About
Founder, Ohana Consulting LLC
The AI opportunity in healthcare isn't surprising to me. Neither are the reasons it tends to fail. I've spent twenty years at the intersection of clinical workflow, data exchange standards, and enterprise software — inside the organizations that built the systems AI now needs to work with.
What is new — and genuinely hard — is the governance problem. AI systems in regulated environments require accountability mechanisms that don't exist yet in most organizations. The standards bodies write frameworks for human reviewers. The AI systems operate on structured data. Bridging that gap is the work.
Eight years as a technology executive for advanced clinical solutions. The most significant work here was Calypso — an internal platform I designed and built for multi-EHR integration using FHIR and SMART on FHIR. One application, any EHR. Calypso gave clinical and administrative applications access to patient data across health systems without proprietary integration contracts for each.
Beyond Calypso: I led Optum's technical engagement on 21st Century Cures compliance, contributed to AI-driven clinical decision support offerings, and served as the lead technology executive for prior authorization guidance initiatives. The through-line across all of it was the same — open standards as the foundation, governance as the enabler, and clinical workflow as the constraint that everything else has to fit inside.
Architect and designer for embedded systems, OpenStack, and OpenShift (Docker/Kubernetes). This is where the cloud-native infrastructure expertise lives — the same stack that now runs AI workloads in production. Understanding distributed systems, container orchestration, and the operational requirements of software running at scale is not optional background knowledge for AI deployment; it's the foundation.
Software Development Product Manager across IBM's full software portfolio. The defining project of this period: I conceived and drove the decision to open source Eclipse, one of the most consequential bets in enterprise open source history. It shaped how I think about open standards — not as compliance obligations but as strategic instruments for building ecosystems that outlast any single vendor.
That lens — understanding how open standards actually function in commercial ecosystems, where the value gets created, and how to participate constructively — is directly applicable to the interoperability standards that healthcare runs on.
Product Manager for ThinkPad Accessories, including secure external storage, adapter cables, and USB-C implementations. The value here is less the domain and more the discipline: hardware-software integration at the product level, security requirements at the silicon level, and the full product lifecycle from specification to manufacturing to market.
B.S., Electrical Engineering — Rutgers University
M.S. Certificate, Healthcare Informatics — Boston University
The combination is deliberate. Engineering gives me the technical foundation to evaluate what's actually possible. Healthcare informatics gives me the clinical and regulatory context to understand what's actually required. Most AI projects in healthcare suffer from too much of one and not enough of the other.