Featured InsightMay 2026
Design Before Deploy
Objective-Function Governance for AI-Assisted Medicare Review
Lance McNeill, MBA, MPAff
How WISeR, Private-Payer AI Denials, and Medicare Audit Appeals Reveal Why High-Stakes Public AI Systems Must Be Co-Created Before Procurement
AI GovernanceMedicareHealthcare Policy
Policy White PaperMay 2026 - Updated Edition
Upstream Denials, Downstream Costs
Hidden Systemic Costs and Measurement Failure in Medicare Unified Program Integrity Contractor (UPIC) Determinations
Lance McNeill, MBA, MPAff
UPICs are paid to find fraud, waste, and abuse. But who measures whether their determinations are right? This updated Arclight Insights white paper estimates the hidden systemic cost of reversed, plausibly reversible, and unappealed UPIC determinations at $49 million to $250 million annually, while documenting a deeper measurement failure: CMS does not publish contractor-level appeal outcomes. The paper argues that Medicare program integrity should measure accuracy, not just activity.
MedicareUPICProgram IntegrityAppeals
White PaperApril 2026
Pricing Spike to Spiral
How reimbursement dynamics and incentives create rapid pricing escalation in skin substitute markets.
MedicareHealthcare PolicyProgram Design
AnalysisApril 2026
Rationale Drift in Medicare Audit Appeals
How denial rationales shift across audit stages, undermining due process and consistent adjudication.
MedicareAppealsDue Process
EssayMay 2026
Common Sense 250 Years Since
A Legitimacy Audit for the AI Republic at America's 250th Birthday
Lance McNeill, MBA, MPAff
Two hundred and fifty years after Thomas Paine used Common Sense to challenge inherited authority, this essay asks what a legitimacy audit would reveal about American public institutions today. It argues that declining public trust, fiscal opacity, institutional capture, and administrative complexity are not just political frustrations; they are design failures that become more dangerous as artificial intelligence enters the machinery of government.
The essay makes a case for AI as a civic accountability layer: not a tool merely for government to process, monitor, or enforce faster, but a tool citizens can use to see public power more clearly. Its central principle is simple: audit before automation, co-creation before deployment, and public purpose before institutional convenience.
Civic AccountabilityAI GovernancePublic TrustAmerica 250