Case Study — CareAxis

Multi-Clinic Coordination Platform

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

Clinics Unified

73%

Reduction in Care Handoff Errors

EMR Systems Integrated

4.2×

Referral Completion Rate Improvement

Solution Blueprint

How It All Fits Together

Integration Layer

HL7 FHIR R4 façade
8 EMR connectors
Event-driven patient sync

Clinical Operations Layer

Care gap detection engine
Referral workflow automation
Population health dashboard

Compliance Layer

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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