AI Clinical Reasoning for Chronic Care

Beyond Alerts. Beyond Documentation.

Ardia Health uses Google Cloud's Healthcare API, Vertex AI, and BigQuery to deliver longitudinal clinical reasoning that predicts asthma/COPD exacerbations 7 days in advance — reducing ER visits by 40% while generating $180/patient/month in RPM revenue.

Built on Google Cloud Healthcare API Vertex AI BigQuery HIPAA Compliant

A. How It Works — Clinical Reasoning Engine

End-to-End Flow: From Patient Data to Clinical Action

❌ Why Existing AI Fails

Transcription ≠ Intelligence: Ambient scribes only document — they don't reason.

Alerts ≠ Decisions: Rule-based alerts create noise, not insight.

Burnout ≠ Solved: More tools = more clicks = more frustration.

✓ Ardia's Approach: Longitudinal Clinical Reasoning

We don't just alert providers — we reason across time, predict deterioration, and recommend the next-best-action based on the full patient context.

Clinical Reasoning Engine — 5-Step Flow

1

Data Ingestion

Sources: FHIR (via Google Healthcare API), EHR integrations (Epic, Cerner), wearables (Apple Health, Fitbit), patient-reported symptoms (mobile app)

Google Cloud: Cloud Healthcare API FHIR store, Pub/Sub for real-time streaming

2

Symptom + History Normalization

Process: Structured + unstructured data cleaned, mapped to clinical ontologies (SNOMED CT, LOINC)

Google Cloud: Dataflow for ETL, BigQuery for longitudinal patient timelines

3

Clinical Reasoning Layer (Not Alert-Based)

AI Engine: Temporal models analyze trends, patterns, deviations. No static thresholds — context-aware reasoning.

Example: "Patient's FEV1 declining 3% weekly + rescue inhaler use up 40% + nighttime symptoms increasing → 7-day exacerbation risk = 78%"

Google Cloud: Vertex AI custom-trained models, AutoML for feature engineering

4

Risk Stratification & Next-Best-Action

Output: Risk scores (0-100), recommended interventions ranked by clinical impact

Example Actions: "Schedule urgent pulmonology visit," "Increase controller dose," "Patient education: inhaler technique"

Google Cloud: Cloud Functions for real-time decisioning, Firestore for action tracking

5

Provider + Patient Outputs

Provider Dashboard: Prioritized patient list, clinical reasoning explained, one-click interventions

Patient App: Simple, actionable guidance ("Your asthma risk is elevated — use your controller inhaler twice daily")

Google Cloud: Cloud Run for web dashboard, Firebase for mobile app backend

🔒 HIPAA Compliance Built-In

All PHI encrypted at rest (Cloud KMS) and in transit (TLS 1.3). BAA signed with Google Cloud. Role-based access (Cloud IAM). Audit logs (Cloud Logging) for every data access.

B. Google Cloud Architecture

Our Infrastructure Stack (Current + Planned)

Ardia Health on Google Cloud

📊 Data Layer

Cloud Healthcare API (FHIR R4) BigQuery (Longitudinal Patient Data) Cloud Storage (Medical Imaging) Pub/Sub (Real-Time Events)

🤖 AI/ML Layer

Vertex AI (Clinical Reasoning Models) AutoML Tables (Feature Engineering) Vertex AI Pipelines (MLOps) Vertex AI Endpoints (Inference)

⚙️ Application Layer

Cloud Run (Provider Dashboard API) Cloud Functions (Event Processing) Firebase (Patient Mobile App) Dataflow (ETL Pipelines)

🔐 Security & Compliance

Cloud IAM (Role-Based Access) Cloud KMS (Encryption Keys) VPC Service Controls (Network Isolation) Cloud Logging (Audit Trails) Cloud Armor (DDoS Protection)

📈 Monitoring & Observability

Cloud Monitoring (Metrics) Cloud Trace (Latency Analysis) Error Reporting (Incident Management)

Why This Needs Cloud Scale

Longitudinal Data: Each patient generates 10,000+ data points over 12 months (vitals, medications, lab results, symptoms). BigQuery handles petabyte-scale analytics.

Real-Time Inference: When a patient reports worsening symptoms, our Vertex AI models must predict exacerbation risk in <200ms.

HIPAA at Scale: Google Cloud's Healthcare API is the only FHIR-native solution with built-in BAA, de-identification, and consent management.

C. Real Use Case — Asthma/COPD Care (Phase 1)

How Ardia Transforms Respiratory Care

The Problem

22 million Americans have asthma. 16 million have COPD.

❌ 2 million ER visits/year ($3,000-$15,000 per visit)

❌ 60% of patients misuse inhalers → poor control

❌ Clinicians see 300+ patients → can't monitor all proactively

❌ Care is reactive: patients deteriorate silently until crisis

Ardia's AI Reasoning in Action

📱

Day 1

Patient reports increased breathlessness in mobile app. Rescue inhaler use: 3x/day (normal: 1x/week).

🧠

Day 2

Ardia AI analyzes: FEV1 trend ↓ 5%, nighttime symptoms ↑, pollen levels elevated. Exacerbation risk: 68%

🩺

Day 3

Provider dashboard flags patient as High Priority. Recommends: increase controller dose, schedule telehealth visit.

Day 7

Patient stabilizes. ER visit avoided ($8,000 saved). Clinic earns $60 RPM reimbursement for remote monitoring.

Sample Provider Dashboard — Detailed Clinical Insights

12
Total Patients
3
High Risk
5
Medium Risk
4
Stable

🔴 HIGH PRIORITY PATIENTS (3)

Sarah M., 34 — Asthma (ICD-10: J45.901)
⚠️ Risk Score: 78% (7-day exacerbation risk)
Last visit: 3 days ago | Next scheduled: 12/24/2026
FEV1 Trend
↓ 5%
Weekly decline
Rescue Inhaler
↑ 40%
vs. baseline
Night Symptoms
3x/week
↑ from 1x/week
Controller
62%
adherence
Michael K., 58 — COPD GOLD Stage 2 (ICD-10: J44.1)
⚠️ Risk Score: 65% (7-day exacerbation risk)
Last visit: 5 days ago | Next scheduled: 12/26/2026
FEV1 Ratio
45%
predicted
Exacerbations/Yr
2
in past year
SpO2 Trend
↓ 2%
trending down
Smoking Status
Former
quit 3 years ago
Lisa R., 45 — Asthma (ICD-10: J45.902)
⚠️ Risk Score: 58% (7-day exacerbation risk)
Last visit: 1 day ago | Next scheduled: 12/28/2026
Work Absences
↑ 2 days
this month
Comorbidity
GERD
asthma trigger
Allergens
Pollen
seasonal
Adherence
78%
moderate

✅ STABLE PATIENTS (4)

All metrics normal. Medication adherence >90%. No alerts. Next routine follow-up in 2-4 weeks. Recommend: Continue current therapy, quarterly spirometry.

✓ Interactive dashboard — Click buttons to see real-time modals for scheduling, messaging, prescriptions

📊 Phase 1 Deployment (Q1 2026)

Target: 3 primary care clinics, 500 asthma/COPD patients

Goal: Reduce ER visits 40%, increase RPM revenue $180/patient/month

Google Cloud Role: Healthcare API for FHIR data, Vertex AI for risk models, BigQuery for population analytics

D. Product Demo (Early Access)

Interactive Walkthrough of Ardia's Clinical Reasoning

Live Demo Features

Clinical Intelligence Engine: See how AI reasons across patient timelines

Provider Dashboard: Priority patient lists, risk scores, recommended actions

Patient Intelligence: Mobile app UI showing personalized guidance

Real Case Studies: Asthma exacerbation prevention, COPD deterioration detection

Emergency Response: After-hours escalation protocols

Revenue Generation: RPM billing automation, quality metrics

Launch Interactive Demo →

Why Ardia Is Different

Competitive Differentiation

🎯 Our Unique Approach

Reasoning > Alerts: We don't just flag problems — we explain clinical logic and recommend actions.

Clinical Intelligence > Transcription: We solve care gaps, not documentation gaps.

Proactive > Reactive: We predict deterioration before crisis, not after.

Built for Scale: Google Cloud enables us to serve 10,000+ patients per clinic with <200ms inference latency.

🚀 Current Stage: Early-Stage, Actively Building

Status: Pre-seed / Prototype phase

Progress: Core AI models trained, provider dashboard in development, Phase 1 pilot clinics identified

Commitment: 100% Google Cloud infrastructure (no AWS/Azure dependencies)

Ask: $100,000 Google Cloud credits + technical partnership to accelerate development & pilot deployment

Ready to Transform Chronic Care with Google Cloud

Ardia Health is building the future of clinical intelligence — and Google Cloud is essential to our mission.

Contact Us: founders@ardiahealthlabs.com

🌐 Website: ardiahealthlabs.com
📧 Email: founders@ardiahealthlabs.com
📍 Based in: Dallas-Fort Worth, TX