Practical, code-first tutorials for building healthcare AI applications on HealthCloud. Each guide takes you from zero to a working production system.
Get the HealthCloud platform running with your first workflow execution in under 10 minutes.
Generate an API key from your HealthCloud developer account.
export HC_API_KEY=hc_test_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Create a project to house your assets and deployments.
POST /v1/projects
{
"name": "My First Project",
"organization_id": "org_123",
"environment": "sandbox"
}Install a pre-built agent from the HealthCloud Marketplace.
POST /v1/assets/install
{
"asset_id": "agent_diagnostic_v1",
"project_id": "proj_abc"
}Deploy the installed agent to your sandbox environment.
POST /v1/deployments
{
"asset_id": "agent_diagnostic_v1",
"project_id": "proj_abc",
"environment": "sandbox",
"config": {}
}Execute a diagnostic workflow and receive a result.
POST /v1/workflows/run
{
"workflow_id": "uti_screening",
"input": {
"patient_id": "pat_demo_001"
}
}
// Response
{
"status": "completed",
"result": {
"diagnosis": "UTI Likely",
"confidence": 0.91,
"recommended_action": "antibiotic_treatment"
}
}Complete tutorials for the most common healthcare AI use cases on HealthCloud.
Create an AI-powered screening application for UTI detection using HealthCloud diagnostic models, FHIR-native data storage, and automated provider notification.
Install the UTI Diagnostic Model from the marketplace into your project.
POST /v1/assets/install
{
"asset_id": "model_uti_diagnostic_v2",
"project_id": "proj_abc"
}Link a synthetic patient dataset to use for model validation.
POST /v1/integrations/configure
{
"type": "dataset",
"dataset_id": "ds_synthetic_uti_1k",
"project_id": "proj_abc"
}Define the end-to-end workflow from symptom intake to result delivery.
POST /v1/workflows
{
"name": "UTI Screening",
"steps": [
"collect_intake_form",
"run_uti_diagnostic_model",
"generate_lab_order",
"notify_provider"
]
}Deploy the workflow as an accessible API endpoint.
POST /v1/deployments
{
"workflow_id": "wf_uti_screening",
"environment": "production",
"expose_endpoint": true
}Sample Output
{
"diagnosis": "Likely UTI",
"confidence": 0.92,
"evidence": ["dysuria", "frequency", "elevated_wbc"],
"recommended_action": "antibiotic_treatment",
"suggested_order": "urine_culture"
}Build a continuous vital-sign monitoring system that ingests device data, normalizes to FHIR, triggers anomaly detection, and alerts care teams.
Configure a device connector for Dexcom continuous glucose monitoring.
POST /v1/integrations/configure
{
"type": "device",
"provider": "dexcom",
"credentials": {
"client_id": "dc_client_xxx",
"client_secret": "dc_secret_xxx"
}
}Configure the FHIR normalization pipeline for glucose readings.
POST /v1/pipelines/fhir-mapping
{
"source": "dexcom_glucose",
"target_resource": "Observation",
"loinc_code": "2339-0",
"unit": "mg/dL"
}Define threshold-based alert logic and care team notification.
POST /v1/workflows
{
"name": "Glucose Alert Workflow",
"trigger": {
"event": "observation.created",
"condition": "value > 180 OR value < 70"
},
"steps": ["anomaly_detection", "risk_score", "alert_provider"]
}Deploy the RPM monitoring agent to run continuously.
POST /v1/deployments
{
"asset_id": "agent_rpm_monitor_v1",
"config": {
"check_interval_minutes": 5,
"alert_channel": "webhook"
}
}Sample Output
{
"alert_type": "glucose_critical_high",
"patient_id": "pat_123",
"observation": {
"value": 247,
"unit": "mg/dL",
"recorded_at": "2026-03-17T14:22:00Z"
},
"severity": "urgent",
"provider_notified": true
}Build a fully automated prior authorization workflow that connects EHR data, submits to payer APIs, tracks status, and handles appeals.
Install the HealthCloud Prior Authorization Agent.
POST /v1/assets/install
{
"asset_id": "agent_prior_auth_v1",
"project_id": "proj_abc"
}Configure the CMS Prior Authorization API integration.
POST /v1/integrations/configure
{
"type": "payer",
"provider": "cms",
"api_version": "PAS_R4",
"endpoint": "https://prior-auth.cms.gov/fhir/r4"
}Build the end-to-end prior auth workflow with appeals handling.
POST /v1/workflows
{
"name": "CMS Prior Authorization",
"steps": [
"extract_patient_data",
"verify_eligibility",
"submit_prior_auth",
"track_status",
"handle_denial"
]
}Subscribe to payer approval and denial events via webhooks.
POST /v1/webhooks
{
"url": "https://your-app.com/webhooks/prior-auth",
"events": [
"prior_auth.approved",
"prior_auth.denied",
"prior_auth.pending_info"
]
}Sample Output
{
"authorization_id": "auth_cms_456789",
"status": "approved",
"patient_id": "pat_123",
"procedure_code": "99091",
"valid_from": "2026-03-18",
"valid_to": "2026-06-18",
"payer": "CMS"
}Configure a bidirectional FHIR integration with Epic or Athenahealth to sync patient data, write observations, and launch SMART apps.
Select and configure your EHR connector from the integration catalog.
POST /v1/integrations/configure
{
"type": "ehr",
"provider": "epic",
"fhir_base_url": "https://fhir.epic.com/interconnect-fhir-oauth/api/FHIR/R4",
"auth_type": "smart_on_fhir"
}Complete the OAuth 2.0 SMART on FHIR authorization flow.
// Redirect user to Epic authorization GET /v1/integrations/epic/authorize? response_type=code& client_id=hc_app_xxx& scope=patient/*.read+launch/patient& redirect_uri=https://your-app.com/callback
Define which FHIR resources to sync and how they map to your data model.
POST /v1/integrations/epic/resource-map
{
"resources": ["Patient", "Observation", "Condition", "Encounter"],
"sync_frequency": "real_time",
"direction": "bidirectional"
}Initiate the first patient data synchronization.
POST /v1/integrations/epic/sync
{
"patient_ids": ["pat_123", "pat_456"],
"resources": ["Patient", "Observation"],
"date_range": {
"start": "2025-01-01",
"end": "2026-03-17"
}
}Sample Output
{
"sync_id": "sync_epic_789",
"status": "completed",
"resources_synced": {
"Patient": 142,
"Observation": 3847,
"Condition": 289,
"Encounter": 712
},
"duration_ms": 4230
}Coordinate multiple AI agents using the Model Context Protocol (MCP) to build a collaborative prior authorization and eligibility verification system.
Initialize an MCP session to coordinate multiple agents.
POST /v1/mcp/sessions
{
"agents": [
"agent_intake_v1",
"agent_eligibility_v1",
"agent_prior_auth_v1",
"agent_followup_v1"
],
"context": {
"patient_id": "pat_123",
"workflow": "prior_authorization"
}
}Attach each agent to the shared MCP session context.
POST /v1/mcp/sessions/sess_abc/agents
{
"agent_id": "agent_eligibility_v1",
"role": "eligibility_verifier",
"permissions": ["read_patient", "query_payer"]
}Inject shared patient context that all agents can access.
POST /v1/mcp/sessions/sess_abc/context
{
"patient": {
"id": "pat_123",
"condition": "UTI",
"payer": "CMS"
},
"insurance": {
"member_id": "CMS_9876543",
"plan": "Medicare Part B"
}
}Run the multi-agent workflow with shared context.
POST /v1/mcp/sessions/sess_abc/execute
{
"workflow": "coordinated_prior_auth",
"mode": "sequential"
}Sample Output
{
"session_id": "sess_abc",
"status": "completed",
"agents_executed": 4,
"steps_completed": [
"intake_collected",
"eligibility_verified",
"prior_auth_submitted",
"followup_scheduled"
],
"authorization_id": "auth_mcp_001",
"total_duration_ms": 1847
}Launch from a pre-built project template with full demo data and architecture already configured.
Complete diagnostic intake-to-result pipeline for urinary tract infection detection.
Full remote patient monitoring stack with device ingestion, FHIR normalization, and alerting.
End-to-end prior authorization workflow connected to CMS and commercial payer APIs.
Risk stratification and care gap analytics across a patient population with intervention workflows.
Follow these patterns from day one to build production-grade healthcare AI systems.
Never call agents directly from your application. Use workflows to define, sequence, and monitor every step.
Each agent should do one thing well. Compose complex logic from multiple focused agents via MCP sessions.
Build event-driven systems by subscribing to HealthCloud events rather than polling API endpoints.
Store all clinical data as FHIR R4 resources to ensure interoperability and AI model compatibility.
Try the interactive API Explorer, review the Object Reference, or open Studio to build with a template.