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Out of the FHIR Podcast · New episodes weekly

I help healthcare orgs make sense of FHIR, AI, and quality measurement

I'm Eugene Vestel. Through consulting, open-source tools, and the Out of the FHIR podcast, I help teams navigate healthcare interoperability and turn data into outcomes.

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Payer Interoperability Analytics & AI Lead at Outcomes · Former NCQA Advisor · 15+ years in healthcare data

Figure 1

What “quality measurement” looks like when it stops being a slide.

Fig. 1CBP · Controlling High Blood Pressure
SourceCQL
valueset "Systolic BP": '2.16.840.1.113883.3.526.3.1032' define "Numerator":  exists (    [Observation: "Systolic BP"] BP      where BP.effective during "Measurement Period"        and BP.value < 140 'mm[Hg]'  )
CompiledANSI SQL
SELECT DISTINCT p.patient_idFROM   patient AS pJOIN   observation AS o  ON   o.subject_ref = p.patient_idJOIN   valueset_member AS v  ON   v.code = o.code AND   v.system = o.code_systemWHERE  v.valueset_oid = '2.16.840.1.113883.3.526.3.1032'  AND  o.effective BETWEEN :period_start AND :period_end  AND  o.value_quantity < 140
Measure
1
Value sets
1
Source lines
7
Target lines
10
Fig. 1 — A quality-measure numerator written once in CQL, and the warehouse SQL it compiles to. The value set resolves to a join, the measurement period to a bounded predicate.

  • Outcomes

    Payer Interoperability Analytics & AI Lead

  • NCQA Advisor

    Quality Measurement

  • b.well Connected Health

    Director of Data & Analytics

  • UPMC Health System

    5 years in Clinical Analytics

  • Analytics on FHIR

    Conference Speaker · 2025

Podcast

Out of the FHIR

Weekly conversations with the people building the future of healthcare interoperability. From HL7 work group chairs to startup founders to CMS policy makers — the stories behind the standards.

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    Why CQL needs a better execution story

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Open Source

Building HealthClaw

An open-source AI health agent stack built on MCP, FHIR R4, and SMART on FHIR — exploring what happens when patients have the same processing power as provider systems.

Livehealthclaw.io

HealthClaw Guardrails

A security layer between AI agents and clinical data. Redacts PHI on every read, enforces multi-step human approval for clinical writes — proposal, permission evaluation, HMAC confirmation, immutable audit log — and keeps your health agent interactions HIPAA-compliant.

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  • 12 MCP Tools
  • PHI Redaction
  • FHIR R4/R6
  • US Core v9
  • Fasten Connect
  • Local SQLite
SMART on FHIR

Smart Health Connect

A SMART on FHIR patient records platform that aggregates your health data from Epic, Cerner, and other EHRs into a single secure interface. Provides curated health visualizations and MCP tools — the data layer that HealthClaw agents work with.

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  • SMART on FHIR R4
  • React + TypeScript
  • MCP Tools
  • AI Health Insights
  • Multi-EHR
  • PostgreSQL
Ecosystem Analysisainpi.dev

AINPI

An ongoing analysis of the CMS health tech ecosystem and the national provider directory modernization effort. Mapping the players, the standards, and the FHIR-based architecture behind the next-generation healthcare directory.

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  • CMS Ecosystem
  • National Provider Directory
  • NPPES
  • FHIR
  • Policy Analysis

More experiments in progress — Curatr Skills and others

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Resources

Free guides & references

Practical resources I've written based on real implementation experience.

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Advisory

Work with me

I advise healthcare organizations on FHIR implementation strategy, data architecture, quality measurement, and AI readiness. Whether you're starting your FHIR journey or optimizing an existing implementation, I can help you move faster and avoid common pitfalls.

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  • FHIR implementation strategy
  • Data architecture & pipelines
  • Quality measure implementation
  • SQL on FHIR adoption
  • AI & LLM integration
  • Team training & enablement

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