Literature DB >> 26420555

Overpaying morbidity adjusters in risk equalization models.

R C van Kleef1, R C J A van Vliet2, W P M M van de Ven2.   

Abstract

Most competitive social health insurance markets include risk equalization to compensate insurers for predictable variation in healthcare expenses. Empirical literature shows that even the most sophisticated risk equalization models-with advanced morbidity adjusters-substantially undercompensate insurers for selected groups of high-risk individuals. In the presence of premium regulation, these undercompensations confront consumers and insurers with incentives for risk selection. An important reason for the undercompensations is that not all information with predictive value regarding healthcare expenses is appropriate for use as a morbidity adjuster. To reduce incentives for selection regarding specific groups we propose overpaying morbidity adjusters that are already included in the risk equalization model. This paper illustrates the idea of overpaying by merging data on morbidity adjusters and healthcare expenses with health survey information, and derives three preconditions for meaningful application. Given these preconditions, we think overpaying may be particularly useful for pharmacy-based cost groups.

Keywords:  Health insurance; Overpaying; Risk equalization; Risk selection

Mesh:

Year:  2015        PMID: 26420555     DOI: 10.1007/s10198-015-0729-2

Source DB:  PubMed          Journal:  Eur J Health Econ        ISSN: 1618-7598


  23 in total

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Authors:  L M Lamers; R C J A Vliet
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Authors:  Randall P Ellis; Thomas G McGuire
Journal:  J Health Econ       Date:  2006-08-14       Impact factor: 3.883

4.  Optimal risk adjustment with adverse selection and spatial competition.

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5.  Measuring population health risks using inpatient diagnoses and outpatient pharmacy data.

Authors:  Y Zhao; R P Ellis; A S Ash; D Calabrese; J Z Ayanian; J P Slaughter; L Weyuker; B Bowen
Journal:  Health Serv Res       Date:  2001-12       Impact factor: 3.402

6.  Principal inpatient diagnostic cost group model for Medicare risk adjustment.

Authors:  G C Pope; R P Ellis; A S Ash; C F Liu; J Z Ayanian; D W Bates; H Burstin; L I Iezzoni; M J Ingber
Journal:  Health Care Financ Rev       Date:  2000

7.  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

8.  Diagnostic risk adjustment for Medicaid: the disability payment system.

Authors:  R Kronick; T Dreyfus; L Lee; Z Zhou
Journal:  Health Care Financ Rev       Date:  1996

9.  Diagnosis-based risk adjustment for Medicare capitation payments.

Authors:  R P Ellis; G C Pope; L Iezzoni; J Z Ayanian; D W Bates; H Burstin; A S Ash
Journal:  Health Care Financ Rev       Date:  1996
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  3 in total

1.  Deriving risk adjustment payment weights to maximize efficiency of health insurance markets.

Authors:  Timothy J Layton; Thomas G McGuire; Richard C van Kleef
Journal:  J Health Econ       Date:  2018-07-23       Impact factor: 3.883

2.  Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

Authors:  Frank Eijkenaar; René C J A van Vliet; Richard C van Kleef
Journal:  Health Serv Res       Date:  2018-10-16       Impact factor: 3.402

3.  Improving risk equalization with constrained regression.

Authors:  Richard C van Kleef; Thomas G McGuire; René C J A van Vliet; Wynand P P M van de Ven
Journal:  Eur J Health Econ       Date:  2016-12-10
  3 in total

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