Refinements to the CMS-HCC Model For Risk Adjustment of Medicare Capitation Payments Presented by: John Kautter, Ph.D. Gregory Pope, M.S. Eric Olmsted, Ph.D. RTI International Contact: John Kautter, PhD, jkautter@rti.org RTI International is a trade name of Research Triangle Institute.

History of Medicare Risk Adjustment Demographics (AAPCC) Doesn’t explain cost variation Favorable selection => higher program costs Principal inpatient diagnoses (PIP-DCG model, 2000) Incentive to admit Penalizes plans that avoid admissions Inpatient and ambulatory diagnoses (2004)

CMS-HCC Model Centers for Medicare & Medicaid Services (CMS) Hierarchical Condition Categories (HCC) model Prospective Inpatient and outpatient diagnoses w/o distinction 70 diagnostic categories (HCCs) Hierarchical within diseases

CMS-HCC Model (continued) Cumulative (additive) across diseases 6 disease interactions Discretionary diagnoses are excluded Demographic factors included Calibrated on 1999/2000 Medicare 5% Sample

CMS-HCC Model Performance Percentage of cost variation explained Age/Sex: 0.8% PIP-DCG: 5.5% CMS-HCC: 10.0%

CMS-HCC Models for Medicare Subpopulations Disabled End-stage renal disease Institutionalized New enrollees Secondary payer status Frail elderly

Disabled Over 10% of Medicare population Under age 65 Model estimated separately for aged and disabled Overall cost patterns similar For 5 diagnostic categories, incremental expense of the disabled is higher 5 disease interactions for disabled in final CMS-HCC model

End-Stage Renal Disease About 1% of Medicare population Very expensive: approximately $50,000/year 3-segment model Dialysis patients CMS-HCC model calibrated on dialysis patients Transplant period (3 months) Lump-sum payment Post-transplant period Aged/disabled CMS-HCC model w/add-on for drugs

Institutionalized Beneficiaries About 5% of Medicare population Costly, but less expensive than community residents for same diagnostic profile Combined CMS-HCC model Overpredicts costs for institutionalized Underpredicts costs for community frail elderly

Institutionalized Beneficiaries (continued) Different cost patterns by age and diagnosis for community and institutionalized CMS-HCC model calibrated separately on community and institutionalized Current year institutional status reported by nursing homes

New Enrollees Lack 12 months of base year enrollment Two-thirds are 65 year olds New enrollees versus continuing enrollees Much less costly at age 65 Similar costs at other ages Merged new/continuing enrollee sample Separate cost weights for 65 year olds Demographic model

Medicare as Secondary Payer Beneficiaries with active employee employer-sponsored insurance Costs are lower Multiplier scales cost predictions down Multiplier is ratio of mean actual to mean predicted expenditures

Frail Elderly Diagnosis-based models underpredict expenditures for the functionally impaired Medicare specialty plans (e.g., PACE) serve functionally-impaired populations Frailty adjuster to better predict their costs Predicts costs unexplained by CMS-HCC Based on difficulties in ADLs ADLs collected from surveys or assessments

CMS-HCC Model Refinements Additional HCCs added to model 100% institutional sample used for institutional model calibration Changes in diagnostic classification 2002/2003 Medicare FFS data used for calibration of all models

Availability of Additional HCCs For Part D risk adjuster, plans required to submit diagnoses for 127 HCCs Additional 57 HCCs available for CMS-HCC models (127 – 70 = 57)

Adding HCCs Benefits Greater accuracy in predicting illness burden Rewards plans who enroll and treat beneficiaries with these diagnoses E.g., Special Needs Plans (SNPs) Drawbacks Creates greater opportunities for diagnostic “upcoding”

HCCs Added to CMS-HCC Model Available additional HCCs reviewed by project team to determine which were appropriate for payment model Number of HCCs increased from 70 to 101

Examples of HCCs Added to CMS-HCC Model “Refined” CMS-HCC Model HCC Community Institutional Type I Diabetes Mellitus $1,557 $1,435 Dementia/ Cerebral Degeneration $1,576 − − Hypertension $388 $919

100% Institutional Sample CMS-HCC institutional model calibrated on 5% institutional sample (n = 65,593) To increase statistical accuracy and stability, “refined” CMS-HCC institutional model calibrated on 100% institutional sample (n = 1,238,842)

Distribution of Annualized Medicare Expenditures, 2003 5% Community 100% Institutional Sample Size 1,380,978 1,238,842 Expenditures Mean $6,541 $11,252 95th Percentile $31,285 $47,390 90th Percentile $17,682 $31,553 Median $1,445 $3,028 10th Percentile $56 $538 5th Percentile $0 $349

Changes in Diagnostic Classification Diabetes complications moved to diabetes hierarchy E.g., diabetic neuropathy moved from HCC 71 Polyneuropathy to HCC 16 Diabetes with Neurologic or Other Specified Manifestation HCC 119 Proliferative Diabetic Retinopathy and Vitreous Hemorrhage deleted and most moved to HCC 18 Diabetes with Ophthalmologic or Unspecified Manifestation Cerebral Palsy consolidated in HCC 70 Cerebral Palsy and Muscular Distrophy

Refined CMS-HCC Community and Institutional Models % of Cost Variation Explained # HCCs CMS-HCC Community 9.8% 70 Institutional 6.0% 69 “Refined” CMS-HCC Community 11.0% 101 Institutional 8.9% 90

Refined CMS-HCC Model Performance – I Predictive ratios, prior year expenditure quintiles Age/Sex CMS-HCC First 2.65 1.20 Second 1.82 1.19 Third 1.31 1.09 Fourth 0.91 0.99 Fifth 0.46 0.90

Refined CMS-HCC Model Performance – II Predicted ratios by CMS-HCC predicted expenditure deciles Age/Sex CMS-HCC First 2.84 0.88 Second 2.43 0.92 Third 2.10 0.94 Fourth 1.70 0.97 Fifth 1.49 0.97 Sixth 1.27 1.00 Seventh 1.06 1.01 Eighth 0.86 1.04 Ninth 0.64 1.04 Tenth 0.35 1.00

Conclusions Medicare risk adjustment has been evolving Demographic  Inpatient  All-Encounter (AAPCC) (PIP-DCG) (CMS-HCC) The “refined” CMS-HCC model represents a more comprehensive all-encounter risk adjustment model Increases payment accuracy for plans Viability of plans Beneficiaries’ access to plans