1 / 25

Refinements to the CMS-HCC Model For Risk Adjustment of Medicare Capitation Payments

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.

desma
Download Presentation

Refinements to the CMS-HCC Model For Risk Adjustment of Medicare Capitation Payments

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 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.

  2. 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)

  3. 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

  4. 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

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

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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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)

  16. 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”

  17. 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

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

  19. 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)

  20. Distribution of Annualized Medicare Expenditures, 2003 5% Community100% 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

  21. 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

  22. 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

  23. Refined CMS-HCC Model Performance – I • Predictive ratios, prior year expenditure quintiles Age/SexCMS-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

  24. Refined CMS-HCC Model Performance – II • Predicted ratios by CMS-HCC predicted expenditure deciles Age/SexCMS-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

  25. 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

More Related