Literature DB >> 29790162

Getting What We Pay For: How Do Risk-Based Payments to Medicare Advantage Plans Compare with Alternative Measures of Beneficiary Health Risk?

Paul D Jacobs1, Richard Kronick2.   

Abstract

OBJECTIVE: To estimate the relative health risk of Medicare Advantage (MA) beneficiaries compared to those in Traditional Medicare (TM). DATA SOURCES/STUDY
SETTING: Medicare claims and enrollment records for the sample of beneficiaries enrolled in Part D between 2008 and 2015. STUDY
DESIGN: We assigned therapeutic classes to Medicare beneficiaries based on their prescription drug utilization. We then regressed nondrug health spending for TM beneficiaries in 2015 on demographic and therapeutic class identifiers for 2014 and used coefficients from this regression to predict relative risk of both MA and TM beneficiaries. PRINCIPAL
FINDINGS: Based on prescription drug utilization data, beneficiaries enrolled in MA in 2015 had 6.9 percent lower health risk than beneficiaries in TM, but differences based on coded diagnoses suggested MA beneficiaries were 6.2 percent higher risk. The relative health risk based on drug usage of MA beneficiaries compared to those in TM increased by 3.4 p.p. from 2008 to 2015, while the relative risk using diagnoses increased 9.8 p.p.
CONCLUSIONS: Our results add to a growing body of evidence suggesting MA receives favorable, or, at worst, neutral selection. If MA beneficiaries are no healthier and no sicker than similar beneficiaries in TM, then payments to MA plans exceed what is warranted based on their health status. © Health Research and Educational Trust.

Keywords:  Medicare advantage; coding intensity; risk adjustment

Mesh:

Substances:

Year:  2018        PMID: 29790162      PMCID: PMC6232441          DOI: 10.1111/1475-6773.12977

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  12 in total

1.  Longitudinal Patterns of Spending Enhance the Ability to Predict Costly Patients: A Novel Approach to Identify Patients for Cost Containment.

Authors:  Julie C Lauffenburger; Jessica M Franklin; Alexis A Krumme; William H Shrank; Troyen A Brennan; Olga S Matlin; Claire M Spettell; Gregory Brill; Niteesh K Choudhry
Journal:  Med Care       Date:  2017-01       Impact factor: 2.983

2.  Projected Coding Intensity In Medicare Advantage Could Increase Medicare Spending By $200 Billion Over Ten Years.

Authors:  Richard Kronick
Journal:  Health Aff (Millwood)       Date:  2017-02-01       Impact factor: 6.301

3.  Favorable selection, risk adjustment, and the Medicare Advantage program.

Authors:  Michael A Morrisey; Meredith L Kilgore; David J Becker; Wilson Smith; Elizabeth Delzell
Journal:  Health Serv Res       Date:  2012-10-22       Impact factor: 3.402

4.  Measuring coding intensity in the Medicare Advantage program.

Authors:  Richard Kronick; W Pete Welch
Journal:  Medicare Medicaid Res Rev       Date:  2014-07-17

5.  Medicare Prescription Drug Plan Enrollees Report Less Positive Experiences Than Their Medicare Advantage Counterparts.

Authors:  Marc N Elliott; Bruce E Landon; Alan M Zaslavsky; Carol Edwards; Nathan Orr; Megan K Beckett; Joshua Mallett; Paul D Cleary
Journal:  Health Aff (Millwood)       Date:  2016-03       Impact factor: 6.301

6.  Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan.

Authors:  Raymond Nc Kuo; Mei-Shu Lai
Journal:  BMC Health Serv Res       Date:  2010-05-17       Impact factor: 2.655

7.  Analysis Of Medicare Advantage HMOs compared with traditional Medicare shows lower use of many services during 2003-09.

Authors:  Bruce E Landon; Alan M Zaslavsky; Robert C Saunders; L Gregory Pawlson; Joseph P Newhouse; John Z Ayanian
Journal:  Health Aff (Millwood)       Date:  2012-12       Impact factor: 6.301

8.  New risk-adjustment system was associated with reduced favorable selection in medicare advantage.

Authors:  J Michael McWilliams; John Hsu; Joseph P Newhouse
Journal:  Health Aff (Millwood)       Date:  2012-12       Impact factor: 6.301

9.  Steps to reduce favorable risk selection in medicare advantage largely succeeded, boding well for health insurance exchanges.

Authors:  Joseph P Newhouse; Mary Price; Jie Huang; J Michael McWilliams; John Hsu
Journal:  Health Aff (Millwood)       Date:  2012-12       Impact factor: 6.301

10.  Risk adjustment of Medicare capitation payments using the CMS-HCC model.

Authors:  Gregory C Pope; John Kautter; Randall P Ellis; Arlene S Ash; John Z Ayanian; Lisa I Lezzoni; Melvin J Ingber; Jesse M Levy; John Robst
Journal:  Health Care Financ Rev       Date:  2004
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  5 in total

1.  Likelihood of hospital readmission in Medicare Advantage and Fee-For-Service within same hospital.

Authors:  Daniel H Jung; Eva DuGoff; Maureen Smith; Mari Palta; Andrea Gilmore-Bykovskyi; John Mullahy
Journal:  Health Serv Res       Date:  2020-07-01       Impact factor: 3.402

2.  Association of Race and Ethnicity and Medicare Program Type With Ambulatory Care Access and Quality Measures.

Authors:  Kenton J Johnston; Gmerice Hammond; David J Meyers; Karen E Joynt Maddox
Journal:  JAMA       Date:  2021-08-17       Impact factor: 157.335

3.  Improving the Performance of Risk Adjustment Systems: Constrained Regressions, Reinsurance, and Variable Selection.

Authors:  Thomas G McGuire; Anna L Zink; Sherri Rose
Journal:  Am J Health Econ       Date:  2021-10-04

4.  The effects of coding intensity in Medicare Advantage on plan benefits and finances.

Authors:  Paul D Jacobs; Richard Kronick
Journal:  Health Serv Res       Date:  2020-11-09       Impact factor: 3.402

Review 5.  Medicare Advantage Chart Reviews Are Associated With Billions in Additional Payments for Some Plans.

Authors:  David J Meyers; Amal N Trivedi
Journal:  Med Care       Date:  2021-02-01       Impact factor: 3.178

  5 in total

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