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Diagnosis-Based Risk Adjustment for Medicare Prescription Drug Plan Payments John Robst Melvin Ingber Jesse Levy Centers for Medicare & Medicaid Services.

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Presentation on theme: "Diagnosis-Based Risk Adjustment for Medicare Prescription Drug Plan Payments John Robst Melvin Ingber Jesse Levy Centers for Medicare & Medicaid Services."— Presentation transcript:

1 Diagnosis-Based Risk Adjustment for Medicare Prescription Drug Plan Payments John Robst Melvin Ingber Jesse Levy Centers for Medicare & Medicaid Services

2 The Drug Benefit – Part D Mandated by MMA; Starts in 2006 Covers self-administered prescription drugs not covered by Medicare Part B Beneficiaries may enroll in any one of the prescription drug plans (PDPs) or Medicare Advantage (MA)-PDPs in their region Formularies and prices are not standardized Premiums are set by bid and formula

3 The Drug Benefit – Part D Standard benefit, initial thresholds for beneficiary: –Monthly premium –(A) $250 deductible –(B) 25% coins. from $250 to $2250 total spending –(C) 100% coins. from $2250 to $5100 (out-of-pkt = $3600) –(D) above $5100, greater of (5% coins., $2 generic/preferred, $5 brand) Plan pays in (B) and (D); is paid capitated amount by Medicare for (B) and part of (D)

4 Bid to be Risk Adjusted Preferred approach by system implementers: Capitated payment = Bid * Risk factor * Geographic price index Bid - Average monthly cost incurred by plan under standard benefit for person with national average risk

5 Risk Adjustment Approach Build on underpinnings of prospective CMS-HCC model for Part A and B services –ICD-9 codes grouped into DxGs; DxGs grouped into HCCs –Expected spending = f (age/sex, HCC 1 … HCC n ) Hierarchies of severity ICD-9 codes needed go beyond the abbreviated set initially required for CMS-HCC model –Conditions with low inpatient/ambulatory costs may have significant drug costs – hypertension, high cholesterol….

6 Data Existing estimation data are far from perfect – inadequate Medicare prescription drug data Data for predictors must be available for FFS and managed care (MA) beneficiaries: demographics and diagnoses Due to the lack of data, we can’t include prior drug use in the model

7 Data Federal retirees with Medicare in the Blue Cross - Blue Shield FEHBP –~ 1 million persons, 3 years (2000-2002) –Link to Medicare diagnosis files –No disabled under 65 –Reasonable national representation after reweighting –No cap, 25% coinsurance for retail, copays for mail order ($35 brand, $10 generic) –Total enrollee and plan spending for each person

8 Estimation Linear additive model Model should have clinical credibility –Individual DxGs are grouped clinically –Hierarchies imposed –Models for total drug costs have R 2 of about.25 –Age/sex coefficients exceed deductible even in very comprehensive model CMS announced new data requirements in May 2004 –Codes required were published based on preliminary models

9 Other Data and Adjustments to Spending Other data: 5 percent Medicaid-Medicare dual eligible sample from 1999/2000 Policy makers required a low income subsidy and an institutionalized subsidy in payments Start everyone on same basis – i.e., BCBS with standard benefit - Adjust Medicaid expenditures downward - Adjust everyone downward

10 Model estimates - examples

11 Predictive Ratios

12

13 Subsidies

14 Geographic Price Adjuster MMA: Test for geographic price variation; adjust if needed 34 geographic regions Data sources –IMS, Verispan, BCBS –Variation in drug prices for third party payers –Indexes vary depending on method and market basket


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