Integrated Clinical Intelligence Suite
A next-generation healthcare ecosystem that bridges the clinical encounter and patient recovery with integrated AI, combining ambient documentation with proactive patient monitoring.
The brief
We built and shipped an integrated clinical suite that links the encounter to recovery: an ambient scribe drafts the note in real time, then a monitoring layer tracks each patient between visits and escalates risk automatically: one system from the exam room to follow-up, replacing two disconnected tools and a manual triage queue.
By combining automated documentation with proactive patient monitoring, the suite turns raw medical data into actionable insights.
How it works in the clinic
Intelligent Documentation
- Captures doctor-patient nuances in real time using speech-to-text and NLP.
- Automatically pre-fills EHRs for practitioner review and one-click filing.
Post-Treatment Engagement
- Generates customized journals based on specific session diagnoses.
- Tracks high-relevancy clinical markers, such as medication side effects.
Risk Stratification
- Uses a “traffic light” system to analyze patient responses.
- Red: immediate risk
- Yellow: moderate
- Green: on track
Proactive Care Coordination
- Initiates secure AI chats for red / yellow flags.
- Performs triage interviews and enables automated escalation.
What it runs on
The solution uses a service-oriented architecture based on microservices to ensure scalability, security, and HIPAA eligibility.
Microservices Layer (AWS EKS)
The Node.js backend is decoupled into specialized services running on Kubernetes:
- Scribe Service. Manages real-time audio streams and interfaces with AWS HealthScribe.
- Patient Engagement & Triage. Orchestrates Amazon Bedrock and Lex logic for questionnaires and follow-up chats.
- Scheduling & Analytics. Integrates calendar systems and aggregates performance metrics.
Hybrid Data & Storage Strategy
To balance archival durability with high-speed search, a polyglot storage approach is used:
- Structured Data. Amazon RDS (PostgreSQL) serves as the primary registry for patient data.
- Archival Transcripts. Amazon S3 with Glacier lifecycle policies stores raw audio and full transcripts.
- Search Engine. Amazon OpenSearch Serverless handles full-text search and vector embeddings for RAG.
- Caching & Messaging. MemoryDB for Redis ensures durable session state; Amazon MQ decouples service communication.
Run, monitor, stay compliant
AI-Driven Testing & CI/CD
The AWS CodeSuite pipeline ensures high velocity through automated quality gates:
- Autonomous Test Generation. Amazon Bedrock analyzes code changes to select or generate relevant Playwright E2E scripts.
- Self-Healing Locators. The Playwright suite uses AI to adapt to UI changes automatically, preventing pipeline breakage.
Dashboarding & Monitoring
A dual-layer approach provides a single pane of glass via Amazon Managed Grafana:
- Infrastructure (CloudWatch). Tracks RDS CPU, MemoryDB health, and MQ message counts.
- Clinical Intelligence. Monitors red-flag density, AI latency, and EKS pod health.
Tuned for clinical relevance
To ensure generated content is medically sound, we employ a context-aware prompting strategy using a frontier clinical model.
System Role
Board-certified clinical assistant persona.
Primary Data
Structured JSON from the Virtual Scribe (diagnosis, vitals).
Constraint Guardrails
Symptom tracking at an 8th-grade reading level; no medical advice.
Strategy
Uses chain-of-thought to identify risks (e.g. DVT) before formulating questions.
The outcome
In production this put one system in front of the clinician for the whole arc of care: the scribe drafts the note during the visit, the questionnaire follows the patient home, and the flagging layer surfaces the cases that need attention before they become emergencies, so the manual triage queue and the second documentation tool both went away.
Frequently asked questions
What does the Integrated Clinical Intelligence Suite do?
It links the clinical encounter to recovery: an ambient AI scribe drafts the note in real time, then a monitoring layer tracks each patient between visits and escalates risk automatically, replacing two disconnected tools and a manual triage queue with one system.
How does the risk-stratification “traffic light” system work?
Patient questionnaire responses are scored red, yellow or green. Red and yellow flags automatically initiate secure AI triage chats and enable escalation, so high-risk patients are surfaced before they become emergencies.
Is the suite HIPAA-eligible?
Yes. It runs on a HIPAA-eligible AWS microservices architecture (EKS, RDS, S3, OpenSearch) with encryption, durable session state and audit logging throughout.