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.

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.

Track record

  • 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

Newsletter

The FHIR IQ Playbook

A weekly newsletter on FHIR implementation, quality measurement, healthcare AI, and the tools and standards shaping interoperability. Written for the people doing the actual work.

Read by 450+ healthcare data professionals · Presented at Analytics on FHIR 2025

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Open Source

What I'm building

A guardrail layer between AI agents and health data, a personal care agent built on top of it, and an open corpus of the quality measures the whole industry keeps rewriting from scratch. All open, all running.

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.

  • 12 MCP Tools
  • PHI Redaction
  • FHIR R4/R6
  • US Core v9
  • Fasten Connect
  • Local SQLite
Livecareagents.cloud

CareAgents

Spin up a personal health agent in under a minute. Every read redacted, every access audited, every action approved by you — guardrailed by HealthClaw. This is what the guardrail layer looks like once a person is actually using it.

  • Personal health agent
  • Redacted reads
  • Audited access
  • Human approval
Liveopenquality.us

Open Quality

An open, MIT-licensed corpus of healthcare quality measures with verified provenance, plus a typed record of what implementers have actually learned about each one. CQL and SQL alongside the measure, not buried in a PDF.

  • MIT licensed
  • Verified provenance
  • CQL + SQL
  • Implementer notes
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.

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

More experiments in progress — Curatr Skills and others

See all projects on GitHub

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.

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

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