Azalea Triage

Azalea Triage Intelligent patient routing engine

Azalea Triage ingests unstructured patient-submitted symptoms and requests, performs urgency classification, and routes each case to the appropriate clinical or operational queue via configurable rules and model-driven scoring.

Technical capabilities:

• Input processing: Parses free-text symptom descriptions, structured intake forms, and patient requests (portal messages, chat, phone transcripts) into normalized case records
• Urgency classification: Applies a clinical acuity model to score and categorize cases (e.g., emergent / urgent / routine / administrative), with configurable thresholds per care setting
• Routing logic: Directs cases to the correct destination — clinical team, care coordinator, billing/admin queue, or escalation pathway — based on classification output plus configurable business rules (specialty, provider availability, payer, location)
• Escalation handling: Flags time-sensitive or high-acuity cases for immediate human review, with configurable SLAs and alerting
• Auditability: Logs classification rationale and routing decisions for clinical oversight, QA, and compliance review
• Integration: Designed to sit alongside existing EHR/telehealth intake systems, consuming inbound patient data and pushing routed cases into downstream queues or task systems
• Human-in-the-loop: Supports override and correction workflows so staff can adjust routing decisions, which can feed back into model tuning

Deployment considerations: Intended for environments with defined clinical escalation protocols and staff review capacity for high-acuity flags; not intended as a standalone diagnostic or autonomous clinical decision-making tool.

Pricing: $70,000

Azalea Triage Intelligent patient routing engine

System Architecture

1. Ingestion Layer

• Multi-channel intake adapters (patient portal API, SMS/chat webhook, telephony transcript feed, structured EHR intake forms)
• Normalization service converts heterogeneous inputs into a unified case schema (patient ID, timestamp, source channel, raw text, structured fields)
• PHI-aware preprocessing with field-level encryption at ingestion

2. Classification Engine

• NLP pipeline: named-entity recognition for symptom/condition extraction, negation detection (e.g., "no chest pain"), temporal reasoning (symptom onset/duration)
• Acuity scoring model: gradient-boosted or transformer-based classifier trained on clinically labeled triage data, outputting a calibrated urgency score (0–1) mapped to categorical bands (emergent / urgent / routine / administrative)
• Confidence thresholding: low-confidence classifications auto-route to human review queue rather than forcing a decision
• Model versioning and shadow-mode deployment support for safe rollout of updated classifiers

3. Routing Orchestrator

• Rules engine (declarative, e.g. YAML/JSON-configured) layered on top of model output — combines acuity score with business logic (specialty match, provider capacity, payer/network rules, geographic/location constraints)
• Priority queueing with weighted fairness to prevent starvation of lower-urgency cases
• Destination adapters push routed cases to downstream systems (EHR task lists, care coordination platforms, admin ticketing systems) via REST/HL7 FHIR/webhook

4. Escalation & Alerting

• Real-time alerting service (push/SMS/pager integration) triggered on emergent classifications
• Configurable SLA timers with breach notifications
• Dead-letter queue for failed routing attempts, with automatic retry and fallback-to-human-review

5. Human-in-the-Loop Layer

• Override interface for staff to reclassify or reroute cases
• Correction events captured as labeled training data for periodic model retraining
• Reviewer audit trail (who overrode what, when, rationale)

6. Observability & Compliance

• Structured decision logs (input features, model output, rule matches, final routing) retained for audit and QA
• Metrics pipeline tracking classification accuracy, routing latency, escalation response time, override rate
• Access controls and encryption aligned with HIPAA data handling requirements; full audit logging for compliance review

7. Integration Surface

• Inbound: EHR/telehealth intake APIs, patient portals, messaging platforms
• Outbound: FHIR-compatible case objects, task/queue systems, alerting/paging services
• Sync/async modes supported depending on downstream system capabilities

Pricing: $70,000

Here's a price breakdown for Azalea Triage at $70,000, structured across the typical cost categories for a system like this:

Notes on structure:

• This assumes a first-year all-in price (license + implementation), which is typical for enterprise healthcare software — renewal years are usually license + support only (often 60–70% of year-one cost, roughly $40–45K).
• Actual weighting shifts based on deployment complexity — a single-clinic deployment skews toward implementation being smaller and license being a larger share; a multi-site health system deployment would push integration and compliance costs up.
• Volume/case-count tiers aren't reflected here — if pricing is usage-based (e.g., per-case or per-provider), the breakdown would look different (e.g., platform fee + per-case rate).