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Interoperability

SynCare: FHIR-Compliant Health Information Exchange

A data platform enabling seamless health information exchange across disparate EHR systems, built on FHIR R4 and designed for coordinated care delivery in multi-payer, multi-provider environments.

Role

Product Lead

Domain

Interoperability / HIE

Stack

FHIR R4, HL7v2, REST APIs

Setting

Multi-Site Care Network

Problem

Care teams operating across multiple sites lacked a unified view of patient data. Critical information — medications, recent labs, specialist notes — was siloed across different EHR systems (Epic, athenahealth, eClinicalWorks), leading to duplicated tests, missed medication interactions, and fragmented care transitions. Existing integration approaches relied on batch file drops and manual reconciliation, creating 24-48 hour data latency.

Approach

Designed and led development of a FHIR-native integration platform that aggregated patient data from multiple EHR systems into a single longitudinal record accessible at the point of care.

  • FHIR R4 resource mapping — standardized clinical data from heterogeneous sources into canonical Patient, Condition, MedicationRequest, Observation, and DocumentReference resources
  • Real-time event-driven sync — replaced batch ETL with HL7v2 ADT/ORM event triggers feeding a FHIR write pipeline, reducing data latency from days to minutes
  • Clinical data reconciliation — built deduplication logic for medications and problems using RxNorm and SNOMED CT terminology mapping
  • Provider-facing dashboard — embedded aggregated patient summary within existing EHR workflows via SMART on FHIR launch context

Results

Deployed across a multi-site care network, connecting three distinct EHR platforms into a unified interoperability layer.

87%
Reduction in data latency
3
EHR systems connected
31%
Fewer duplicate lab orders

Lessons

Interoperability is as much a governance challenge as a technical one. The hardest problems weren't FHIR resource mapping — they were getting clinical stakeholders across organizations to agree on data quality standards and reconciliation rules. Building trust through transparent data lineage and clinician-facing data provenance indicators was essential for adoption.