ARCLIGHT

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Arclight Insights

Policy Research on Complex Systems

Featured Research

Featured InsightApril 2026

Design Before Deploy

Objective-Function Governance for AI-Assisted Medicare Review

Lance McNeill, MBA, MPAff

AI in healthcare does not fail because of capability alone. It fails when systems are optimized around the wrong institutional incentives before affected stakeholders have helped define what the system should actually do. Using Medicare's WISeR model and private-payer denial systems as case studies, this paper applies objective-function governance to public-sector AI: define the objective, constraints, edge cases, evidence standards, and accountability structures before procurement and deployment.

AI GovernanceMedicareHealthcare Policy

Additional Insights

White PaperApril 2026

Upstream Denials, Downstream Costs

How upstream audit determinations drive downstream cost, delay, and administrative burden across the Medicare appeals system.

MedicareProgram IntegrityIncentive Analysis
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
Forthcoming

Future Research

Additional papers in development

Arclight's research agenda continues. Papers in development address systemic accountability gaps, co-creation methodology in public-sector AI, and governance frameworks for high-stakes automated decision systems.