Proof of concept deployments and results from early customers demonstrate the power of AI-driven fraud detection at scale
Scale of fraud, waste, and abuse across government benefit programs
Source: CMS Improper Payments Report, HHS OIG Data, State Medicaid Director surveys. The $29B figure represents federal estimates of Medicaid fraud, waste, and abuse. State-level research by HRN Group and academic institutions suggests the true figure is likely 40-50% higher when accounting for undetected fraud vectors.
Early deployment results from healthcare system engagement
Large regional health system with complex payer billing
Identified in initial 90-day engagement through claims analysis, fee schedule review, and denial management
$1.8M
Underpayments from fee schedule corrections
$1.2M
Appeal-eligible claim denials prioritized for recovery
$800K
Coding optimization and place-of-service corrections
$400K
MCO capitation overpayment recovery potential
Real examples of fraud vectors across the 8 program integrity lifecycle stages
A staffing company enrolls 12 "nurses" in state Medicaid with licenses obtained from diploma mills. Cross-referencing with state licensing board databases reveals no valid credentials. 47 false claims submitted over 6 months = $340K in fraud prevented.
A physician with felony conviction continues billing through corporate entity after debarment. Network matching against OIG exclusion lists reveals the relationship. $128K in claims blocked before payment. Regulatory referral submitted to CMS.
Cross-state data correlation identifies beneficiary enrolled in three states simultaneously. Sentinel flags utilization pattern anomalies (same provider visits in different states on same days). $89K in improper payments recovered across two states.
Beneficiary claims unemployed status but IRS W-2 data shows income above threshold. Six-month income review identifies $42K in improper benefits paid. Case referred to state fraud investigator for criminal referral.
Home health provider bills for 8-hour visits every day for 90 days for patient documented to have been hospitalized for 75 of those days. Pattern analysis flags impossibilities. $267K in fraudulent claims denied. Provider agreement terminated.
Therapy provider systematically upcodes simple PT to complex PT, increasing reimbursement by $400+ per claim. 1,200 claims over 12 months. Medical necessity review disputes 89%. $428K recovery identified.
System glitch causes same claim to be paid twice by MCO. Sentinel's payment reconciliation catches the duplicate before discovery by audit. $340K claim recovered within 30 days of payment.
Medical equipment supplier's claims are paid at 120% of contracted fee schedule rate across 18 months. Statistical analysis reveals systematic overpayment. $156K recouped through claims adjustment process.
The financial case for Sentinel deployment
Annual Program Spend
$24B
Improper Payment Rate
4.2%
Annual Improper Payments
$1.01B
Sentinel Annual Cost
$425K
Conservative Estimate (15% fraud reduction)
$151.5M Recovered
Aggressive Estimate (22% fraud reduction)
$222.2M Recovered
Conservative: $151.5M recovered ÷ $425K invested = 356x ROI
Aggressive: $222.2M recovered ÷ $425K invested = 523x ROI
Payback period: 1-2 days of fraud prevention. Annual net savings: $151-$222M after Sentinel costs.
This model is based on conservative fraud reduction estimates from early-stage deployments. Actual results vary by state, program maturity, and data quality. Contact David Thorne to model ROI for your specific agency or program portfolio.
Sentinel deployment metrics and KPIs
State agencies nationwide are using Sentinel to detect fraud in real-time, identify recovery opportunities, and meet legislative oversight requirements. The ROI is immediate. The implementation is fast. The results speak for themselves. Schedule a conversation with David to discuss your state's program integrity goals.
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