Built for the leaders accountable to both the auditor and the CFO.
Bigelow Healthcare Consulting is a specialist advisory practice focused on one thing: helping risk-adjusted plans and payers of all sizes run risk adjustment programs that are both audit-defensible and financially sound. Mark Bigelow founded the firm after fifteen years across healthcare finance, operations, and risk adjustment leadership at organizations that carry the risk themselves — and he translates that work into the financial language CFOs, actuaries, and finance teams use to evaluate it.
Mark has held executive leadership roles in risk adjustment at Cambia Health Solutions, Premera Blue Cross, Optum Care, PacificSource Health Plan, and EXL Health, with earlier career roles in finance and analytics at Molina Healthcare.
Across that tenure, the cumulative impact has added up to more than $100M in documented coding accuracy; spanning risk-score accuracy, predictive analytics, submissions transformation, expanded HCC recapture, and actuarially supported rate advocacy. While leading the Risk & Quality product at EXL, the product was recognized with the 2022 Best-in-KLAS award for risk adjustment analytics.
One thing sets the practice apart from most RA advisors: fluency in finance. Mark started in FP&A and never left the discipline behind. He translates risk adjustment work into the language CFOs, actuaries, and finance teams use — MLR impact, RAF-to-revenue translation, audit exposure as a balance-sheet risk, bid implications, vendor cost-to-revenue. The work does not live in operations alone; it has to pencil out in the boardroom. That lens traces back to an MBA from the University of Washington and a BA in Economics from Brigham Young University, with emphases in financial economics, econometrics, and strategy.
The practice is built around a specific belief: that in 2026, regional payers and providers can be successful in risk-adjusted business but only with deep provider partnerships, actionable analytics, and complete and accurate coding and submissions, defensible to any regulator.
Listen first. Every engagement opens by listening — a short diagnostic where I read the policies, sit with the coders, review the vendor SLAs, and pull the audit and encounter data. I don't write recommendations on a program I haven't understood from the inside.
Do the right thing. I design coding and documentation workflows to be defensible under RADV extrapolation, aligned with current HRA guidance, and consistent with MEAT documentation standards. Compliance comes before capture — when a practice is technically available but wouldn't survive an audit, I say so, even when it costs RAF.
I speak finance. Every recommendation is quantified in the terms your CFO, actuary, and finance team work in: MLR impact, RAF-to-revenue translation, audit exposure as a balance-sheet risk, bid implications, vendor cost-to-revenue. Compliance and operations are necessary. Penciling out in the boardroom is also necessary.
AI-assisted, human-accountable. I use AI in my own analytical work — data analysis, modeling, financial calculations, and planning. I don't use it to make clinical, coding, or diagnosis determinations, and I don't put anything in front of a regulator that a qualified person hasn't reviewed and can defend. Where coding technology is in scope for your program, I evaluate it — including AI-agent coders, which I believe can outperform legacy NLP — on accuracy and audit-defensibility, and recommend accordingly.
Results you can measure. Each engagement is anchored to two or three numbers — coding accuracy, RAF capture, audit pass rate, vendor cost-to-revenue — and scoped so your team can run the changes after I leave.
Help you rebuild coder workflows for V28. Prepare for a RADV audit under extrapolation. Stand up vendor oversight that catches problems before CMS does. Reframe coding-accuracy targets so clinical, compliance, and finance leaders are accountable to the same number. Quantify every recommendation in the financial terms your CFO needs to approve it.
Recommend coding or documentation practices I cannot defend in an audit. Optimize for RAF capture at the expense of OIG-defensibility. Take over your chart coding, or stand behind any coding approach — AI-agent or human — that wouldn't survive a RADV audit. Build an engagement plan that depends on a vendor I know underperforms. Hand a plan leadership team a recommendation that hasn’t been pressure-tested against MLR, bid, and audit-exposure math.
Ready to talk?
The first conversation is thirty minutes. It focuses on your highest-pressure problem — V28, RADV, coding accuracy, vendor performance, or something else — and whether there is a good fit before either side commits further.