecture Overview (Six-Layer Stack, LangGraph State Machine, Neo4j Schema) - Stage 1: Patient Registration - Stage 2: HIPAA & Consent Management (10 Consents) - Stage 3: Care Team Selection (Patient-Driven Democratic Model) - Stage 4: Treatment Initiation (Safety Pre-Check Matrix) **PART 2: PLATFORM MODULES (Stages 5-8, 13-22)** - Stage 5: Patient Dashboard (AI-Powered, 26 Features) - Stage 6: Chronic Care Management (RPM + Digital Therapeutics) - Stage 7: Clinical Workstation (Ambient Documentation) - Stage 8: Context Graph (13 Ontologies, PathRAG + GraphRAG) - Stages 13-22: Portal, Dashboards, AI Chat, Telehealth, Care Plans, Alerts, Workflow, CDS, Predictive, Imaging, Population Health, Clinical Trials, Voice AI, XAI, Public Health **PART 3: ADVANCED COMMUNICATION & COORDINATION (Stages 9-12) — DEEP DIVE** - Stage 9: Doctor-to-Doctor Communication (D2D) — Dialogue Storage & AI Summarization - Stage 10: Care Audio & Ambient Documentation — 3 Pillars - Stage 11: AI Announcements & Patient Instructions — Alert Escalation - Stage 12: Care Handoff Coordination — I-PASS, SBAR, ISBAR3 **PART 4: WORLD-CLASS MODULES NO COMPETITOR HAS (Stages 23-50)** - Stage 23-41: Family, Pharmacy, Insurance, Appointments, Genomics, Mental Health, Feedback, Education, Audit, SDoH, DTx, Transport, Nutrition, Advance Directives, Second Opinion, Rehab, Community Resources, Research Consent, Wellness Goals - Stage 42: Medication Reconciliation (AI-BPMH) ← **NEW** - Stage 43: Medication Therapy Management (MTM) ← **NEW** - Stage 44: Patient-Reported Outcomes (PROMIS/CAT) ← **NEW** - Stage 45: Shared Decision Making (SDM Dashboard) ← **NEW** - Stage 46: AI Symptom Triage & Self-Assessment ← **NEW** - Stage 47: Digital Twin & Predictive Simulation ← **NEW** - Stage 48: Cybersecurity & Zero-Trust Access ← **NEW** - Stage 49: Post-Discharge Surveillance (30-Day) ← **NEW** - Stage 50: Social Prescribing & Non-Medical Rx ← **NEW** **PART 5: INFRASTRUCTURE & DISCHARGE (Stages 51-60)** **PART 6: COMPLETE TECHNICAL SPECIFICATIONS** - Neo4j Schema (50+ Node Types, 65+ Edge Types) - 13 Ontology Integration (74+ Terms) - LangGraph Architecture (60+ Nodes) - Kafka Event System (35+ Topics) - API Specification (75+ Endpoints) - 20 AI Agent Definitions - Competitive Matrix (vs Top 15 Global Competitors) --- ## ARCHITECTURE OVERVIEW ### System Architecture — Six-Layer Stack ``` LAYER 1: PATIENT INTERFACE React Native App | Web Portal | Voice AI | SMS | Wearable SDK LAYER 2: API GATEWAY + AUTHENTICATION Kong/Apigee | OAuth 2.0 + SMART on FHIR | Zero-Trust | mTLS | JWT + RBAC LAYER 3: AGENT ORCHESTRATION (LangGraph) 60-Node State Machine | 20 AI Agents | 4 Gate Nodes | Human-in-Loop LAYER 4: SPECIALIST AI CLONES MedicationSafety | Diagnosis | Predictive | Handoff | Communication | Audio | Triage LAYER 5: KNOWLEDGE GRAPH + DATA LAYER Neo4j (KG) | PostgreSQL (OLTP) | Redis (Cache) | TimescaleDB (Time-Series) Weaviate/Pinecone (Vector) | MarkLogic (Documents) | Kafka (Streaming) 13 Ontologies | PathRAG + GraphRAG | Graphiti Temporal Edges LAYER 6: HEALTHCARE SYSTEM INTEGRATION Epic/Cerner FHIR R4 | NCPDP SCRIPT (Pharmacy) | X12 (Claims) HL7 v2.x (Legacy) | DICOM (Imaging) | 340+ Insurance Payers TEFCA/HIE | Blue Button 2.0 | Public Health Registries ``` ### SwarmCareState — Shared LangGraph State Definition ```python from typing import TypedDict, Optional, List, Dict, Any from datetime import datetime from enum import Enum class JourneyStatus(Enum): NOT_STARTED = "not_started" IN_PROGRESS = "in_progress" COMPLETE = "complete" FAILED = "failed" BLOCKED = "blocked" class SwarmCareState(TypedDict): # Patient Identity patient_id: str # "PAT-MOGLI-001" mrn: str # "MRN-2026-00451" patient_data: Dict[str, Any] # Full demographics # Journey Control current_stage: str journey_status: JourneyStatus stage_results: Dict[str, Dict[str, Any]] stage_timestamps: Dict[str, datetime] error_log: List[Dict[str, Any]] # Clinical Data conditions: List[Dict[str, Any]] medications: List[Dict[str, Any]] allergies: List[Dict[str, Any]] lab_results: List[Dict[str, Any]] vital_signs: List[Dict[str, Any]] encounters: List[Dict[str, Any]] procedures: List[Dict[str, Any]] # Consent & Compliance consents: Dict[str, Dict[str, Any]] hipaa_acknowledged: bool audit_trail: List[Dict[str, Any]] # Care Team care_team: List[Dict[str, Any]] care_team_communications: List[Dict] handoff_records: List[Dict[str, Any]] # AI & Audio audio_recordings: List[Dict[str, Any]] ai_announcements: List[Dict[str, Any]] patient_instructions: List[Dict[str, Any]] # RPM & Wearables wearable_devices: List[Dict[str, Any]] rpm_readings: List[Dict[str, Any]] rpm_alerts: List[Dict[str, Any]] # Knowledge Graph ontology_terms: Dict[str, List[Dict]] graph_node_count: int graph_edge_count: int # Insurance & Billing insurance: Dict[str, Any] prior_authorizations: List[Dict] claims: List[Dict[str, Any]] billing_records: List[Dict[str, Any]] # v5 NEW Modules medication_reconciliation: Dict[str, Any] mtm_reviews: List[Dict[str, Any]] prom_scores: Dict[str, Any] sdm_sessions: List[Dict[str, Any]] triage_assessments: List[Dict[str, Any]] digital_twin_state: Dict[str, Any] social_prescriptions: List[Dict[str, Any]] post_discharge_checks: List[Dict[str, Any]] # Family & Engagement family_members: List[Dict[str, Any]] patient_feedback: List[Dict[str, Any]] wellness_goals: List[Dict[str, Any]] education_content: List[Dict[str, Any]] # Meta created_at: datetime updated_at: datetime version: str # "5.0" ``` --- ## STAGE 1: PATIENT REGISTRATION **LangGraph Node:** `registration_node` | **Agent:** RegistrationAgent | **Kafka:** `swarmcare.patient.registered` ```python async def registration_node(state: SwarmCareState) -> SwarmCareState: """ GATE NODE — Must pass to proceed. Validates demographics, generates MRN, verifies insurance eligibility (270/271), creates FHIR Patient resource, persists to Neo4j. Failure: Routes to registration_failed -> END """ pass ``` **Mogli Patel — Complete Demographics:** | Field | Value | |-------|-------| | Patient ID | `PAT-MOGLI-001` | | MRN | `MRN-2026-00451` | | Name | Mogli Patel | | DOB | 1988-06-15 (Age 37) | | Gender | Male | | Race / Ethnicity | Asian / South Asian (Indian) | | Languages | English (primary), Hindi | | Email | mogli.patel@email.com | | Phone | (512) 555-0198 | | Address | 742 Rainforest Drive, Austin, TX 78701 | | Emergency Contact | Akela Patel (Brother) — (512) 555-0277 | | Employment | Software Engineer at TechCorp Austin | | Insurance | Blue Cross Blue Shield TX — PPO Gold | | Member ID | BCBS-TX-2026-88451 | | Group | GRP-TECHCORP-500 | | Copay PCP/Specialist | $25 / $50 | | Deductible | $1,500 (Met: $425) | | OOP Max | $6,000 | | Pharmacy Benefit | Express Scripts (Tier 1: $10 / Tier 2: $35 / Tier 3: $70) | **FHIR Patient Resource:** ```json { "resourceType": "Patient", "id": "PAT-MOGLI-001", "identifier": [ {"system": "urn:swarmcare:mrn", "value": "MRN-2026-00451"}, {"system": "urn:bcbs:member", "value": "BCBS-TX-2026-88451"} ], "active": true, "name": [{"use": "official", "family": "Patel", "given": ["Mogli"]}], "gender": "male", "birthDate": "1988-06-15", "address": [{"city": "Austin", "state": "TX", "postalCode": "78701"}], "communication": [ {"language": {"coding": [{"code": "en"}]}, "preferred": true}, {"language": {"coding": [{"code": "hi"}]}} ] } ``` **Neo4j Cypher:** ```cypher CREATE (p:Patient { patient_id: 'PAT-MOGLI-001', mrn: 'MRN-2026-00451', first_name: 'Mogli', last_name: 'Patel', date_of_birth: date('1988-06-15'), gender: 'Male', race: 'Asian', ethnicity: 'South Asian', preferred_language: 'en', secondary_language: 'hi', email: 'mogli.patel@email.com', phone: '(512) 555-0198', city: 'Austin', state: 'TX', zip: '78701', county: 'Travis County', census_tract: '48453001802', employer: 'TechCorp Austin', created_at: datetime(), status: 'active', version: 1 }) CREATE (i:Insurance { insurance_id: 'INS-MOGLI-001', payer: 'BCBS Texas', plan_name: 'PPO Gold', member_id: 'BCBS-TX-2026-88451', copay_pcp: 25, copay_specialist: 50, deductible: 1500, deductible_met: 425, oop_max: 6000, status: 'active' }) MATCH (p:Patient {patient_id: 'PAT-MOGLI-001'}) MATCH (i:Insurance {insurance_id: 'INS-MOGLI-001'}) CREATE (p)-[:HAS_INSURANCE {type: 'primary', validity: 'current', created_at: datetime(), version: 1}]->(i) ``` **API:** `POST /api/v1/patients/register` → `{patient_id, mrn, fhir_resource, status}` **Stage Output:** `{status: "complete", patient_id: "PAT-MOGLI-001", insurance_verified: true, neo4j_nodes: 2, neo4j_edges: 1}` --- ## STAGE 2: HIPAA & CONSENT MANAGEMENT (10 Consents) **LangGraph Node:** `consent_node` | **Agent:** ComplianceAgent | **Kafka:** `swarmcare.consent.signed` ```python async def consent_node(state: SwarmCareState) -> SwarmCareState: """ GATE NODE — 5 required consents must be signed to proceed. Presents 10 consent types (5 required, 5 optional). Digital signature with timestamp, IP, device fingerprint. """ pass ``` **5 REQUIRED (must sign all):** | # | Consent Type | Status | Signed At | |---|-------------|--------|-----------| | 1 | HIPAA Privacy Notice | SIGNED | 2026-02-22T08:05:00Z | | 2 | Treatment Consent | SIGNED | 2026-02-22T08:05:30Z | | 3 | Data Sharing (Care Team) | SIGNED | 2026-02-22T08:06:00Z | | 4 | Telehealth Consent | SIGNED | 2026-02-22T08:06:30Z | | 5 | Financial Responsibility | SIGNED | 2026-02-22T08:07:00Z | **5 OPTIONAL (patient chooses):** | # | Consent Type | Status | Notes | |---|-------------|--------|-------| | 6 | Research Participation | OPTED IN | Anonymized data for studies | | 7 | Family/Caregiver Access | OPTED IN | Akela: full; Sita: read-only | | 8 | Wearable Data Sharing | OPTED IN | CGM, BP, scale data | | 9 | AI Decision Support | OPTED IN | AI suggests, never decides | | 10 | Audio Recording | OPTED IN | Encounters recorded for SOAP | **Neo4j:** 10 Consent nodes linked to Patient via `HAS_CONSENT` edges with Graphiti temporal validity. --- ## STAGE 3: CARE TEAM SELECTION (Patient-Driven Democratic Model) **LangGraph Node:** `care_team_selection_node` | **Agent:** CareCoordinationAgent | **Kafka:** `swarmcare.care_team.assembled` ```python async def care_team_selection_node(state: SwarmCareState) -> SwarmCareState: """ GATE NODE — PCP must be selected at minimum. DEMOCRATIC MODEL: Patient Mogli CHOOSES his care team. AI recommends based on conditions, insurance, ratings, language, proximity. Patient has final say. """ pass ``` **Mogli's Care Team (9 Members, Patient-Selected):** | Role | Provider | Specialty | Why Mogli Chose | |------|----------|-----------|----------------| | PCP | Dr. Bagheera | Internal Medicine | Speaks Hindi, 4.9-star, manages all 5 conditions | | Care Coordinator | Nurse Baloo | RN, Care Coord | Warm, chronic care specialist | | Endocrinologist | Dr. Shere Khan | Endocrinology | Top T2DM specialist in Austin | | Nephrologist | Dr. Hathi | Nephrology | CKD Stage 2, BCBS in-network | | Pulmonologist | Dr. Kaa | Pulmonology | Asthma, telehealth available | | Cardiologist | Dr. Mowgli Sr. | Cardiology | HTN + HLD, preventive | | Clinical Pharmacist | Dr. Raksha | PharmD | Polypharmacy, MTM specialist | | Mental Health | Dr. Rama | PsyD | Diabetes distress, CBT | | Dietitian | Shanti RD | Registered Dietitian | South Asian diet expertise | **Neo4j:** 9 Provider nodes with `HAS_CARE_TEAM_MEMBER` edges. Each edge has `selected_by: 'patient'`. --- ## STAGE 4: TREATMENT INITIATION (Safety Pre-Check Matrix) **LangGraph Node:** `treatment_start_node` | **Agent:** MedicationSafetyAgent + DiagnosisAgent | **Kafka:** `swarmcare.treatment.initiated` ```python async def treatment_start_node(state: SwarmCareState) -> SwarmCareState: """ GATE NODE — Safety pre-check must pass. Loads conditions, medications, allergies, labs, vitals. Runs DDI, allergy cross-reactivity, renal dosing, duplicate therapy, formulary checks. """ pass ``` **5 Active Conditions:** | Condition | ICD-10 | SNOMED-CT | Onset | Status | |-----------|--------|-----------|-------|--------| | Type 2 Diabetes with CKD | E11.65 | 44054006 | 2020-03 | Active | | Essential Hypertension | I10 | 59621000 | 2019-08 | Active | | Mild Persistent Asthma | J45.30 | 195967001 | 2015-05 | Active | | Hyperlipidemia | E78.5 | 55822004 | 2021-01 | Active | | CKD Stage 2 | N18.2 | 431856006 | 2023-06 | Active | **6 Active Medications:** | Medication | Dose | Freq | RxNorm | DrugBank | For | |-----------|------|------|--------|----------|-----| | Metformin | 1000mg | BID | 861004 | DB00331 | T2DM | | Empagliflozin | 10mg | Daily | 1545653 | DB09038 | T2DM + CKD | | Lisinopril | 20mg | Daily | 314076 | DB00722 | HTN + Renoprotection | | Amlodipine | 5mg | Daily | 329526 | DB00381 | HTN | | Atorvastatin | 20mg | Daily HS | 259255 | DB01076 | HLD | | Albuterol | 90mcg | PRN | 307782 | DB01001 | Asthma | **2 Allergies:** | Allergen | Severity | Reaction | Cross-Reactivity | |----------|----------|----------|------------------| | Sulfonamides | Moderate | Rash, Urticaria | Thiazides (caution) | | Shellfish | Mild | GI upset | Iodine contrast (low risk) | **Key Lab Results:** | Test | Value | LOINC | Flag | |------|-------|-------|------| | HbA1c | 7.8% | 4548-4 | HIGH | | Fasting Glucose | 156 mg/dL | 1558-6 | HIGH | | eGFR | 72 mL/min | 48642-3 | LOW | | UACR | 45 mg/g | 9318-7 | HIGH | | LDL | 128 mg/dL | 2089-1 | HIGH | | BP | 142/88 mmHg | 85354-9 | Stage 1 HTN | | BMI | 28.5 | 39156-5 | Overweight | **Safety Pre-Check Matrix Result:** ``` DDI Check: 15 pairs checked, 2 flagged (monitor), 0 blocked - Metformin + Empagliflozin: MONITOR (hypoglycemia risk) - Lisinopril + Empagliflozin: MONITOR (hyperkalemia, K=4.8) Allergy Cross-Reactivity: ALL CLEAR (no sulfa meds prescribed) Renal Dosing (eGFR=72): ALL APPROPRIATE (no adjustments needed) Duplicate Therapy: ALL CLEAR Formulary: Empagliflozin needs Prior Auth (Tier 3, $70/mo) OVERALL: SAFE TO PROCEED ``` **Neo4j:** Creates ~34 nodes (5 Conditions, 6 Medications, 2 Allergies, 11 LabResults, 10 VitalSigns) and ~48 edges (HAS_CONDITION, TAKES_MEDICATION, HAS_ALLERGY, HAS_LAB_RESULT, HAS_VITAL_SIGN, TREATS, INTERACTS_WITH). --- ## STAGE 5: PATIENT DASHBOARD (AI-Powered — 26 Features) **LangGraph Node:** `dashboard_node` | **Agent:** DashboardAgent | **Kafka:** `swarmcare.dashboard.loaded` ```python async def dashboard_node(state: SwarmCareState) -> SwarmCareState: """ Generates personalized AI dashboard with 26 widget features. Calculates Health Score (composite metric 0-100). Renders RPM vitals, medication tracker, care gaps, AI insights. """ pass ``` **Mogli's Dashboard — 26 Features:** | # | Widget | Mogli's Data | Description | |---|--------|-------------|-------------| | 1 | Health Score | 68.5/100 | Composite: HbA1c (25%), BP (20%), eGFR (15%), Adherence (15%), BMI (10%), Activity (10%), Mental (5%) | | 2 | Condition Summary | 5 active chronic | Color-coded severity cards | | 3 | Medication Tracker | 6 meds, 91% adherent | Dose schedule, refill dates, adherence trend | | 4 | RPM Vitals (Live) | CGM 156, BP 142/88 | Real-time wearable data with sparklines | | 5 | Lab Results Timeline | 11 recent labs | Interactive chart with trend arrows | | 6 | Care Gaps | 3 open gaps | Flu vaccine, eye exam, foot exam | | 7 | Upcoming Appointments | 2 this week | Dr. Bagheera (PCP), Dr. Shere Khan (Endo) | | 8 | Care Team | 9 providers | Photo, specialty, message button | | 9 | AI Health Insight | "HbA1c trending up" | Natural language AI interpretation | | 10 | Risk Score | Moderate (62/100) | 30-day hospitalization risk | | 11 | Care Plan Progress | 67% complete | Goal tracking with milestones | | 12 | Message Center | 3 unread | Secure messaging with care team | | 13 | Education Library | 5 assigned | Diabetes, CKD, nutrition content | | 14 | Symptom Log | Last entry: today | Daily symptom diary | | 15 | Activity Tracker | 4,200 steps today | Wearable-synced step/exercise data | | 16 | Nutrition Log | 1,800 cal today | AI-analyzed food diary | | 17 | Mood Tracker | 7/10 today | Daily mental health check-in | | 18 | Sleep Quality | 6.5 hrs, 78% quality | Sleep tracker integration | | 19 | Prior Auth Status | 1 pending (Empagliflozin) | Real-time PA tracking | | 20 | Insurance Summary | $425/$1,500 deductible | Benefits used, remaining | | 21 | Family View | Akela (brother) active | Caregiver dashboard access | | 22 | Emergency Info | Allergies + ICE contact | Quick-access card | | 23 | Telehealth Quick-Start | Join/schedule | One-tap video visit | | 24 | Prescription Refills | Metformin due in 5 days | Auto-refill management | | 25 | Clinical Trial Match | 2 matches | Eligible T2DM trials in Austin | | 26 | Wellness Goals | 3 active goals | Gamified progress tracking | **Neo4j:** DashboardSession node with `health_score: 68.5`, linked via `HAS_DASHBOARD_SESSION`. --- ## STAGE 6: CHRONIC CARE MANAGEMENT (RPM + Digital Therapeutics) **LangGraph Node:** `chronic_care_node` | **Agent:** ChronicCareAgent | **Kafka:** `swarmcare.rpm.reading`, `swarmcare.rpm.alert` ```python async def chronic_care_node(state: SwarmCareState) -> SwarmCareState: """ Manages RPM device enrollment, reading ingestion, threshold alerting, CPT billing code generation (99457, 99458, 99490, 99491). Digital therapeutics enrollment (BlueStar Diabetes). """ pass ``` **Mogli's Connected Devices:** | Device | Model | What It Measures | Reading Frequency | Alert Thresholds | |--------|-------|-----------------|-------------------|-----------------| | CGM | Dexcom G7 | Interstitial glucose | Every 5 min | <70 or >250 mg/dL | | BP Monitor | Omron Evolv | Systolic/Diastolic | 2x daily | >160/100 or <90/60 | | Smart Scale | Withings Body+ | Weight, BMI, body fat | Daily | >5 lbs gain in 3 days | | Peak Flow | Smart PEF | Peak expiratory flow | 2x daily | <80% personal best | **RPM Billing Codes (Monthly):** | CPT | Description | Requirements | Reimbursement | |-----|------------|-------------|---------------| | 99453 | RPM setup | Initial device + education | $19.32 (one-time) | | 99454 | Device supply | 16+ days readings/month | $55.72/month | | 99457 | RPM management | 20+ min clinical time | $50.94/month | | 99458 | Additional 20 min | Each additional 20 min | $42.22/month | | 99490 | CCM | 20+ min non-face-to-face | $62.69/month | | 99491 | CCM (physician) | 30+ min physician time | $86.74/month | **Neo4j:** WearableDevice nodes + RPMReading nodes (time-series) + RPMAlert nodes. --- ## STAGE 7: CLINICAL WORKSTATION (Provider-Facing) **LangGraph Node:** `clinical_workstation_node` | **Agent:** ClinicalDocAgent | **Kafka:** `swarmcare.encounter.documented` Features: Ambient AI documentation (Abridge-style), CPOE (Computerized Provider Order Entry), CDS Hooks integration, real-time patient context panel, multi-condition view, order sets, smart phrases, voice-to-SOAP. --- ## STAGE 8: CONTEXT GRAPH (Knowledge Graph — 13 Ontologies) **LangGraph Node:** `context_graph_node` | **Agent:** KnowledgeGraphAgent | **Kafka:** `swarmcare.graph.updated` ```python async def context_graph_node(state: SwarmCareState) -> SwarmCareState: """ Maps all clinical data to 13 ontology systems. Creates OntologyTerm nodes in Neo4j. Enables PathRAG + GraphRAG hybrid retrieval. Natural language query interface to knowledge graph. """ pass ``` **Mogli's 74 Ontology Terms Across 13 Systems:** | # | Ontology | Term Count | Examples | |---|----------|-----------|---------| | 1 | SNOMED-CT | 7 | T2DM (44054006), HTN (59621000), Asthma (195967001) | | 2 | ICD-11 | 5 | 5A11, BA00, CA23.0, 5C80, GB61.1 | | 3 | ICD-10-CM | 5 | E11.65, I10, J45.30, E78.5, N18.2 | | 4 | RxNorm | 6 | Metformin (861004), Empagliflozin (1545653) | | 5 | LOINC | 8 | HbA1c (4548-4), eGFR (48642-3) | | 6 | CPT | 5 | 99214, 99457, 99490, 90686, 93784 | | 7 | HL7 FHIR R4 | 8 | Patient, Condition, MedicationRequest, Observation | | 8 | UMLS | 5 | C0011860 (Diabetes), C0020538 (Hypertension) | | 9 | HPO | 5 | HP:0003074 (Hyperglycemia), HP:0000822 (HTN) | | 10 | Gene Ontology | 3 | GO:0006006 (Glucose metabolism) | | 11 | DrugBank | 6 | DB00331 (Metformin), DB09038 (Empagliflozin) | | 12 | OMOP CDM | 5 | Standard concept mappings | | 13 | ChEBI | 6 | CHEBI:6801 (Metformin), CHEBI:4031 (Empagliflozin) | **PathRAG Query Example:** ``` User: "Why is Mogli on both Lisinopril and Empagliflozin?" PathRAG Trace: Patient(Mogli) -> HAS_CONDITION -> Condition(T2DM with CKD) Condition(CKD Stage 2) -> TREATED_BY -> Medication(Lisinopril) [renoprotective] Condition(T2DM) -> TREATED_BY -> Medication(Empagliflozin) [glycemic + renal benefit] Medication(Lisinopril) -> INTERACTS_WITH -> Medication(Empagliflozin) [monitor K+] Answer: "Both provide renal protection through different mechanisms - Lisinopril via RAAS blockade, Empagliflozin via tubuloglomerular feedback. Together they slow CKD progression." ``` --- ## STAGES 13-22: PLATFORM MODULES (Summary) These stages correspond to the 10 remaining modules from v2 (Patient Portal through Public Health). Each runs as a LangGraph node in the linear chain. | Stage | Module | Key Features | Agent | |-------|--------|-------------|-------| | 13 | Patient Portal | PHR, secure messaging, lab viewer, bill pay, proxy access | DashboardAgent | | 14 | Doctor Dashboard | Patient panel, inbox, orders, schedules, quality metrics | ClinicalDocAgent | | 15 | Staff Dashboard | Task queues, referral management, PA tracking, bed board | CareCoordinationAgent | | 16 | AI Chat | Symptom Q&A, med info, appointment booking, multi-language | TriageAgent | | 17 | Telehealth | Video visits, screen share, e-prescribe, remote exam | TelehealthAgent | | 18 | Care Plans | SMART goals, care pathways, shared planning, milestone tracking | CareCoordinationAgent | | 19 | Care Gaps | HEDIS/MIPS gaps, preventive screenings, auto-outreach | PopHealthAgent | | 20 | Workflow Engine | Task assignment, escalation rules, SLA tracking, queue management | CareCoordinationAgent | | 21 | Clinical Decision Support | CDS Hooks, order alerts, guideline engine, Infobutton | DiagnosisAgent | | 22 | Predictive Analytics | 30-day readmission risk, deterioration score, no-show prediction | PredictiveAgent | Additional modules (Medical Imaging, Population Health, Clinical Trials, Voice AI, Explainable AI, Public Health) continue in the chain as Stages completing through Stage 22. --- ## STAGE 9: DOCTOR-TO-DOCTOR COMMUNICATION (D2D) — DEEP DIVE **LangGraph Node:** `doctor_communication_node` | **Agent:** CommunicationAgent | **Kafka:** `swarmcare.d2d.message`, `swarmcare.d2d.summary.generated` ```python async def doctor_communication_node(state: SwarmCareState) -> SwarmCareState: """ Enables secure, audited, AI-summarized provider-to-provider communication. Features: 1. Encrypted messaging (AES-256-GCM) between care team members 2. Thread-based dialogue storage with full audit trail 3. AI summarization of multi-message conversations 4. Auto-extraction of clinical decisions, action items, follow-ups 5. Patient visibility toggle (transparency by default) 6. Image/file attachment support (DICOM, labs, photos) 7. Priority flagging (routine, urgent, critical) 8. Read receipts + response time tracking 9. Auto-tagging by condition, medication, or care topic 10. Integration with clinical workstation inbox """ pass ``` **D2D Feature Set (25 Features):** | # | Feature | Description | |---|---------|-------------| | 1 | Secure Messaging | AES-256-GCM encrypted, HIPAA-compliant | | 2 | Thread Management | Conversations grouped by topic/patient/condition | | 3 | Dialogue Storage | Every message stored as Neo4j CommunicationLog node | | 4 | AI Conversation Summary | LLM generates DoctorDialogue summary after thread closes | | 5 | Clinical Decision Extraction | AI extracts decisions, rationale, action items | | 6 | Action Item Tracking | Auto-generated tasks with assignee and due date | | 7 | Patient Visibility | Summaries shared with patient (opt-in, default: ON) | | 8 | Priority Levels | Routine / Urgent / Critical / Emergency | | 9 | Read Receipts | Delivery confirmation + read time tracking | | 10 | Response SLA | Urgent: 1hr, Critical: 15min, Emergency: immediate | | 11 | File Attachments | Labs, imaging, wound photos, ECG strips | | 12 | DICOM Viewer | Inline medical image viewing | | 13 | @Mention Providers | Tag specific team members for attention | | 14 | Condition Tagging | Auto-tag conversations by ICD-10/SNOMED condition | | 15 | Medication Discussion | Flag when medications are discussed (DDI awareness) | | 16 | Referral Request | Initiate specialist referral within D2D thread | | 17 | Curbside Consult | Quick informal consult (documented, lower friction) | | 18 | Multi-Provider Thread | 3+ providers in single conversation | | 19 | Template Messages | Pre-built templates for common discussions | | 20 | Voice Message | Audio message with auto-transcription | | 21 | Translation | Auto-translate between provider languages | | 22 | Escalation Rules | Auto-escalate if no response within SLA | | 23 | Analytics | Communication frequency, response time, topic trends | | 24 | Compliance Logging | Every message logged for HIPAA audit | | 25 | Smart Notifications | Context-aware: suppress low-priority during procedures | **Mogli's D2D Communication — Example Exchange:** ``` THREAD: "Mogli Patel - BP Management + Renal Considerations" Thread ID: D2D-MOGLI-001 Started: 2026-02-22T10:00:00Z Participants: Dr. Bagheera (PCP), Dr. Shere Khan (Endo), Dr. Hathi (Nephro) Priority: URGENT Condition Tags: [HTN - I10], [CKD Stage 2 - N18.2], [T2DM - E11.65] ───────────────────────────────────────────────── MSG-001 | Dr. Bagheera (PCP) | 10:00 AM ───────────────────────────────────────────────── Mogli's BP is consistently running 142/88 despite Lisinopril 20mg + Amlodipine 5mg. eGFR 72 and UACR 45 — CKD progressing. @Dr. Shere Khan @Dr. Hathi — should we intensify antihypertensives or prioritize Empagliflozin for renal protection? [Attached: BP_Trend_Chart.pdf, Lab_Results_Feb2026.pdf] ───────────────────────────────────────────────── MSG-002 | Dr. Shere Khan (Endo) | 10:22 AM ───────────────────────────────────────────────── The UACR of 45 is concerning. Empagliflozin at 10mg is already providing some renoprotection, but I'd prioritize BP control first. CREDENCE and DAPA-CKD trials show that SGLT2i benefits are additive to RAAS blockade. I recommend increasing Lisinopril to 40mg before adding a third antihypertensive. ───────────────────────────────────────────────── MSG-003 | Dr. Hathi (Nephro) | 10:45 AM ───────────────────────────────────────────────── Agree with increasing Lisinopril to 40mg. Monitor K+ closely (currently 4.8 — approaching upper limit). Recheck BMP in 2 weeks. If BP remains uncontrolled, consider chlorthalidone BUT be cautious given sulfonamide allergy — thiazides have structural similarity. Would recommend indapamide instead if diuretic needed. Target BP <130/80 per KDIGO 2024 guidelines for CKD + diabetes. ───────────────────────────────────────────────── MSG-004 | Dr. Bagheera (PCP) | 11:02 AM ───────────────────────────────────────────────── Excellent points. Plan: 1. Increase Lisinopril 20mg -> 40mg daily 2. Recheck BMP + K+ in 2 weeks 3. If BP still >130/80 in 4 weeks, add Indapamide 1.25mg (not HCTZ - sulfa allergy) 4. Continue Empagliflozin 10mg for dual benefit 5. Schedule Mogli for follow-up BP check in 2 weeks Sharing summary with Mogli per his transparency preference. Thanks team! ───────────────────────────────────────────────── ``` **AI-Generated Summary (DoctorDialogue Node):** ```json { "dialogue_id": "DIA-MOGLI-001", "thread_id": "D2D-MOGLI-001", "patient_id": "PAT-MOGLI-001", "participants": ["Dr. Bagheera", "Dr. Shere Khan", "Dr. Hathi"], "summary": "Care team discussed Mogli's suboptimal BP control (142/88) despite dual antihypertensive therapy, in context of CKD Stage 2 (eGFR 72, UACR 45). Decision: Increase Lisinopril from 20mg to 40mg. If BP remains above target after 4 weeks, add Indapamide 1.25mg instead of HCTZ due to sulfonamide allergy. Continue Empagliflozin for dual glycemic and renal benefit. Monitor potassium closely given current level of 4.8.", "clinical_decisions": [ {"decision": "Increase Lisinopril 20mg to 40mg daily", "rationale": "BP 142/88 above target <130/80 per KDIGO 2024", "decided_by": "consensus"}, {"decision": "Avoid thiazides, use Indapamide if needed", "rationale": "Sulfonamide allergy cross-reactivity risk", "decided_by": "Dr. Hathi"}, {"decision": "Continue Empagliflozin 10mg", "rationale": "CREDENCE/DAPA-CKD dual benefit", "decided_by": "Dr. Shere Khan"} ], "action_items": [ {"action": "Increase Lisinopril to 40mg", "assignee": "Dr. Bagheera", "due": "2026-02-22", "status": "pending"}, {"action": "Order BMP + K+ recheck", "assignee": "Dr. Bagheera", "due": "2026-03-08", "status": "pending"}, {"action": "Schedule BP follow-up", "assignee": "Nurse Baloo", "due": "2026-03-08", "status": "pending"}, {"action": "Review BP trend in 4 weeks", "assignee": "Dr. Hathi", "due": "2026-03-22", "status": "pending"}, {"action": "Initiate Empagliflozin PA", "assignee": "Dr. Raksha", "due": "2026-02-23", "status": "pending"} ], "conditions_discussed": ["I10", "N18.2", "E11.65"], "medications_discussed": ["Lisinopril", "Empagliflozin", "Indapamide", "HCTZ"], "guidelines_referenced": ["KDIGO 2024", "CREDENCE Trial", "DAPA-CKD Trial"], "patient_shared": true, "generated_at": "2026-02-22T11:05:00Z" } ``` **Patient-Facing Summary (Shared with Mogli):** > "Your doctors discussed your blood pressure, which has been running higher than the target. They decided to increase your Lisinopril from 20mg to 40mg to better control it. They'll recheck your blood work in 2 weeks to make sure your kidneys and potassium are handling the higher dose well. Your Empagliflozin is helping both your diabetes and kidney health, so that stays the same. If your blood pressure is still high after 4 weeks, they may add another medication." **Neo4j — Communication + Dialogue Nodes:** ```cypher // Store each message as CommunicationLog CREATE (msg:CommunicationLog { message_id: 'MSG-D2D-MOGLI-001', thread_id: 'D2D-MOGLI-001', sender_id: 'PROV-BAGHEERA-001', sender_role: 'PCP', recipients: ['PROV-SHERE-KHAN-001', 'PROV-HATHI-001'], content_encrypted: true, priority: 'urgent', condition_tags: ['I10', 'N18.2', 'E11.65'], has_attachments: true, attachment_types: ['pdf', 'pdf'], sent_at: datetime('2026-02-22T10:00:00Z'), read_by: ['PROV-SHERE-KHAN-001', 'PROV-HATHI-001'], read_at: [datetime('2026-02-22T10:15:00Z'), datetime('2026-02-22T10:30:00Z')] }) // Store AI-generated dialogue summary CREATE (dia:DoctorDialogue { dialogue_id: 'DIA-MOGLI-001', thread_id: 'D2D-MOGLI-001', participants: ['Dr. Bagheera', 'Dr. Shere Khan', 'Dr. Hathi'], message_count: 4, summary: 'BP management discussion. Decision: Increase Lisinopril to 40mg...', clinical_decisions: 3, action_items: 5, action_items_completed: 0, guidelines_referenced: ['KDIGO 2024', 'CREDENCE', 'DAPA-CKD'], patient_shared: true, generated_at: datetime('2026-02-22T11:05:00Z') }) // Link to Patient MATCH (p:Patient {patient_id: 'PAT-MOGLI-001'}) MATCH (dia:DoctorDialogue {dialogue_id: 'DIA-MOGLI-001'}) CREATE (p)-[:HAS_D2D_DIALOGUE {validity: 'current', created_at: datetime()}]->(dia) ``` **API Endpoints:** ``` POST /api/v1/d2d/messages — Send D2D message GET /api/v1/d2d/threads/{patient_id} — List all threads for patient GET /api/v1/d2d/threads/{thread_id}/messages — Get messages in thread POST /api/v1/d2d/threads/{thread_id}/summarize — Trigger AI summarization GET /api/v1/d2d/dialogues/{patient_id} — Get AI-generated summaries GET /api/v1/d2d/action-items/{patient_id} — Get pending action items POST /api/v1/d2d/messages/{msg_id}/read — Mark as read ``` --- ## STAGE 10: CARE AUDIO & AMBIENT DOCUMENTATION — DEEP DIVE **LangGraph Node:** `care_audio_node` | **Agent:** AudioAgent | **Kafka:** `swarmcare.audio.recorded`, `swarmcare.audio.transcribed`, `swarmcare.soap.generated` ```python async def care_audio_node(state: SwarmCareState) -> SwarmCareState: """ Three pillars of care audio: 1. AMBIENT ENCOUNTER DOCUMENTATION — Record visit, auto-generate SOAP note 2. PATIENT EDUCATION AUDIO — AI-generated explanations in patient's language 3. CARE TEAM PODCAST — Weekly AI-generated audio digest per provider Pipeline: Audio -> Whisper Transcription -> NLP Processing -> SOAP/Summary """ pass ``` **Pillar 1: Ambient Encounter Documentation (Abridge/Augmedix-style)** ``` ENCOUNTER RECORDING — Dr. Bagheera + Mogli Patel Date: 2026-02-22 | Duration: 18 min 32 sec | Type: Follow-up Visit Consent: Audio Recording Consent (CONSENT-MOGLI-010) = SIGNED Pipeline: Audio (WAV/FLAC) → Whisper v3 Transcription → Speaker Diarization → Medical NLP Entity Extraction → SOAP Note Generation → ICD-10 Auto-Coding → CPT Auto-Coding → Provider Review Queue AUTO-GENERATED SOAP NOTE: ━━━━━━━━━━━━━━━━━━━━━━━ SUBJECTIVE: Chief Complaint: Follow-up for diabetes, hypertension, and kidney function HPI: 37M with T2DM (6 years), HTN, CKD Stage 2, HLD, and asthma presents for routine follow-up. Reports increased thirst and fatigue over past 2 weeks. Home glucose readings averaging 150-180 mg/dL fasting. BP readings at home consistently 138-145/85-90. Medication adherence self-reported at ~90%. Denies chest pain, SOB at rest, edema. Asthma well-controlled, using albuterol ~1x/week. Diet compliance "fair" - admits to occasional high-carb meals. ROS: Positive for polyuria, polydipsia, fatigue. Negative for 12 other systems. OBJECTIVE: Vitals: BP 142/88, HR 78, RR 16, T 98.4F, SpO2 97%, BMI 28.5 General: Well-appearing, NAD HEENT: PERRL, EOMI, no thyromegaly CV: RRR, no murmurs, no JVD, no edema Lungs: CTAB, no wheezing Abdomen: Soft, NT, ND, +BS Extremities: No edema, pulses 2+ bilateral, monofilament intact Skin: No ulcers, no acanthosis nigricans ASSESSMENT: 1. T2DM with CKD - suboptimal control (HbA1c 7.8%, target <7%) 2. HTN - above target (142/88, target <130/80 per KDIGO) 3. CKD Stage 2 - stable but UACR elevated at 45 4. HLD - LDL 128, above target of <100 5. Asthma - well-controlled on PRN albuterol PLAN: 1. Increase Lisinopril 20mg -> 40mg daily (per D2D discussion) 2. Continue Metformin 1000mg BID + Empagliflozin 10mg daily 3. Consider increasing Atorvastatin 20mg -> 40mg if LDL not at target in 3mo 4. Recheck BMP, K+, eGFR, UACR in 2 weeks 5. Recheck HbA1c in 3 months 6. Refer to Shanti RD for medical nutrition therapy 7. Care gaps: Schedule diabetic eye exam, foot exam, flu vaccine 8. Follow-up: 2 weeks for BP recheck, 3 months for comprehensive AUTO-CODED: ICD-10: E11.65, I10, N18.2, E78.5, J45.30 CPT: 99214 (Established, moderate MDM), 93784 (ABPM) E/M Level: 4 (moderate complexity, 25 min total time) STATUS: Pending Dr. Bagheera review and sign-off ``` **Pillar 2: Patient Education Audio (AI-Generated)** ```json { "audio_id": "AUDIO-EDU-MOGLI-001", "type": "education_audio", "title": "Understanding Your Kidney Health and Diabetes", "language": "en", "secondary_language_version": "hi", "duration_seconds": 180, "reading_level": "6th grade", "content_summary": "Explains connection between diabetes and kidney disease, why eGFR and UACR are important, how medications protect kidneys, dietary changes to slow progression.", "personalized_for": "PAT-MOGLI-001", "conditions_addressed": ["E11.65", "N18.2"], "generated_at": "2026-02-22T11:30:00Z", "tts_engine": "ElevenLabs Medical Voice", "reviewed_by": "Dr. Bagheera" } ``` **Pillar 3: Care Team Podcast (NotebookLM-style Weekly Digest)** ```json { "podcast_id": "PODCAST-BAGHEERA-W08-2026", "type": "care_team_podcast", "provider_id": "PROV-BAGHEERA-001", "title": "Dr. Bagheera's Week 8 Patient Panel Digest", "duration_seconds": 420, "format": "two_host_discussion", "content": { "patient_highlights": [ "Mogli Patel: BP still above target, Lisinopril increased, watch K+", "3 other patients with notable changes this week" ], "care_gaps_due": "7 patients overdue for preventive screenings", "lab_results_pending": "12 results awaiting review", "action_items_open": "15 open items across panel", "upcoming_appointments": "28 visits scheduled next week" }, "generated_at": "2026-02-23T06:00:00Z" } ``` **Neo4j — Audio Recording Nodes:** ```cypher CREATE (ar:AudioRecording { audio_id: 'AUDIO-ENC-MOGLI-001', type: 'encounter_audio', encounter_id: 'ENC-MOGLI-20260222', duration_seconds: 1112, provider_id: 'PROV-BAGHEERA-001', transcription_status: 'complete', soap_generated: true, soap_status: 'pending_review', icd10_auto_coded: ['E11.65', 'I10', 'N18.2', 'E78.5', 'J45.30'], cpt_auto_coded: ['99214', '93784'], consent_id: 'CONSENT-MOGLI-010', recorded_at: datetime('2026-02-22T09:30:00Z') }) MATCH (p:Patient {patient_id: 'PAT-MOGLI-001'}) MATCH (ar:AudioRecording {audio_id: 'AUDIO-ENC-MOGLI-001'}) CREATE (p)-[:HAS_AUDIO_RECORDING {validity: 'current', created_at: datetime()}]->(ar) ``` --- ## STAGE 11: AI ANNOUNCEMENTS & PATIENT INSTRUCTIONS — DEEP DIVE **LangGraph Node:** `ai_announcements_node` | **Agent:** InstructionAgent | **Kafka:** `swarmcare.announcement.sent`, `swarmcare.instruction.delivered`, `swarmcare.alert.escalated` ```python async def ai_announcements_node(state: SwarmCareState) -> SwarmCareState: """ Three sub-systems: 1. AI ANNOUNCEMENTS — Personalized patient communications 2. PATIENT INSTRUCTIONS — Structured clinical instructions (AVS, discharge, pre-visit) 3. ALERT DOCTOR SYSTEM — Multi-level escalation with fatigue prevention """ pass ``` **Sub-System 1: AI Announcements (Personalized to Mogli)** | # | Announcement Type | Channel | Time | Example for Mogli | |---|------------------|---------|------|-------------------| | 1 | Daily Health Briefing | Push + App | 7:00 AM | "Good morning Mogli! Your glucose overnight averaged 142. Remember to take Metformin with breakfast. You have a virtual visit with Dr. Bagheera at 2 PM." | | 2 | Medication Reminder | Push + SMS | Per schedule | "Time for your evening Atorvastatin 20mg. Take with or without food." | | 3 | Achievement Alert | Push | On trigger | "Great work! You've been 91% adherent to medications this month — up from 85% last month!" | | 4 | Lab Result Ready | Push + Email | On result | "Your lab results from Feb 15 are ready. Dr. Bagheera has reviewed them. Tap to view." | | 5 | Care Gap Nudge | Push | Weekly | "You're due for your annual diabetic eye exam. Want me to find available appointments?" | | 6 | RPM Insight | Push | On anomaly | "Your BP readings this week average 140/87 — slightly above your 130/80 target. Dr. Bagheera has been notified." | | 7 | Appointment Prep | Push + Email | 24hr before | "Your visit with Dr. Shere Khan is tomorrow at 10 AM. Please fast for 8 hours before. Here's what to expect." | | 8 | Refill Reminder | Push + SMS | 5 days before | "Your Metformin prescription has 5 days remaining. Auto-refill is scheduled. Tap to modify." | | 9 | Wellness Tip | Push | 3x/week | "Try a 15-minute walk after lunch — studies show it can reduce post-meal glucose by 20-30%." | | 10 | Weekly Summary | Email + App | Sunday AM | "This week: Health Score 68.5 (+1.2), BP avg 140/87, Glucose avg 152, Steps avg 4,200" | **Sub-System 2: Patient Instructions (Structured Clinical)** **After-Visit Summary (AVS) — Generated from Stage 10 SOAP:** ```json { "instruction_id": "INST-MOGLI-AVS-001", "type": "after_visit_summary", "encounter_id": "ENC-MOGLI-20260222", "provider": "Dr. Bagheera", "visit_date": "2026-02-22", "language": "en", "reading_level": "6th_grade", "sections": { "what_we_discussed": "We reviewed your diabetes, blood pressure, and kidney health. Your HbA1c is 7.8% (target is below 7%). Your blood pressure is 142/88 (target is below 130/80).", "medication_changes": [ {"change": "INCREASED", "medication": "Lisinopril", "from": "20mg daily", "to": "40mg daily", "reason": "To better control blood pressure and protect kidneys", "start_date": "2026-02-22"} ], "new_orders": [ "Blood test (BMP, K+) in 2 weeks at Quest Diagnostics", "HbA1c recheck in 3 months", "Referral to Shanti RD (Dietitian) for nutrition counseling" ], "follow_up": "Return in 2 weeks for blood pressure recheck with Dr. Bagheera", "red_flags": [ "Call us immediately if: dizziness/lightheadedness, swelling in legs/feet, significantly decreased urine output, muscle cramps or weakness", "Go to ER if: chest pain, difficulty breathing, severe headache with vision changes" ], "self_care": [ "Check blood pressure twice daily and log results", "Continue checking blood sugar before meals", "Low-sodium diet (<2,000mg/day) to support blood pressure", "Walk 30 minutes daily" ] }, "delivery_methods": ["app_notification", "email", "patient_portal"], "patient_acknowledged": true, "acknowledged_at": "2026-02-22T14:30:00Z" } ``` **Sub-System 3: Alert Doctor System (4-Level Escalation)** ``` ALERT ESCALATION FRAMEWORK: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ LEVEL 1 — ROUTINE (Green) Response: 24 hours | Channel: Inbox notification Example: "Mogli's adherence dropped to 85% this week" LEVEL 2 — URGENT (Yellow) Response: 4 hours | Channel: Push + SMS + Inbox Example: "Mogli's BP reading 158/95 — above urgent threshold" LEVEL 3 — CRITICAL (Orange) Response: 1 hour | Channel: Push + SMS + Phone call (auto) Example: "Mogli's glucose 42 mg/dL — severe hypoglycemia detected by CGM" LEVEL 4 — EMERGENCY (Red) Response: Immediate | Channel: All + 911 coordination Example: "Mogli's CGM shows prolonged glucose <40 + no movement detected" Auto-action: Notify emergency contact (Akela), prepare ER briefing packet ALERT FATIGUE PREVENTION: - AI filtering: Suppress duplicate alerts within 30-min window - Smart bundling: Group related alerts (e.g., 3 high BPs → 1 trend alert) - Quiet hours: Non-critical alerts held 10 PM - 7 AM (patient preference) - Context awareness: Suppress "high glucose" alert after known high-carb meal - Provider workload: Route to on-call if primary at capacity - Escalation tracking: Measure alert-to-action time, identify fatigue patterns ``` **Mogli's Active Alerts:** | Alert ID | Level | Trigger | Message | Routed To | Status | |----------|-------|---------|---------|-----------|--------| | ALERT-001 | URGENT | BP 158/95 | "BP above urgent threshold" | Dr. Bagheera | Acknowledged | | ALERT-002 | ROUTINE | HbA1c 7.8% | "HbA1c above target, trending up" | Dr. Shere Khan | Pending | | ALERT-003 | ROUTINE | Eye exam overdue | "Diabetic eye exam 3 months overdue" | Nurse Baloo | Scheduled | **Neo4j:** ```cypher CREATE (alert:Alert { alert_id: 'ALERT-MOGLI-001', level: 'urgent', trigger_type: 'rpm_threshold', trigger_value: 'BP 158/95', message: 'BP above urgent threshold of 150/95', routed_to: 'PROV-BAGHEERA-001', acknowledged: true, acknowledged_at: datetime('2026-02-22T10:15:00Z'), action_taken: 'Lisinopril increased per D2D thread', created_at: datetime('2026-02-22T09:45:00Z') }) ``` --- ## STAGE 12: CARE HANDOFF COORDINATION — DEEP DIVE **LangGraph Node:** `care_handoff_node` | **Agent:** HandoffAgent | **Kafka:** `swarmcare.handoff.initiated`, `swarmcare.handoff.confirmed` ```python async def care_handoff_node(state: SwarmCareState) -> SwarmCareState: """ Multi-protocol care handoff coordination with AI-generated documentation. Supported Protocols: I-PASS, SBAR, ISBAR3 Handoff Types: shift, provider-to-provider, specialist referral, hospital-to-home, facility-to-facility, PCP-to-specialist Features: 1. AUTO-GENERATED I-PASS from patient data (no manual entry) 2. Real-time handoff quality scoring 3. Receiving provider confirmation (closed-loop) 4. Patient notification of handoff 5. Continuity verification (no dropped tasks/orders) """ pass ``` **6 Handoff Types Supported:** | Type | From → To | Trigger | Protocol | Example for Mogli | |------|-----------|---------|----------|------------------| | Shift | Dr. A → Dr. B | End of shift | I-PASS | Night coverage handoff | | Provider-to-Provider | PCP → PCP | Provider leave | I-PASS | Dr. Bagheera vacation coverage | | Specialist Referral | PCP → Specialist | New consult | SBAR | Referral to Dr. Hathi (Nephro) | | Hospital-to-Home | Inpatient → Outpatient | Discharge | I-PASS + SBAR | Post-admission transition | | Facility-to-Facility | Hospital A → B | Transfer | ISBAR3 | Inter-facility transfer | | PCP-to-Specialist | PCP → Specialist | Ongoing | SBAR | Monthly Endo update | **AI-Generated I-PASS for Mogli (Auto-Generated from SwarmCareState):** ``` ╔══════════════════════════════════════════════════════════════════════╗ ║ I-PASS HANDOFF — Mogli Patel (PAT-MOGLI-001) ║ ║ Generated: 2026-02-22T16:00:00Z | Type: Shift Handoff ║ ║ From: Dr. Bagheera (Day) → Dr. Akela-Cover (Night) ║ ╠══════════════════════════════════════════════════════════════════════╣ ║ ║ ║ I — ILLNESS SEVERITY: MODERATE ║ ║ • 37M with 5 chronic conditions (T2DM, HTN, CKD2, HLD, Asthma)║ ║ • Suboptimal BP control (142/88), HbA1c above target (7.8%) ║ ║ • CKD Stage 2 with elevated UACR (45 mg/g) ║ ║ • Medication change today: Lisinopril 20mg → 40mg ║ ║ • Currently STABLE, monitoring for response to dose change ║ ║ ║ ║ P — PATIENT SUMMARY: ║ ║ Mogli is a 37-year-old software engineer with T2DM (6 years), ║ ║ HTN, CKD Stage 2, HLD, and mild persistent asthma. He was ║ ║ seen today for routine follow-up. BP remains above target ║ ║ despite dual therapy. Lisinopril increased to 40mg today. ║ ║ Empagliflozin providing dual glycemic and renal benefit. ║ ║ Sulfonamide allergy (rash/urticaria) — avoid thiazides. ║ ║ RPM devices: Dexcom G7 CGM, Omron Evolv BP monitor. ║ ║ ║ ║ A — ACTION LIST: ║ ║ 1. Monitor BP via RPM — alert if >160/100 or symptoms ║ ║ 2. Monitor glucose via CGM — alert if <70 or >250 ║ ║ 3. Watch for hyperkalemia symptoms (K+ is 4.8, on Lisinopril ║ ║ + Empagliflozin) ║ ║ 4. BMP + K+ ordered for 2026-03-08 at Quest ║ ║ 5. Pending: Empagliflozin prior authorization ║ ║ 6. Referral to Shanti RD (dietitian) submitted ║ ║ 7. Care gaps: Diabetic eye exam, foot exam, flu vaccine ║ ║ ║ ║ S — SITUATION AWARENESS & CONTINGENCY: ║ ║ IF BP >160/100 → Contact patient, consider ER if symptomatic ║ ║ IF glucose <70 → Ensure patient has fast-acting carbs, advise ║ ║ IF K+ >5.5 → Hold Lisinopril, notify Dr. Bagheera ║ ║ IF decreased urine output → Assess for AKI, check Cr/BUN ║ ║ IF asthma exacerbation → Albuterol PRN, assess need for oral ║ ║ steroids (note: steroids will spike glucose) ║ ║ IF dizziness/syncope → May be from Lisinopril increase, ║ ║ check orthostatic BP ║ ║ ║ ║ S — SYNTHESIS BY RECEIVER: ║ ║ □ Receiver confirms understanding of illness severity ║ ║ □ Receiver confirms awareness of medication change today ║ ║ □ Receiver confirms contingency plans for K+, BP, glucose ║ ║ □ Receiver asks clarifying questions ║ ║ □ Receiver accepts handoff responsibility ║ ║ ║ ║ HANDOFF QUALITY SCORE: 94/100 ║ ║ (Completeness: 96, Accuracy: 95, Timeliness: 92, Confirmation: 93)║ ╚══════════════════════════════════════════════════════════════════════╝ ``` **SBAR for Specialist Referral (Mogli → Nephrology):** ``` SITUATION: Referring Mogli Patel (37M) to Nephrology for CKD Stage 2 co-management in setting of T2DM BACKGROUND: T2DM x6 years, HTN x7 years, eGFR 72 (declining from 85 in 2024), UACR 45 mg/g. On Lisinopril 40mg + Empagliflozin 10mg. Sulfonamide allergy. K+ 4.8. ASSESSMENT: CKD Stage 2 with microalbuminuria, likely diabetic nephropathy. Renal function declining ~6.5 mL/min/year. Risk of progression to Stage 3 within 2 years without intervention. RECOMMENDATION: Request nephrology co-management for: (1) renal-protective medication optimization, (2) UACR monitoring protocol, (3) dietary guidance for CKD + DM, (4) assess need for nephrology-specific labs (Cystatin C, phosphorus, PTH). ``` **Neo4j — Handoff Record:** ```cypher CREATE (ho:HandoffRecord { handoff_id: 'HANDOFF-MOGLI-001', type: 'shift_handoff', protocol: 'I-PASS', from_provider: 'PROV-BAGHEERA-001', to_provider: 'PROV-AKELA-COVER-001', illness_severity: 'MODERATE', action_items_count: 7, contingency_plans: 6, quality_score: 94, receiver_confirmed: true, confirmed_at: datetime('2026-02-22T16:15:00Z'), patient_notified: true, auto_generated: true, created_at: datetime('2026-02-22T16:00:00Z') }) MATCH (p:Patient {patient_id: 'PAT-MOGLI-001'}) MATCH (ho:HandoffRecord {handoff_id: 'HANDOFF-MOGLI-001'}) CREATE (p)-[:HAS_HANDOFF {validity: 'current', created_at: datetime()}]->(ho) ``` --- ## STAGES 23-41: WORLD-CLASS MODULES (Summary Table) | Stage | Module | Key Features | Mogli Example | Neo4j Node | |-------|--------|-------------|---------------|------------| | 23 | Family & Caregiver | Proxy access, Zarit Burden Scale, caregiver dashboard | Akela (full), Sita (read-only), Zarit: 28 (mild burden) | FamilyMember | | 24 | Pharmacy Integration | E-prescribing (NCPDP SCRIPT), formulary check, PGx dosing | Express Scripts linked, auto-refill Metformin | PharmacyOrder | | 25 | Insurance & Prior Auth | Auto FHIR Prior Auth, real-time eligibility, appeals | Empagliflozin PA: approved in 2.4 hrs (vs 14-21 days manual) | PriorAuth | | 26 | Appointment Management | AI scheduling, no-show prediction (92% accuracy), NEMT | Next: Dr. Bagheera 2/25, Dr. Shere Khan 3/1 | Appointment | | 27 | Genomics & Precision | PGx panel, polygenic risk, pharmacogenomic dosing | CYP2C19 normal metabolizer, SLCO1B1 normal (atorvastatin safe) | GenomicProfile | | 28 | Mental Health | PHQ-9, GAD-7, Diabetes Distress Scale, CBT referral | PHQ-9: 7 (mild), GAD-7: 5 (mild), DDS: 2.3 (moderate) | MentalHealthScreen | | 29 | Patient Feedback | NPS, HCAHPS alignment, AI sentiment, complaint tracking | NPS: 72, Overall satisfaction: 4.3/5 | PatientFeedback | | 30 | Education Content | Multi-language, multi-format, health literacy adaptation | 5 modules assigned: Diabetes 101, CKD Basics, etc. | EducationContent | | 31 | Audit & Compliance | HIPAA logging, immutable trail, MIPS/HEDIS reporting | 847 audit events logged, 100% compliant | AuditTrail | | 32 | SDoH | PRAPARE screening, Z-codes, community resource matching | Food security: adequate, Housing: stable, Transport: adequate | SDoHAssessment | | 33 | Digital Therapeutics | FDA-cleared DTx, prescription DTx management | BlueStar Diabetes (enrollment pending) | DigitalTherapeutic | | 34 | Transportation | NEMT coordination, ride-hailing integration, cost tracking | Uber Health linked, next ride scheduled 2/25 | TransportRequest | | 35 | Nutrition & Diet | Medical nutrition therapy, meal planning, food logging | South Asian diet adapted, 1800 cal/day, low sodium | NutritionPlan | | 36 | Advance Directives | Living will, healthcare proxy, POLST, code status | Full Code, healthcare proxy: Akela Patel | AdvanceDirective | | 37 | Second Opinion | Virtual second opinion facilitation, record sharing | Not currently requested | SecondOpinion | | 38 | Rehabilitation | PT/OT tracking, exercise Rx, recovery milestones | Exercise Rx: 150 min/week moderate activity | RehabPlan | | 39 | Community Resources | 211 integration, social services, support groups | Austin Diabetes Support Group, YMCA diabetes prevention | CommunityResource | | 40 | Research Consent | Biobank consent, clinical trial enrollment, data donation | Opted in: anonymized data for T2DM research | ResearchConsent | | 41 | Wellness Goals | SMART goals, gamification, streaks, rewards | Goal 1: HbA1c <7%, Goal 2: 7000 steps/day, Goal 3: BP <130/80 | WellnessGoal | --- ## STAGE 42: MEDICATION RECONCILIATION (AI-BPMH) — NEW, NO COMPETITOR HAS THIS **LangGraph Node:** `medication_reconciliation_node` | **Agent:** MedicationSafetyAgent | **Kafka:** `swarmcare.medrec.completed` ```python async def medication_reconciliation_node(state: SwarmCareState) -> SwarmCareState: """ AI-Driven Medication Reconciliation at EVERY transition of care. Implements AHRQ MATCH Toolkit + Joint Commission NPSG.03.06.01. Creates Best Possible Medication History (BPMH) by: 1. Pull current med list from SwarmCare state 2. Query pharmacy claims (NCPDP/Surescripts) 3. Query insurance formulary (Express Scripts) 4. Patient interview (structured or voice) 5. Cross-reference community pharmacy records 6. AI comparison: current vs prescribed vs claimed vs patient-reported 7. Flag discrepancies: omissions, duplications, dosing errors, DDIs 8. Pharmacist review queue for flagged items 9. Reconciled list approved and communicated to all providers Trigger Points: - Admission to any care setting - Transfer between units/facilities - Discharge from any care setting - New provider added to care team - Every scheduled encounter (proactive) Research basis: 67% of medication histories have errors (NCBI). 26% of charts have discrepancies at prescription renewal. AI MedRec reduces errors by 50-64% (pharmacist-driven studies). """ pass ``` **Mogli's Medication Reconciliation:** ``` BEST POSSIBLE MEDICATION HISTORY (BPMH) — Mogli Patel ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Reconciliation Date: 2026-02-22 Trigger: Routine encounter + Lisinopril dose change Reconciled By: Dr. Raksha (PharmD) + AI MedRec Engine SOURCE COMPARISON: ┌──────────────────┬─────────────────┬──────────────────┬──────────────────┐ │ Medication │ SwarmCare List │ Pharmacy Claims │ Patient Reports │ ├──────────────────┼─────────────────┼──────────────────┼──────────────────┤ │ Metformin 1000mg │ BID ✓ │ BID ✓ │ "I take it twice"│ │ Empagliflozin │ 10mg daily ✓ │ 10mg daily ✓ │ "The new one" ✓ │ │ Lisinopril │ 40mg daily *NEW │ 20mg (old fill) │ "Just increased" │ │ Amlodipine │ 5mg daily ✓ │ 5mg daily ✓ │ ✓ │ │ Atorvastatin │ 20mg HS ✓ │ 20mg ✓ │ ✓ │ │ Albuterol PRN │ 90mcg ✓ │ Last fill 45d ago│ "Rarely use" ✓ │ │ Vitamin D3 │ NOT LISTED │ NOT CLAIMED │ "I take 2000 IU" │ │ Fish Oil │ NOT LISTED │ NOT CLAIMED │ "Sometimes" │ │ Turmeric suppl │ NOT LISTED │ NOT CLAIMED │ "For inflammation"│ └──────────────────┴─────────────────┴──────────────────┴──────────────────┘ DISCREPANCIES FOUND: 3 1. OMISSION: Vitamin D3 2000 IU not in medical record → Action: Add to medication list, check 25-OH Vitamin D level → Clinical significance: MODERATE (CKD patients need Vitamin D monitoring) 2. OMISSION: Fish oil (Omega-3) intermittent use not documented → Action: Add to medication list as PRN supplement → Clinical significance: LOW (but monitor with Atorvastatin for myalgia) 3. SUPPLEMENT INTERACTION: Turmeric (curcumin) may interact with Metformin → Action: Counsel patient — turmeric can potentiate hypoglycemia → Clinical significance: MODERATE (monitor blood glucose) RECONCILED MEDICATION LIST (Final — Approved by Dr. Raksha): 1. Metformin 1000mg PO BID — CONTINUE 2. Empagliflozin 10mg PO Daily — CONTINUE 3. Lisinopril 40mg PO Daily — CHANGED (was 20mg) 4. Amlodipine 5mg PO Daily — CONTINUE 5. Atorvastatin 20mg PO QHS — CONTINUE 6. Albuterol 90mcg INH PRN — CONTINUE 7. Vitamin D3 2000 IU PO Daily — ADDED (patient-reported) 8. Fish Oil (Omega-3) 1000mg PO Daily PRN — ADDED (patient-reported) 9. Turmeric supplement — COUNSELED (interaction risk with Metformin) ``` **Neo4j:** ```cypher CREATE (mr:MedicationReconciliation { reconciliation_id: 'MEDREC-MOGLI-001', trigger: 'routine_encounter_dose_change', sources_checked: ['swarmcare', 'pharmacy_claims', 'patient_interview'], total_medications: 9, discrepancies_found: 3, discrepancy_types: ['omission', 'omission', 'supplement_interaction'], resolved: true, resolved_by: 'PROV-RAKSHA-001', clinical_significance: ['moderate', 'low', 'moderate'], additions: ['Vitamin D3', 'Fish Oil'], changes: ['Lisinopril 20mg to 40mg'], reconciled_at: datetime('2026-02-22T12:00:00Z') }) ``` --- ## STAGE 43: MEDICATION THERAPY MANAGEMENT (MTM) — NEW **LangGraph Node:** `mtm_node` | **Agent:** MedicationSafetyAgent | **Kafka:** `swarmcare.mtm.review.completed` ```python async def mtm_node(state: SwarmCareState) -> SwarmCareState: """ Comprehensive Medication Review (CMR) per CMS MTM requirements. Mogli qualifies under CMS 2025 expanded criteria: - 5+ chronic medications (he has 6+) - 1+ chronic condition (he has 5) - Total med costs > $4,935/year (estimated $6,240/year) MTM aligns with TEFCA standards for data sharing. Generates Medication Action Plan (MAP) and Personal Medication Record (PMR). """ pass ``` **Mogli's Comprehensive Medication Review (CMR):** ```json { "mtm_id": "MTM-MOGLI-001", "review_type": "comprehensive_medication_review", "pharmacist": "Dr. Raksha (PharmD)", "date": "2026-02-22", "qualifies_because": { "chronic_medications": 6, "chronic_conditions": 5, "estimated_annual_med_cost": 6240, "cms_threshold": 4935 }, "findings": [ { "finding": "Suboptimal glycemic control despite dual therapy", "recommendation": "Consider adding GLP-1 RA if HbA1c remains >7% at 3-month recheck", "priority": "high", "evidence": "ADA 2026 Standards — triple therapy recommended if HbA1c >7% on dual" }, { "finding": "Statin dose may be insufficient for ASCVD risk reduction", "recommendation": "Consider Atorvastatin 40mg (LDL 128, target <100 for diabetic + CKD)", "priority": "medium", "evidence": "ACC/AHA 2024 — moderate-to-high intensity statin for diabetes + CKD" }, { "finding": "Vitamin D supplementation appropriate but level unknown", "recommendation": "Check 25-OH Vitamin D level, adjust dose accordingly", "priority": "medium", "evidence": "KDIGO 2024 — monitor and supplement Vitamin D in CKD" }, { "finding": "Turmeric supplement may potentiate hypoglycemia with Metformin", "recommendation": "Counsel on timing, monitor glucose more closely", "priority": "low", "evidence": "Case reports of enhanced Metformin effect with curcumin" } ], "medication_action_plan": { "actions": [ "Continue current regimen with Lisinopril dose increase", "Recheck HbA1c in 3 months — escalate therapy if >7%", "Discuss Atorvastatin dose increase at next cardiology visit", "Order Vitamin D level", "Counsel on turmeric-Metformin interaction" ], "next_review": "2026-05-22", "shared_with_patient": true } } ``` --- ## STAGE 44: PATIENT-REPORTED OUTCOMES (PROMIS/CAT) — NEW **LangGraph Node:** `prom_node` | **Agent:** DashboardAgent | **Kafka:** `swarmcare.prom.submitted` ```python async def prom_node(state: SwarmCareState) -> SwarmCareState: """ Implements Patient-Reported Outcomes Measurement Information System (PROMIS) with Computer Adaptive Testing (CAT) for efficient measurement. CAT adapts questions in real-time based on patient answers. Typically 4-12 questions yield a highly reliable score. Domains measured: - Physical Function (T-score) - Pain Interference (T-score) - Fatigue (T-score) - Sleep Disturbance (T-score) - Depression (T-score) - Anxiety (T-score) - Social Function (T-score) - Global Health (Physical + Mental composite) Scores integrated into EHR, visible on dashboard, used for SDM. T-score: Mean 50, SD 10. Higher = more of the domain. """ pass ``` **Mogli's PROMIS CAT Scores:** | Domain | T-Score | Interpretation | Trend | Questions Asked | |--------|---------|---------------|-------|----------------| | Physical Function | 45.2 | Slightly below avg | Stable | 6 | | Pain Interference | 48.1 | Average | Improved | 5 | | Fatigue | 55.3 | Slightly above avg (more fatigued) | Worsened | 7 | | Sleep Disturbance | 52.8 | Average | Stable | 4 | | Depression | 50.5 | Average | Stable | 5 | | Anxiety | 49.2 | Average | Improved | 4 | | Social Function | 47.6 | Slightly below avg | Stable | 5 | | Global Physical | 44.8 | Below average | Worsened | — | | Global Mental | 49.3 | Average | Stable | — | **Key Insight:** Mogli's fatigue score (55.3) correlates with suboptimal HbA1c (7.8%). AI flags: "Increased fatigue may be related to hyperglycemia. Consider correlation when reviewing glycemic management plan." **Neo4j:** ```cypher CREATE (prom:PROMScore { prom_id: 'PROM-MOGLI-001', instrument: 'PROMIS-CAT', physical_function: 45.2, pain_interference: 48.1, fatigue: 55.3, sleep_disturbance: 52.8, depression: 50.5, anxiety: 49.2, social_function: 47.6, global_physical: 44.8, global_mental: 49.3, total_questions_asked: 36, completion_time_seconds: 420, administered_at: datetime('2026-02-22T08:30:00Z'), next_due: date('2026-05-22') }) ``` --- ## STAGE 45: SHARED DECISION MAKING (SDM DASHBOARD) — NEW **LangGraph Node:** `sdm_node` | **Agent:** DiagnosisAgent | **Kafka:** `swarmcare.sdm.session.completed` ```python async def sdm_node(state: SwarmCareState) -> SwarmCareState: """ Implements Shared Decision Making (SDM) dashboard integrating: - PRO scores from Stage 44 - Clinical data from patient record - Evidence-based treatment options with outcomes data - Patient preferences and goals Generates treatment option cards with: - Expected outcome (based on similar patients) - Side effect profile - Cost comparison - Patient preference alignment score Used during clinical encounters to co-create treatment decisions. """ pass ``` **Mogli's SDM Session — Glycemic Management Decision:** ``` SHARED DECISION MAKING — Treatment Escalation for T2DM Patient: Mogli Patel | HbA1c: 7.8% | Target: <7% Current: Metformin 1000mg BID + Empagliflozin 10mg Daily OPTION A: Continue Current + Lifestyle Intensification Expected HbA1c: 7.4% in 6 months (based on similar patients) Pros: No new medications, lower cost, no new side effects Cons: May not reach target, relies heavily on diet/exercise compliance Cost: $80/month (current) Patient preference match: 60% OPTION B: Add GLP-1 Receptor Agonist (Semaglutide 0.5mg weekly) Expected HbA1c: 6.8% in 6 months Pros: Strong evidence, weight loss benefit (avg 8-12 lbs), CV protection Cons: Weekly injection, GI side effects (nausea ~20%), higher cost Cost: $850/month (with insurance: $70/month after PA) Patient preference match: 78% OPTION C: Add DPP-4 Inhibitor (Sitagliptin 100mg daily) Expected HbA1c: 7.2% in 6 months Pros: Oral medication, well-tolerated, weight neutral Cons: Modest HbA1c reduction, less CV/renal benefit than GLP-1 RA Cost: $380/month (with insurance: $35/month) Patient preference match: 65% MOGLI'S DECISION: Option B (Semaglutide) — Aligned with goals of: - Achieving HbA1c <7% - Losing weight (BMI 28.5 → target 25) - Maximizing kidney protection Provider Note: Discussed all options with Mogli. He prefers injection over additional pill. Weight loss benefit was primary motivator. GI side effects discussed — start at 0.25mg and titrate. PA submitted. ``` --- ## STAGE 46: AI SYMPTOM TRIAGE & SELF-ASSESSMENT — NEW **LangGraph Node:** `symptom_triage_node` | **Agent:** TriageAgent | **Kafka:** `swarmcare.triage.completed` ```python async def symptom_triage_node(state: SwarmCareState) -> SwarmCareState: """ Ada Health / Buoy Health / Clearstep -style AI symptom assessment. Patient can initiate at any time from app. Features: 1. Conversational symptom intake (NLP-powered) 2. Context-aware: uses patient's existing conditions, medications, allergies 3. Differential diagnosis generation (ranked by probability) 4. Triage level: Self-care / Virtual visit / Urgent care / ER 5. Auto-scheduling if visit recommended 6. Escalation to care team if urgent/emergency 7. Full audit trail of assessment stored in Neo4j """ pass ``` **Mogli's Triage Example:** ``` TRIAGE SESSION — 2026-02-24T21:30:00Z Patient: Mogli Patel | Initiated via: SwarmCare App Mogli: "I'm feeling really dizzy when I stand up and my legs feel weak" AI Assessment (Context-Aware): Known: Lisinopril increased 2 days ago (20mg → 40mg) Known: BP baseline 142/88, now checking for orthostatic hypotension Known: K+ was 4.8, Lisinopril can increase potassium Known: eGFR 72, CKD Stage 2 Follow-up Questions (5 asked): 1. "When did the dizziness start?" → "This morning" 2. "Does it happen when going from sitting to standing?" → "Yes, exactly" 3. "Any chest pain or shortness of breath?" → "No" 4. "Have you been drinking enough water?" → "Maybe not enough" 5. "Have you checked your blood pressure?" → "138/82 sitting, felt dizzy standing" TRIAGE RESULT: Probable Cause: Orthostatic hypotension secondary to Lisinopril dose increase Differential: 1. Drug-induced orthostatic hypotension (85%) 2. Dehydration (10%) 3. Hyperkalemia (5%) Triage Level: URGENT — Virtual visit recommended within 4 hours ACTIONS TAKEN: 1. Alert sent to Dr. Bagheera (LEVEL 2 - URGENT) 2. Virtual visit auto-scheduled for tonight 10 PM 3. Patient instructions: "Sit on edge of bed for 30 seconds before standing. Drink 2 glasses of water now. If you feel faint, sit/lie down immediately. If chest pain or severe headache occurs, call 911." 4. RPM alert threshold temporarily lowered for BP monitoring ``` --- ## STAGE 47: DIGITAL TWIN & PREDICTIVE SIMULATION — NEW **LangGraph Node:** `digital_twin_node` | **Agent:** PredictiveAgent | **Kafka:** `swarmcare.twin.updated` ```python async def digital_twin_node(state: SwarmCareState) -> SwarmCareState: """ Patient-specific digital twin that simulates health trajectories. Uses: longitudinal patient data, population cohort data, clinical guidelines. Capabilities: 1. "What-if" treatment simulations 2. Disease progression modeling (e.g., CKD stage trajectory) 3. Medication response prediction 4. Lifestyle intervention impact modeling 5. Cost projection under different treatment paths """ pass ``` **Mogli's Digital Twin Predictions:** ``` 5-YEAR TRAJECTORY — Mogli Patel Digital Twin ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SCENARIO A: Current Treatment (No Changes) Year 1: HbA1c 7.6%, eGFR 68, BP 135/82, BMI 28.0 Year 3: HbA1c 7.9%, eGFR 58 (CKD Stage 3a), BP 138/85 Year 5: HbA1c 8.2%, eGFR 48 (CKD Stage 3b), insulin likely needed 5-year cost: $47,200 | Hospitalization risk: 23% SCENARIO B: Add Semaglutide + Lifestyle (Recommended) Year 1: HbA1c 6.5%, eGFR 70, BP 128/78, BMI 26.0 (-2.5) Year 3: HbA1c 6.4%, eGFR 67 (CKD Stage 2 preserved), BP 125/76 Year 5: HbA1c 6.5%, eGFR 63 (slow decline), insulin unlikely 5-year cost: $52,800 | Hospitalization risk: 8% NET SAVINGS vs Scenario A: $14,400 (avoided hospitalizations) SCENARIO C: Aggressive Intervention (All Optimized) Year 1: HbA1c 6.2%, eGFR 71, BP 122/74, BMI 25.0 (-3.5) Year 3: HbA1c 6.0%, eGFR 68, BP 120/72 Year 5: HbA1c 6.1%, eGFR 65, minimal progression 5-year cost: $58,200 | Hospitalization risk: 4% ``` --- ## STAGE 48: CYBERSECURITY & ZERO-TRUST ACCESS — NEW **LangGraph Node:** `cybersecurity_node` | **Agent:** ComplianceAgent | **Kafka:** `swarmcare.security.audit` Features: Zero-trust architecture, mTLS for all internal traffic, AES-256 encryption at rest, field-level encryption for PHI, role-based access control (RBAC), biometric authentication, session management, anomaly detection (unusual access patterns), break-the-glass emergency access with audit, HITRUST CSF compliance, SOC 2 Type II certification, automated penetration testing. --- ## STAGE 49: POST-DISCHARGE SURVEILLANCE (30-Day) — NEW **LangGraph Node:** `post_discharge_surveillance_node` | **Agent:** CareCoordinationAgent | **Kafka:** `swarmcare.discharge.followup` ```python async def post_discharge_surveillance_node(state: SwarmCareState) -> SwarmCareState: """ 30-day post-discharge monitoring to prevent readmissions. Implements AHRQ MATCH Toolkit for care transitions. Timeline: - Day 0-1: Medication reconciliation (Stage 42) - Day 1-3: Transition pharmacist CMR call - Day 3-7: First follow-up visit (virtual or in-person) - Day 7-14: RPM monitoring intensified - Day 14-21: Second follow-up, lab rechecks - Day 21-30: Assessment of stability, care plan adjustment AI monitors: symptom reports, RPM vitals, medication adherence, missed appointments, social determinant changes. """ pass ``` --- ## STAGE 50: SOCIAL PRESCRIBING & NON-MEDICAL RX — NEW **LangGraph Node:** `social_prescribing_node` | **Agent:** CareCoordinationAgent | **Kafka:** `swarmcare.social.prescription` ```python async def social_prescribing_node(state: SwarmCareState) -> SwarmCareState: """ Non-medical prescriptions based on NHS UK social prescribing model. Addresses factors that medications cannot: loneliness, inactivity, food insecurity, financial stress, social isolation. Link workers connect patients to community resources. Prescriptions tracked and outcomes measured like medical interventions. """ pass ``` **Mogli's Social Prescriptions:** | Rx # | Prescription | Provider | Reason | Duration | Outcome Measure | |------|-------------|----------|--------|----------|----------------| | SP-001 | YMCA Diabetes Prevention Program | Dr. Bagheera | Weight loss, activity | 16 weeks | BMI, HbA1c, steps/day | | SP-002 | Austin Diabetes Support Group | Dr. Rama | Peer support, diabetes distress | Ongoing | DDS score, PHQ-9 | | SP-003 | Cooking for Health classes | Shanti RD | Nutrition education | 8 weeks | Diet quality score | | SP-004 | Walk with a Doc Austin | Nurse Baloo | Physical activity | Ongoing | Steps/day, BP trend | --- ## STAGES 51-60: INFRASTRUCTURE & DISCHARGE | Stage | Module | Key Features | |-------|--------|-------------| | 51 | Revenue Cycle Management | Charge capture, claim generation (837P/837I), denial prediction, payment posting | | 52 | Claims Denial & Appeals | AI denial prediction (89% accuracy), auto-appeal generation, root cause analysis | | 53 | Provider Credentialing | Automated verification, NPPES lookup, license expiry alerts, privileging | | 54 | Quality Measures (MIPS/HEDIS) | Automated measure calculation, gap identification, attestation support | | 55 | Interoperability Hub (TEFCA) | TEFCA-compliant exchange, QHIN connectivity, CareQuality, CommonWell, eHealth Exchange | | 56 | Patient Data Export (Blue Button) | FHIR Bulk Data Export, Blue Button 2.0 API, patient-initiated data portability | | 57 | Clinical Registry Reporting | Auto-report to CMS, state registries, cancer registry, immunization registry | | 58 | Care Continuum Analytics | End-to-end journey analytics, bottleneck identification, process mining | | 59 | Neo4j Final Sync + Validation | Full graph validation, orphan node detection, edge integrity check, statistics | | 60 | Discharge Planning & Transition | Comprehensive discharge, transition of care, 30-day plan, patient education packet | ### Stage 59: Neo4j Final Sync — Mogli's Complete Graph Statistics ``` PATIENT GRAPH STATISTICS — Mogli Patel (PAT-MOGLI-001) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Total Nodes: ~320 (expanded from ~180 in v2) Total Edges: ~500 (all with Graphiti temporal validity) NODE BREAKDOWN: Patient: 1 Insurance: 1 Consent: 10 Provider: 9 Condition: 5 Medication: 9 (6 Rx + 3 supplements) Allergy: 2 LabResult: 11 VitalSign: 10 Encounter: 3+ Procedure: 2+ CarePlan: 1 CareGap: 3 Alert: 3+ OntologyTerm: 74 JourneyStage: 60 WearableDevice: 4 RPMReading: 50+ (time-series) CommunicationLog: 4+ (D2D messages) DoctorDialogue: 1+ (AI summaries) AudioRecording: 3 (encounter, education, podcast) PatientInstruction: 3+ (AVS, pre-visit, general) HandoffRecord: 1+ FamilyMember: 2 (Akela, Sita) Appointment: 2+ PriorAuth: 1 (Empagliflozin) GenomicProfile: 1 MentalHealthScreen: 3 (PHQ-9, GAD-7, DDS) PatientFeedback: 1 EducationContent: 5 AuditTrail: 847+ SDoHAssessment: 1 DigitalTherapeutic: 1 TransportRequest: 1 NutritionPlan: 1 AdvanceDirective: 1 WellnessGoal: 3 MedicationReconciliation: 1 MTMReview: 1 PROMScore: 1 SDMSession: 1 TriageAssessment: 1 DigitalTwin: 1 PostDischargeCheck: 0 (not yet discharged) SocialPrescription: 4 DashboardSession: 1 Prediction: 3+ EDGE TYPES (65+, all with Graphiti temporal validity): Every edge has: validity, created_at, valid_from, valid_to, version ``` ### Stage 60: Discharge Planning ```python async def discharge_node(state: SwarmCareState) -> SwarmCareState: """ Final stage. Generates comprehensive discharge package: 1. Final medication reconciliation (complete list with patient education) 2. Follow-up appointment schedule (auto-scheduled) 3. After-Visit Summary in patient's language 4. I-PASS handoff to outpatient providers 5. RPM monitoring plan continuation 6. 30-day post-discharge surveillance activation 7. Community resource connections 8. Patient satisfaction survey trigger 9. Care plan handoff documentation 10. Quality measure assessment (HEDIS/MIPS impact) """ pass ``` --- ## COMPLETE NEO4J SCHEMA ### All Node Types (50+) ``` Patient, Insurance, Consent (x10 types), Provider (x9 roles), Condition, Medication, Allergy, LabResult, VitalSign, Encounter, Procedure, CarePlan, CareGap, Alert, OntologyTerm, JourneyStage, WearableDevice, RPMReading, CommunicationLog, DoctorDialogue, AudioRecording, PatientInstruction, HandoffRecord, FamilyMember, Appointment, PriorAuth, GenomicProfile, MentalHealthScreen, PatientFeedback, EducationContent, AuditTrail, SDoHAssessment, DigitalTherapeutic, TransportRequest, NutritionPlan, AdvanceDirective, WellnessGoal, MedicationReconciliation, MTMReview, PROMScore, SDMSession, TriageAssessment, DigitalTwin, PostDischargeCheck, SocialPrescription, DashboardSession, Prediction, PharmacyOrder, Claim, DenialAppeal, QualityMeasure, RegistryReport, ContinuumAnalytic ``` ### All Edge Types (65+) — Graphiti Temporal Validity ``` EVERY edge includes these Graphiti temporal properties: validity: 'current' | 'historical' | 'pending' | 'invalidated' created_at: datetime valid_from: datetime valid_to: datetime (null = still active) version: integer EDGE LIST: HAS_INSURANCE, HAS_CONSENT, HAS_CARE_TEAM_MEMBER, HAS_CONDITION, TAKES_MEDICATION, HAS_ALLERGY, HAS_LAB_RESULT, HAS_VITAL_SIGN, HAS_ENCOUNTER, HAS_PROCEDURE, HAS_CARE_PLAN, HAS_CARE_GAP, HAS_ALERT, MAPPED_TO_ONTOLOGY, AT_JOURNEY_STAGE, HAS_WEARABLE_DEVICE, HAS_RPM_READING, HAS_RPM_ALERT, HAS_D2D_MESSAGE, HAS_D2D_DIALOGUE, HAS_AUDIO_RECORDING, HAS_INSTRUCTION, HAS_HANDOFF, HAS_FAMILY_MEMBER, HAS_APPOINTMENT, HAS_PRIOR_AUTH, HAS_GENOMIC_PROFILE, HAS_MENTAL_HEALTH_SCREEN, HAS_FEEDBACK, HAS_EDUCATION, HAS_AUDIT_EVENT, HAS_SDOH, HAS_DTX, HAS_TRANSPORT, HAS_NUTRITION_PLAN, HAS_ADVANCE_DIRECTIVE, HAS_WELLNESS_GOAL, HAS_MED_RECONCILIATION, HAS_MTM_REVIEW, HAS_PROM_SCORE, HAS_SDM_SESSION, HAS_TRIAGE, HAS_DIGITAL_TWIN, HAS_POST_DISCHARGE, HAS_SOCIAL_PRESCRIPTION, HAS_DASHBOARD_SESSION, HAS_PREDICTION, HAS_PHARMACY_ORDER, HAS_CLAIM, TREATS (Medication → Condition), INTERACTS_WITH (Medication → Medication), CROSS_REACTS (Allergy → Medication class), PRESCRIBED_BY (Medication → Provider), REFERS_TO (Provider → Provider), COMMUNICATED_WITH (Provider → Provider), MONITORS (WearableDevice → VitalSign type), TRIGGERS (RPMReading → Alert), PART_OF_THREAD (CommunicationLog → DoctorDialogue), GENERATED_FROM (AudioRecording → PatientInstruction), RECONCILED_IN (Medication → MedicationReconciliation), REVIEWED_IN (Medication → MTMReview), INFORMED_BY (SDMSession → PROMScore), SIMULATED_BY (DigitalTwin → Prediction), FULFILLS (Appointment → CareGap) ``` --- ## 13 ONTOLOGY INTEGRATION — MOGLI'S 74 TERMS | # | Ontology | Count | Example Terms | |---|----------|-------|---------------| | 1 | SNOMED-CT | 7 | 44054006 (T2DM), 59621000 (HTN), 195967001 (Asthma), 55822004 (HLD), 431856006 (CKD2) | | 2 | ICD-11 | 5 | 5A11, BA00, CA23.0, 5C80, GB61.1 | | 3 | ICD-10-CM | 5 | E11.65, I10, J45.30, E78.5, N18.2 | | 4 | RxNorm | 6 | 861004 (Metformin), 1545653 (Empagliflozin), 314076 (Lisinopril) | | 5 | LOINC | 8 | 4548-4 (HbA1c), 48642-3 (eGFR), 85354-9 (BP) | | 6 | CPT | 5 | 99214, 99457, 99490, 90686, 93784 | | 7 | HL7 FHIR R4 | 8 | Patient, Condition, MedicationRequest, Observation, Encounter, Procedure, CarePlan, AllergyIntolerance | | 8 | UMLS | 5 | C0011860, C0020538, C0004096, C0020473, C0271650 | | 9 | HPO | 5 | HP:0003074, HP:0000822, HP:0002099, HP:0003077, HP:0012622 | | 10 | Gene Ontology | 3 | GO:0006006, GO:0001822, GO:0006811 | | 11 | DrugBank | 6 | DB00331, DB09038, DB00722, DB00381, DB01076, DB01001 | | 12 | OMOP CDM | 5 | Standard concept mappings for all conditions | | 13 | ChEBI | 6 | CHEBI:6801, CHEBI:4031, CHEBI:43568, CHEBI:2668, CHEBI:39548, CHEBI:2549 | --- ## LANGGRAPH ARCHITECTURE ``` Total LangGraph Nodes: 67 Gate Nodes: 4 (registration, consent, care_team, treatment) Module Nodes: 60 (Stages 5-60 + additional modules) Terminal Nodes: 3 (registration_failed, consent_failed, care_team_failed) Infrastructure: 1 (neo4j_sync) Routing: Gates: conditional_edge (PASS → next stage, FAIL → terminal) Modules: linear chain (each stage → next stage) Parallel: Some stages can run concurrently (e.g., education + wellness goals) ``` --- ## KAFKA EVENT SYSTEM (35+ Topics) | Topic | Trigger | Consumers | |-------|---------|-----------| | swarmcare.patient.registered | Stage 1 complete | Neo4j, FHIR server, Analytics | | swarmcare.consent.signed | Each consent | Audit, Compliance, Neo4j | | swarmcare.care_team.assembled | Stage 3 complete | Scheduling, Notifications | | swarmcare.treatment.initiated | Stage 4 complete | CDS, Pharmacy, Insurance | | swarmcare.dashboard.loaded | Stage 5 | Analytics, Personalization | | swarmcare.rpm.reading | Each device reading | AlertEngine, TimescaleDB, Neo4j | | swarmcare.rpm.alert | Threshold breach | Provider inbox, Escalation engine | | swarmcare.encounter.documented | SOAP generated | Coding, Billing, Neo4j | | swarmcare.d2d.message | Each D2D message | Audit, Neo4j, Notification | | swarmcare.d2d.summary.generated | AI summary ready | Patient portal, Provider inbox | | swarmcare.audio.recorded | Audio captured | Transcription pipeline | | swarmcare.audio.transcribed | Transcription done | NLP, SOAP generator | | swarmcare.soap.generated | SOAP note ready | Provider review queue | | swarmcare.announcement.sent | AI announcement | Push, SMS, Email services | | swarmcare.instruction.delivered | Instruction sent | Patient portal, Audit | | swarmcare.alert.escalated | Alert level change | Escalation engine | | swarmcare.handoff.initiated | Handoff started | Receiving provider | | swarmcare.handoff.confirmed | Handoff accepted | Audit, Care coordination | | swarmcare.prior_auth.submitted | PA sent | Insurance payer, Tracking | | swarmcare.prior_auth.resolved | PA decision | Pharmacy, Provider, Patient | | swarmcare.medrec.completed | Med reconciliation | All providers, Pharmacy | | swarmcare.mtm.review.completed | MTM done | Provider, Patient, Billing | | swarmcare.prom.submitted | PROM scores | Dashboard, SDM, Provider | | swarmcare.sdm.session.completed | SDM decision | CarePlan, Orders, Neo4j | | swarmcare.triage.completed | Triage result | Scheduling, Alerts, Provider | | swarmcare.twin.updated | Digital twin refresh | Dashboard, Predictions | | swarmcare.security.audit | Security event | SOC, Compliance, SIEM | | swarmcare.discharge.followup | Post-discharge check | Care coordination | | swarmcare.social.prescription | Social Rx issued | Community resources | | swarmcare.appointment.scheduled | Appointment made | Calendar, Reminders | | swarmcare.claim.submitted | Claim sent | RCM, Payer | | swarmcare.quality.measured | Quality score | Reporting, Dashboard | | swarmcare.graph.updated | Neo4j changed | Analytics, Audit | --- ## API SPECIFICATION (75+ Endpoints) **Patient & Registration:** ``` POST /api/v1/patients/register GET /api/v1/patients/{id} PUT /api/v1/patients/{id} GET /api/v1/patients/{id}/journey GET /api/v1/patients/{id}/health-score GET /api/v1/patients/{id}/timeline ``` **Clinical:** ``` GET /api/v1/patients/{id}/conditions GET /api/v1/patients/{id}/medications POST /api/v1/patients/{id}/medications/reconcile GET /api/v1/patients/{id}/allergies GET /api/v1/patients/{id}/labs GET /api/v1/patients/{id}/vitals GET /api/v1/patients/{id}/encounters POST /api/v1/encounters/{id}/soap ``` **D2D Communication:** ``` POST /api/v1/d2d/messages GET /api/v1/d2d/threads/{patient_id} GET /api/v1/d2d/threads/{thread_id}/messages POST /api/v1/d2d/threads/{thread_id}/summarize GET /api/v1/d2d/dialogues/{patient_id} GET /api/v1/d2d/action-items/{patient_id} ``` **Audio & Documentation:** ``` POST /api/v1/audio/upload GET /api/v1/audio/{id}/transcription POST /api/v1/audio/{id}/generate-soap POST /api/v1/audio/education/generate GET /api/v1/audio/podcast/{provider_id}/latest ``` **Instructions & Alerts:** ``` POST /api/v1/instructions/create GET /api/v1/instructions/{patient_id} GET /api/v1/announcements/{patient_id} GET /api/v1/alerts/{patient_id} PUT /api/v1/alerts/{id}/acknowledge POST /api/v1/alerts/{id}/escalate ``` **Handoff:** ``` POST /api/v1/handoffs/create POST /api/v1/handoffs/{id}/generate-ipass POST /api/v1/handoffs/{id}/generate-sbar PUT /api/v1/handoffs/{id}/confirm GET /api/v1/handoffs/{patient_id} GET /api/v1/handoffs/{id}/quality-score ``` **RPM & Wearables:** ``` POST /api/v1/rpm/readings GET /api/v1/rpm/{patient_id}/readings GET /api/v1/rpm/{patient_id}/trends GET /api/v1/rpm/{patient_id}/alerts POST /api/v1/rpm/devices/enroll ``` **New v5 Endpoints:** ``` POST /api/v1/medrec/reconcile GET /api/v1/medrec/{patient_id}/history POST /api/v1/mtm/review GET /api/v1/mtm/{patient_id}/reviews POST /api/v1/prom/submit GET /api/v1/prom/{patient_id}/scores POST /api/v1/sdm/session GET /api/v1/sdm/{patient_id}/sessions POST /api/v1/triage/assess GET /api/v1/triage/{patient_id}/history GET /api/v1/twin/{patient_id}/predictions POST /api/v1/twin/{patient_id}/simulate POST /api/v1/social-rx/prescribe GET /api/v1/social-rx/{patient_id} ``` **Knowledge Graph:** ``` POST /api/v1/graph/query (natural language → Cypher) GET /api/v1/graph/{patient_id}/subgraph GET /api/v1/graph/{patient_id}/pathrag GET /api/v1/graph/ontology/{system}/{code} ``` **FHIR R4:** ``` GET /fhir/r4/Patient/{id} GET /fhir/r4/Condition?patient={id} GET /fhir/r4/MedicationRequest?patient={id} GET /fhir/r4/Observation?patient={id} POST /fhir/r4/Claim POST /fhir/r4/ClaimResponse ``` --- ## 20 AI AGENT DEFINITIONS | # | Agent | Stages | Capabilities | |---|-------|--------|-------------| | 1 | RegistrationAgent | 1 | Demographics validation, MRN generation, insurance verification | | 2 | ComplianceAgent | 2, 31, 48 | Consent management, HIPAA audit, security | | 3 | CareCoordinationAgent | 3, 20, 34, 49, 50 | Team assembly, scheduling, transport, post-discharge, social Rx | | 4 | MedicationSafetyAgent | 4, 24, 42, 43 | DDI check, renal dosing, reconciliation, MTM | | 5 | DiagnosisAgent | 4, 21, 45 | Condition assessment, CDS, shared decision making | | 6 | DashboardAgent | 5, 13, 44 | Health score, dashboard rendering, PROMs | | 7 | ChronicCareAgent | 6, 33 | RPM management, DTx, chronic care protocols | | 8 | ClinicalDocAgent | 7, 14 | SOAP notes, ambient documentation, coding | | 9 | KnowledgeGraphAgent | 8 | Ontology mapping, PathRAG, GraphRAG | | 10 | CommunicationAgent | 9 | D2D messaging, summarization, action items | | 11 | AudioAgent | 10 | Transcription, education audio, podcast generation | | 12 | InstructionAgent | 11 | Announcements, AVS, patient instructions, alerts | | 13 | HandoffAgent | 12 | I-PASS/SBAR generation, quality scoring, confirmation | | 14 | InsuranceAgent | 25, 51, 52 | Prior auth, claims, denial management | | 15 | PredictiveAgent | 22, 47 | Risk prediction, digital twin, simulation | | 16 | TriageAgent | 16, 46 | Symptom assessment, triage level, auto-scheduling | | 17 | TelehealthAgent | 17 | Video visits, remote exam, e-prescribe | | 18 | PopHealthAgent | 18, 19, 54 | Population analytics, care gaps, quality measures | | 19 | VoiceAgent | Stage 20 (Voice AI) | Voice commands, voice-to-text, voice navigation | | 20 | XAIAgent | Stage 21 (XAI) | Explainability, reasoning transparency, PathRAG traces | --- ## COMPETITIVE ADVANTAGE MATRIX **SwarmCare v5.0 vs Top 15 Global Competitors:** | Feature | SwarmCare | Epic | Cerner | Innovaccer | Athena | Sully.ai | Abridge | Navina | Viz.ai | |---------|-----------|------|--------|------------|--------|----------|---------|--------|--------| | Patient-Selected Care Team | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | 13 Ontology Integration | ✅ | 3 | 2 | 2 | 1 | 0 | 0 | 1 | 1 | | Patient-Centric Neo4j KG | ✅ | ❌ | ❌ | Partial | ❌ | ❌ | ❌ | ❌ | ❌ | | PathRAG + GraphRAG | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Graphiti Temporal Edges | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | D2D AI Summarization | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Care Audio (3 Pillars) | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | Partial | ❌ | ❌ | | Auto I-PASS Generation | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | AI Medication Reconciliation | ✅ | Partial | Partial | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | MTM with CMR | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | PROMIS CAT Integration | ✅ | Partial | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | SDM Dashboard (PRO-based) | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | AI Symptom Triage | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Patient Digital Twin | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Social Prescribing | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | 20 AI Agents (LangGraph) | ✅ | ❌ | ❌ | ❌ | ❌ | Partial | ❌ | ❌ | ❌ | | 60-Stage Patient Journey | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Care Team Podcast | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Post-Discharge 30-Day AI | ✅ | Partial | Partial | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | Multi-Protocol Handoff | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | **SwarmCare Unique Features: 20/20 | Best Competitor (Epic): 3/20** --- ## SwarmCare v5.0 — BY THE NUMBERS ``` Journey Stages: 60 (vs 22 in v2, 50 in v4) Total Features: 500+ LangGraph Nodes: 67 (60 modules + 4 gates + 3 terminal) Neo4j Node Types: 50+ Neo4j Edge Types: 65+ (all Graphiti temporal) Ontology Systems: 13 (74+ terms for Mogli) AI Agents: 20 API Endpoints: 75+ Kafka Event Topics: 35+ Handoff Protocols: I-PASS, SBAR, ISBAR3 (all auto-generated) RPM Device Types: 4 (CGM, BP, Scale, Peak Flow) Consent Types: 10 (5 required, 5 optional) Languages Supported: 3+ (English, Hindi, Spanish) Audio Types: 3 (Encounter, Education, Podcast) Care Team Size: 9 (patient-selected) Safety Checks: 5 (DDI, Allergy, Renal, Duplicate, Formulary) PROM Domains: 9 (PROMIS CAT) SDM Treatment Options: 3+ per decision point Triage Levels: 4 (Self-care, Virtual, Urgent, ER) Alert Levels: 4 (Routine, Urgent, Critical, Emergency) Digital Twin Scenarios: 3+ per patient Social Prescriptions: 4+ per patient Medication Reconciliation: At every transition of care MTM Reviews: Quarterly (CMS-compliant) Post-Discharge Checks: 30-day protocol (6 touchpoints) Competitors Benchmarked: 100+ platforms worldwide ``` --- ## PATIENT MOGLI PATEL — FINAL GRAPH ``` ┌─ Insurance (BCBS TX) ├─ Consent ×10 ├─ Provider ×9 (Care Team) ├─ Condition ×5 ├─ Medication ×9 (6 Rx + 3 supplements) ├─ Allergy ×2 ├─ LabResult ×11 ├─ VitalSign ×10 ┌──────────────┐ ├─ Encounter ×3+ │ │ ├─ WearableDevice ×4 │ MOGLI │─────├─ RPMReading ×50+ │ PATEL │ ├─ CommunicationLog ×4+ │ (Hub Node) │ ├─ DoctorDialogue ×1+ │ │ ├─ AudioRecording ×3 └──────────────┘ ├─ PatientInstruction ×3+ ├─ HandoffRecord ×1+ ├─ FamilyMember ×2 ├─ Appointment ×2+ ├─ PriorAuth ×1 ├─ GenomicProfile ×1 ├─ MentalHealthScreen ×3 ├─ MedReconciliation ×1 ├─ MTMReview ×1 ├─ PROMScore ×1 ├─ SDMSession ×1 ├─ TriageAssessment ×1 ├─ DigitalTwin ×1 ├─ SocialPrescription ×4 ├─ WellnessGoal ×3 ├─ OntologyTerm ×74 ├─ JourneyStage ×60 ├─ AuditTrail ×847+ └─ ~320 total nodes, ~500 edges Every edge has Graphiti temporal validity: validity | created_at | valid_from | valid_to | version ``` --- **END OF DOCUMENT** **SwarmCare v5.0 — "Of the Patient, To the Patient, By the Patient"** **© 2026 Semantic Data Services. All Rights Reserved.**