Outcomes, evidenced

Challenge

A high-volume specialty healthcare organization needed to own enterprise Epic interoperability and migration end-to-end — across Epic Bridges, Data Courier, FHIR, and OAuth — while protecting patient-identity integrity through the transition.

Approach

Took full ownership of the migration and interoperability workstreams from planning through go-live, treating patient identity and interface discipline as the make-or-break factors rather than the cutover date.

Implementation

• Drove integration planning, vendor coordination, build validation, and go-live readiness across Epic Bridges, Data Courier, FHIR, and OAuth
• Owned critical external interface domains (Rosch, Zocdoc, LabCorp, Quest, Surescripts) spanning ADT/SIU/ORM/ORU/DFT routing and downstream acceptance
• Led enterprise-wide EMPI cleanup — reconciling and de-duplicating patient index tables with robust matching and validation logic
• Coordinated end-to-end data migrations into cloud imaging (Nuance PowerShare) with radiology and IT to preserve workflow continuity

Measurable outcome

Delivered production go-live with downstream data integrity protected: identity conflicts resolved through EMPI reconciliation, and external interfaces accepted reliably across vendors.

Challenge

A 10+ year call-center operation handling 1.2M calls a year had no data layer to govern AI agents, telephony, QA, and vendor performance — leaving spend and outcomes effectively unmeasured.

Approach

Built an executive-grade intelligence and contract-leverage reporting layer that benchmarks vendors against each other and against the business, not against the demo.

Implementation

• Intelligence layer governing 1.2M annual calls across AI agents, telephony, QA, transfers, and containment
• 60+ native KPIs researched per platform and 60+ comparative KPIs designed across RingCentral, Balto, and Cognigy/Ella AI
• Vendor accountability hardened with 10+ contract clauses on security, data use, and performance
• Expansion into marketing forensic audits and attribution to back spend decisions with data

Measurable outcome

Surfaced underutilization and misunderstood intent, validated vendor claims, and supported pricing reductions through data-backed usage reports — turning a cost center into a governed, measurable operation.

Challenge

Hybrid EHR ecosystems needed reliable, standards-compliant HL7 and FHIR exchange across Epic, Cerner, and Meditech — with documentation rigorous enough for federal healthcare integration teams.

Approach

Architected interoperability frameworks and multi-engine interface logic, paired with control documentation detailed enough to guide implementation at federal scale.

Implementation

• 200+ HL7 and FHIR integrations across clinical, operational, and vendor-facing systems
• Multi-engine interface logic across Corepoint, Cloverleaf, Mirth Connect, and InterSystems IRIS
• Interface Control Documents exceeding 100 pages for Department of Defense healthcare integration teams
• HL7 v2 (ADT, ORU, ORM, MDM, RDE) mapped to FHIR R4 with SMART on FHIR scopes and OAuth2 access control

Measurable outcome

Delivered 200+ integrations and 15+ large-scale HIE programs at 95% client satisfaction, while reducing post-deployment defects by 30% through code review and disciplined testing.

Challenge

High-latency, manual clinical and operational workflows needed event-driven automation and applied AI — focused where delay is genuinely expensive.

Approach

Designed automation pipelines and applied-AI solutions on observable infrastructure, prioritizing the moments where latency or missed signal carries real cost.

Implementation

• Telestroke escalation: parse inbound HL7 ADT and instantly alert on-call neurologists via SMS/email (Workato + Corepoint)
• Applied AI/ML tooling (ChatGPT, OHIF Viewer, MONAI) to support clinical decision-making and analysis
• AI operational-intelligence layer governing 1.2M annual calls with explainable, persisted metrics
• Cloud-managed automation on n8n + Baserow with full telemetry and no hidden state

Measurable outcome

Reduced response time in critical stroke cases through automated escalation, and gave leadership data-driven governance over a 1.2M-call operation — automation aimed where it changes outcomes.