Case Study — CareAxis
Unifying 47 Clinics on a Single Care Coordination Platform in 18 Weeks
HIPAA-compliant care coordination across a fragmented regional health network
Industry
Healthcare — Regional Health Network
Timeline
18 weeks
Team
8 engineers
Tech
HL7 FHIR + React + AWS
The Challenge
A regional health network with 47 clinics ran on 8 different EMR systems with no integration between them. Patient handoffs between facilities were manual, relying on fax and phone calls. Care gaps went undetected, referral completion was tracked in spreadsheets, and clinicians had no view of a patient's full care history across the network.
Our Approach
How We Solved It
FHIR Integration Layer
Built a HL7 FHIR R4 integration layer that normalized patient records from 8 different EMR systems into a canonical clinical data model without requiring any EMR replacement.
Care Gap Detection Engine
Deployed clinical rules engine that compares each patient's care history against evidence-based preventive care protocols, surfacing gaps to the care coordinator dashboard in real time.
Referral Workflow Automation
Replaced the fax-and-phone referral process with a structured digital workflow — ordering clinician sends referral, receiving clinic accepts/schedules, and the system tracks completion automatically.
Unified Coordinator Dashboard
Built a role-specific dashboard for care coordinators showing all active patients across facilities, flagging incomplete referrals, overdue follow-ups, and high-risk discharges.
Engineering Process
How We Built It
FHIR Façade Architecture
Rather than deep EMR integration, we built a FHIR façade that each EMR writes to via webhook on patient events — minimal EMR change, immediate interoperability.
HIPAA Audit Trail by Default
Every data access, modification, and patient communication event is logged to an immutable audit trail in AWS S3 with field-level encryption and tamper detection.
Role-Based Clinical Views
Built distinct UI views for physicians, care coordinators, and administrators — each seeing only the data and workflows relevant to their clinical role.
Architecture Decisions
Key Technical Choices
FHIR R4 Over Proprietary Integration
Adopted FHIR R4 as the canonical model despite the upfront mapping effort — it gave us a standards-based foundation that scales as the network adds EMRs.
Event-Driven Over Request-Response
Patient state changes propagate via events rather than polling, ensuring all 47 clinics see updated care plans within seconds of any clinical action.
AWS HealthLake for Patient Data Store
Used AWS HealthLake as the FHIR-compliant data store to inherit HIPAA BAA coverage, audit logging, and ML-ready analytics output without building from scratch.
Results
What We Delivered
Solution Blueprint
How It All Fits Together
- HL7 FHIR R4 façade
- 8 EMR connectors
- Event-driven patient sync
- Care gap detection engine
- Referral workflow automation
- Population health dashboard
- HIPAA audit trails (AWS S3)
- Field-level encryption
- Role-based clinical access
Lessons Learned
What We Improved
Clinical Workflow Design Before System Design
We spent 3 weeks shadowing care coordinators before writing code. The referral workflow we designed in that period had a 94% adoption rate because it matched how coordinators actually work.
FHIR Mapping Is an Ongoing Effort
Each EMR system had unique interpretations of FHIR profiles. Budget for ongoing mapping maintenance — it's not a one-time integration task.
Change Management Needs Its Own Team
The technology worked. The hardest part was getting 47 clinic administrators to change their fax workflows. A dedicated clinical change manager was essential to adoption.
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