Literature DB >> 27140395

Guidelines for Measuring Disease Episodes: An Analysis of the Effects on the Components of Expenditure Growth.

Abe Dunn1, Eli Liebman2, Lindsey Rittmueller1, Adam Hale Shapiro3.   

Abstract

OBJECTIVE: To provide guidelines to researchers measuring health expenditures by disease and compare these methodologies' implied inflation estimates. DATA SOURCE: A convenience sample of commercially insured individuals over the 2003 to 2007 period from Truven Health. Population weights are applied, based on age, sex, and region, to make the sample of over 4 million enrollees representative of the entire commercially insured population. STUDY
DESIGN: Different methods are used to allocate medical-care expenditures to distinct condition categories. We compare the estimates of disease-price inflation by method. PRINCIPAL
FINDINGS: Across a variety of methods, the compound annual growth rate stays within the range 3.1 to 3.9 percentage points. Disease-specific inflation measures are more sensitive to the selected methodology.
CONCLUSION: The selected allocation method impacts aggregate inflation rates, but considering the variety of methods applied, the differences appear small. Future research is necessary to better understand these differences in other population samples and to connect disease expenditures to measures of quality. © Health Research and Educational Trust.

Keywords:  Health care expenditures; disease episodes; measuring expenditures of treatment

Mesh:

Year:  2016        PMID: 27140395      PMCID: PMC5346493          DOI: 10.1111/1475-6773.12498

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


  13 in total

1.  Health care episodes: definition, measurement and use.

Authors:  M C Hornbrook; A V Hurtado; R E Johnson
Journal:  Med Care Rev       Date:  1985

2.  Use of econometric models to estimate expenditure shares.

Authors:  Justin G Trogdon; Eric A Finkelstein; Thomas J Hoerger
Journal:  Health Serv Res       Date:  2008-01-31       Impact factor: 3.402

3.  National health spending by medical condition, 1996-2005.

Authors:  Charles Roehrig; George Miller; Craig Lake; Jenny Bryant
Journal:  Health Aff (Millwood)       Date:  2009-02-24       Impact factor: 6.301

4.  Policy makers will need a way to update bundled payments that reflects highly skewed spending growth of various care episodes.

Authors:  Allison B Rosen; Ana Aizcorbe; Alexander J Ryu; Nicole Nestoriak; David M Cutler; Michael E Chernew
Journal:  Health Aff (Millwood)       Date:  2013-05       Impact factor: 6.301

5.  The growth in cost per case explains far more of US health spending increases than rising disease prevalence.

Authors:  Charles S Roehrig; David M Rousseau
Journal:  Health Aff (Millwood)       Date:  2011-09       Impact factor: 6.301

6.  Implications of utilization shifts on medical-care price measurement.

Authors:  Abe Dunn; Eli Liebman; Adam Hale Shapiro
Journal:  Health Econ       Date:  2014-03-04       Impact factor: 3.046

7.  Decomposing growth in spending finds annual cost of treatment contributed most to spending growth, 1980-2006.

Authors:  Martha Starr; Laura Dominiak; Ana Aizcorbe
Journal:  Health Aff (Millwood)       Date:  2014-05       Impact factor: 6.301

8.  Measuring health care costs of individuals with employer-sponsored health insurance in the U.S.: A comparison of survey and claims data.

Authors:  Ana Aizcorbe; Eli Liebman; Sarah Pack; David M Cutler; Michael E Chernew; Allison B Rosen
Journal:  Stat J IAOS       Date:  2012

Review 9.  Challenges in building disease-based national health accounts.

Authors:  Allison B Rosen; David M Cutler
Journal:  Med Care       Date:  2009-07       Impact factor: 2.983

10.  Need for risk adjustment in adapting episode grouping software to Medicare data.

Authors:  Thomas MaCurdy; Jason Kerwin; Nick Theobald
Journal:  Health Care Financ Rev       Date:  2009
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