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Risk Adjustment in Medicare Part D Prescription Drug Benefit Open Door Forum December 2004 Risk Adjuster Basics • Capitated payment is adjusted according to the expected cost of the enrollee. • Expected cost is derived from enrollee characteristics: ° Enrollees may be sorted, by their characteristics, into cells that have assigned risk factors, or ° Characteristics may be assigned risk factors that are added to produce a total risk factor • In Part D the basic payment formula is: Payment = standardized bid enrollee’s risk factor – plan’s enrollee premium Risk Adjuster Structure • The CMS risk adjuster produces a personspecific risk factor by summing the factors associated with characteristics such as: ° Age/sex, e.g., male 70-74, female 70-74 …. ° Originally disabled status, e.g., male 65+ who entered Medicare < 65 because of disability ° Presence of medical conditions, e.g., cancers, diabetes, liver disorders, ischemic heart diseases, heart failure, psychiatric disorders … Risk Adjuster Structure • The risk model is prospective: the medical conditions from a given year are used to predict expenditures in the next year. • The disease groupings are clusters of related ICD9-CM diagnosis codes. • Diagnoses from hospital inpatient, hospital outpatient, and clinician sources are used. • The disease groups are derived from the CMSHCC risk model used in the Medicare Advantage program today, but have been modified to reflect drug spending as opposed to spending on A/B services. Risk Adjuster Structure • The risk factors for disease groups are additive when the diseases are not closely related: ° inflammatory bowel disease, AMI, schizophrenia • The groups may be in hierarchies when related and their costs have a logical ranking: ° Diabetes with complications, diabetes without complications ° Only the highest coded group in a hierarchy counts for payment. Risk Adjuster Structure Additive model: factors for demographic characteristics + factors for diagnoses Demographics One of : Female age 0-34 … Female age 95+, Male age 0-34 … Male age 95+ Plus factor if aged enrollee had once been eligible for Medicare based on disability Male, Orig. disab. Female Orig. disab. Diagnoses if present + HIV/AIDS + Opportunistic Infections + one of: Diabetes w. complications Diabetes w/o complication + Congestive Heart Failure + …. Risk Adjuster Development • Principal data source: Drug claims for Federal retirees in FEHB Blue Cross Blue Shield Service Benefit Plan + Medicaid sample • Diagnoses from linked Medicare files ° Diagnoses from 2001 to predict costs in 2002 and similarly from 2000 to predict 2001 • Decedents in cost years were included till death. • A linear regression model was estimated ° Dependent variable – total spending on prescription drugs, annualized, mix of retail and mail order ° Explanatory variables – the array of person characteristics - age/sex, diseases ° Estimated coefficients are the incremental costs of each condition or demographic characteristic. Risk Adjuster Development • In an iterative process, the disease groups were disassembled into smaller subgroups, and reassembled to allow empirical estimation of costs and clinical judgment to weigh in the development. • The explanatory power of the model is on a par with other drug models reported (R2=.23 for spending) and is higher than similar models for Parts A and B. Risk Adjuster – rough example 1 for 2006 Coded Characteristic Female, age 76 Diabetes, w. complications Diabetes, uncomplicated High cholesterol Congestive Heart Failure Osteoporosis Total Annual Pred. Spending Spending Model Spending Relative Increment Factor $ 850 .283 1,600 .533 1,000 .333 450 .150 650 .217 500 .167 $4,050 1.350 For implementation, dollar amounts are divided by the national mean (~ $3,000) to create relative factors that multiply base rates. Risk Adjuster for Plan Liability • Plans are not liable for the total spending. Standard benefit liability is 75% of spending from $250 to $2250, about 15% above $5100, and 0% elsewhere. • The structure developed for modeling spending has been re-estimated on the same data set, with the standard benefit structure applied to each enrollee’s spending. • This is the Plan Liability model. (R2=.25) • The average projected 2006 spending in the data is about $3,000; the average plan liability from the data is about $1,100. Risk Adjuster – rough example 2 for 2006 Coded Characteristic Female, age 76 Diabetes, w. complications Diabetes, uncomplicated High cholesterol Congestive Heart Failure Osteoporosis Total Annual Pred. Spending Liability Model Payment Relative Increment Factor $ 550 .500 300 .273 200 .182 150 .136 250 .227 150 .136 $1,400 1.272 For implementation, dollar amounts are divided by the national mean (~ $1,100) to create relative factors that multiply base rates. Risk Adjuster for Plan Liability • Tasks to be completed ° Development of New Enrollee model for people new to Medicare with insufficient data for risk adjustment. This model is based on demographics. ° Study of Medicaid population to investigate: • factors for under-65 disabled population • adjustments for institutional population • adjustments for low-income population Schedule • Late December ° Release of Bidders Data Set - 5% files of FFS beneficiaries with imputed drug utilization • Late January ° Posting of draft model coefficients and mappings of diagnoses to disease groups ° Release of drug risk factors for people in 5% files • Mid February ° 45-day notice for MA with PDP information • Late March ° Bid and Risk Adjustment training • April ° Release of final model, software and final risk factors for 5% file if different from draft