Research, analysis, and insights on AI-driven revenue intelligence for rural hospitals, managed care organizations, and the Medicaid ecosystem.
What the PHTI Report Means for Rural Health — and the Real Path to Solving Uncompensated Care
The Peterson Health Technology Institute just confirmed it on the record: AI is not lowering system-wide healthcare costs — it is raising them. Why generic AI RCM is making rural hospitals the third loser, why MCOs are paying for the same churn, and what an operator-led path forward actually looks like.
The Behavioral Science of Revenue Cycle Intelligence
How cognitive limitations — not staff limitations — drive rural hospital revenue loss. Explores the science of serial vs. parallel processing and what changes when AI can analyze 835 remittance data across all eight dimensions simultaneously.
Why Rural Hospital Revenue Recovery Requires a Different Kind of AI
Why generic healthcare AI fails at the rural hospital Medicaid problem, and what purpose-built, state-specific intelligence looks like in practice. Features Kansas and Nebraska case data with MCO-specific analysis.
Medicaid complexity is structurally underpaying rural hospitals — and almost nobody is working the recovery side.
Why most rural hospitals are being underpaid by Medicaid for services they have already rendered, why generic AI doesn’t solve the problem, and what recovery actually looks like — written for CFOs and boards being asked to make survival decisions without a complete picture.
Why Managed Care Needs a New Intelligence Layer
Medical costs are outpacing capitation. Enrollment is churning. CMS is watching. What the data says about the Medicaid managed care margin crisis — and what MCOs can do about it.
Why New Mexico Hospitals Must Build Their Own Revenue Recovery Infrastructure
When every layer of a state's Medicaid infrastructure fails simultaneously, hospitals are structurally on their own. A state-level case study in systemic failure — and what it means for every hospital in America.