Skills

FHIR and EHR Product Leadership Skills

A product-focused capability inventory spanning strategy, discovery, roadmap decisions, clinical-data interoperability, delivery governance, and post-live measurement.

Capability Areas

Ownership Areas

Product Strategy & Portfolio Direction

Product judgment for deciding which interoperability problems deserve platform investment and how to sequence them.

  • Product problem framing across customer, clinical, technical, and operational needs
  • Roadmap prioritization using onboarding friction, support trends, launch risk, customer urgency, and reusable platform value
  • Standardization decisions versus explicit partner-specific exception handling
  • Legacy-to-modern platform choices grounded in installed-base delivery and support realities

Discovery, Roadmaps & Prioritization

Evidence-driven practices that turn ambiguous integration requests into executable product decisions.

  • Discovery facilitation, user and workflow context, scope boundaries, and requirement traceability
  • Story writing, acceptance criteria, success signals, and dependency decisions
  • Customer-specific urgency balanced against repeatable platform capability
  • Cross-functional alignment across engineering, QA, operations, implementation, security, customers, and vendors

Clinical-Data Interoperability Platforms

Technical fluency used to make credible product tradeoffs across healthcare integration patterns.

  • HL7 v2, FHIR DSTU2, R4, and R5, SMART on FHIR, CDS Hooks, and OAuth2
  • Databases, ODBC, SQL, REST APIs, OpenAPI or Swagger artifacts, webhooks, and interface engines
  • RabbitMQ, queue-based coordination, event-driven workflows, and automation-assisted handoffs
  • Care-setting context across hundreds of ambulatory and acute care EHR/EMR systems, including Epic, eClinicalWorks, and ModMed environments

Delivery Governance & Launch Decisions

Operating controls that connect product intent to safe, evidence-based production decisions.

  • Integration testing, UAT sequencing, defect triage, launch gates, cutover readiness, and hypercare
  • Risk ownership, escalation paths, support handoffs, and executive-ready decision communication
  • HIPAA-aware delivery practices, PHI/PII handling, and audit-conscious process design
  • Tooling fluency with Jira, Confluence, Azure DevOps, GitHub, and SQL-based collaboration

Measurement & Post-Live Learning

Operational evidence used to judge product outcomes and improve future platform decisions.

  • Interface reliability, SLA performance, onboarding cycle time, data-quality exceptions, and incident resolution trends
  • Support ticket patterns and escalation themes as inputs to remediation and roadmap prioritization
  • Post-live review cadences that compare intended outcomes with observed workflow behavior
  • Feedback loops across support, implementation, engineering, and product teams
Technical Artifacts

Representative Interoperability Artifacts

These are anonymized examples of the working artifacts that make EMR connectivity programs more predictable. They are included to show how complex interoperability work is framed and controlled, not to showcase coding for its own sake.

Interoperability Discovery Checklist

An anonymized scoping artifact used to define EMR connectivity work before implementation starts.

Purpose

Clarify partner-system constraints early so technical, operational, and client-facing teams are working from the same problem definition.

What It Covers

  • Workflow, care-setting, and source-system context for the integration request
  • Connectivity model selection across HL7 v2, FHIR, SMART on FHIR, CDS Hooks, APIs, interface engines, databases, and ODBC
  • Mapping assumptions, authentication needs, test dependencies, and launch ownership
  • Support, escalation, and post-live accountability expectations before build begins

Why It Matters

It reduces avoidable churn by making interoperability constraints explicit before they become late-stage delivery surprises.

Hybrid HL7 and FHIR Delivery Playbook

A representative playbook for programs that have to support both legacy interface-engine workflows and more modern API or FHIR delivery.

Purpose

Give implementation, engineering, QA, and support teams one operating model when the technical stack spans both installed-base and modern interoperability patterns.

What It Covers

  • Contract review, acceptance criteria, and readiness checkpoints shared across legacy and API-based workstreams
  • Testing, cutover, and handoff expectations for interface-engine, HL7, and FHIR-driven implementations
  • Ownership rules for production support when different integration models coexist
  • Guidance for standardizing repeatable patterns versus allowing partner-specific exceptions

Why It Matters

It shows how to modernize interoperability delivery without pretending the installed base of EMR connectivity constraints has disappeared.

Go-Live Risk and Hypercare Model

A launch-control artifact used to keep release decisions, cutover communication, and early-life support grounded in real readiness signals.

Purpose

Create a shared view of go or no-go evidence, dependency owners, escalation expectations, and post-live follow-through.

What It Covers

  • Readiness checkpoints tied to testing completion, data quality, interface behavior, and support coverage
  • Dependency tracking across engineering, QA, operations, implementation, and client stakeholders
  • Hypercare severity paths, incident ownership, and communication expectations
  • Post-live review loops that feed stability issues and onboarding lessons back into future delivery work

Why It Matters

It demonstrates operational accountability beyond the interface build itself, which is often where healthcare SaaS programs succeed or fail.