Fifteen-plus years leading enterprise analytics across risk adjustment, clinical quality, population health, and affordability for a $100B+ Medicare Advantage portfolio — now focused on the next frontier: agentic AI that works alongside analytics teams.
I'm a Healthcare Economics and Analytics executive who translates complex data into decisions leaders can act on. My work spans CMS risk adjustment (HCC/RAF), HEDIS/STARS quality, population health, and clinical affordability — the full economic engine of Medicare Advantage.
At UnitedHealth Group and CVS Health, I've led multi-year, enterprise-scale analytics transformations: standing up governance frameworks, building BI platforms, integrating acquired medical groups, and directing AI into production analytics workflows — cutting manual operations by more than 40% across 5M members while improving accuracy.
Beyond the dashboards, I build teams. I've grown and led geographically distributed organizations of 30–45 analysts, actuaries, and data scientists — and lifted retention 25% along the way.
My current focus is the next chapter of that story: transforming analytic workflows into AI employees — agentic systems that don't just report on the work, but do the work: monitoring populations, surfacing risk, drafting analyses, and escalating judgment calls to humans.
A career measured in outcomes — a few representative engagements.
Directed AI integration into enterprise BI workflows, automating risk-adjustment suspecting and quality gap identification across 5M Medicare Advantage members — reducing manual operations 40%+ while improving accuracy.
Spearheaded a 3-year, enterprise-scale analytics transformation — governance frameworks, KPI dashboards, and data validation protocols that maximized operational efficiency across the full Medicare Advantage portfolio.
Key analytic consultant for M&A and risk-transfer initiatives — evaluating business performance and revenue opportunity in diligence, then rapidly integrating acquired medical groups' data into national standards.
Authored a state-by-state pharmacy outcomes report on 80M members cited in state-legislature policy debates, and led landmark cigarette-cessation research using interrupted time-series modeling — a major public-health and brand win.
Lead enterprise BI and analytics delivering insights across the full spectrum of healthcare economics — risk adjustment, clinical quality, population health, and affordability — for 5M+ Medicare Advantage lives and $100B+ in annual revenue.
Led analytics and reporting for the enterprise's fastest-growing business units (Provider Relations, Med-D). Built the Specialty Pharmacy P&L analytics team for 340B initiatives and served as the analytic closer in PBM finalist meetings — driving client retention and new business wins.
Published the state-by-state pharmacy outcomes report analyzing 80M members and led the enterprise prior-authorization analytics initiative recognized by executive leadership as one of the most successful analytic efforts of the year.
Coordinated design projects and validated systems in the diagnostics division, ensuring FDA regulatory compliance and quality standards.
Purdue University · 2009
Purdue University · 2006
I don't just lead analytics — I still build. These working prototypes, engineered end-to-end, explore my core thesis: the analytic workflows teams run today become the AI employees of tomorrow.
Independent personal R&D, built exclusively on public and synthetic data (CMS public use files, CDC, Synthea). Not affiliated with, or representative of, any employer.
Interactive benchmarking of MSSP ACO performance — savings rates, quality scores, and risk-model dynamics — built from CMS public results files with an AI analyst layer for plain-English interpretation.
Geographic atlas of avoidable ED visits and admissions — surfacing where utilization patterns diverge from clinical expectation and what that means for total cost of care.
An AI copilot for care management workflows — prioritizing outreach, drafting member summaries, and flagging care gaps — demonstrated on fully synthetic patient data.
Themes I write and speak on — where healthcare economics is moving and what leaders should do about it.
As CMS keeps tightening the model, risk adjustment is no longer a coding exercise — it's a clinical-data discipline. The organizations that win treat accuracy as an engineering problem, not a chart-chase.
Most healthcare AI dies in the deck. The real shift is analytic workflows becoming AI employees — agents that run suspecting, gap closure, and quality review end-to-end while humans move up to judgment.
Total cost of care doesn't bend with dashboards alone. It bends when utilization signals, risk data, and provider incentives are engineered into one decision system.
Follow along on LinkedIn — where I share perspectives on healthcare economics, value-based care, and building AI-driven analytics organizations.
Follow on LinkedInI selectively engage on problems at the intersection of healthcare economics, analytics strategy, and AI.
Strategic counsel for leaders navigating Medicare Advantage economics and value-based care.
Hands-on guidance transforming analytic workflows into agentic AI teammates — with humans on judgment.
Analytic due diligence for healthcare transactions — from thesis to integration.
Whether it's a leadership conversation, an advisory engagement, or a hard analytics problem — I'd love to hear from you.