Literature DB >> 11477956

Risk adjustment for measuring health outcomes: an application in VA long-term care.

A Rosen1, J Wu, B H Chang, D Berlowitz, C Rakovski, A Ash, M Moskowitz.   

Abstract

An empirically derived risk adjustment model is useful in distinguishing among facilities in their quality of care. We used Veterans Affairs (VA) administrative databases to develop and validate a risk adjustment model to predict decline in functional status, an important outcome measure in long-term care, among patients residing in VA long-term care facilities. This model was used to compare facilities on adjusted and unadjusted rates of decline. Predictors of decline included age, time between assessments, baseline functional status, terminal illness, pressure ulcers, pulmonary disease, cancer, arthritis, congestive heart failure, substance-related disorders, and various neurologic disorders. The model performed well in the development and validation databases (c statistics, 0.70 and 0.68, respectively). Risk-adjusted rates and rankings of facilities differed from unadjusted ratings. We conclude that judgments of facility performance depend on whether risk-adjusted or unadjusted decline rates are used. Valid risk adjustment models are therefore necessary when comparing facilities on outcomes.

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Year:  2001        PMID: 11477956     DOI: 10.1177/106286060101600403

Source DB:  PubMed          Journal:  Am J Med Qual        ISSN: 1062-8606            Impact factor:   1.852


  10 in total

1.  National release of the nursing home quality report cards: implications of statistical methodology for risk adjustment.

Authors:  Yue Li; Xueya Cai; Laurent G Glance; William D Spector; Dana B Mukamel
Journal:  Health Serv Res       Date:  2009-02       Impact factor: 3.402

2.  Does risk adjustment of the CMS quality measures for nursing homes matter?

Authors:  Dana B Mukamel; Laurent G Glance; Yue Li; David L Weimer; William D Spector; Jacqueline S Zinn; Laura Mosqueda
Journal:  Med Care       Date:  2008-05       Impact factor: 2.983

3.  Validation of a Claims-Based Frailty Index Against Physical Performance and Adverse Health Outcomes in the Health and Retirement Study.

Authors:  Dae Hyun Kim; Robert J Glynn; Jerry Avorn; Lewis A Lipsitz; Kenneth Rockwood; Ajinkya Pawar; Sebastian Schneeweiss
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-07-12       Impact factor: 6.053

4.  Identifying the Population with Serious Illness: The "Denominator" Challenge.

Authors:  Amy S Kelley; Evan Bollens-Lund
Journal:  J Palliat Med       Date:  2017-11-10       Impact factor: 2.947

5.  Measuring Frailty in Medicare Data: Development and Validation of a Claims-Based Frailty Index.

Authors:  Dae Hyun Kim; Sebastian Schneeweiss; Robert J Glynn; Lewis A Lipsitz; Kenneth Rockwood; Jerry Avorn
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2018-06-14       Impact factor: 6.053

6.  Comparing Survey-Based Frailty Assessment to Medicare Claims in Predicting Health Outcomes and Utilization in Medicare Beneficiaries.

Authors:  Shannon Wu; John Mulcahy; Judith D Kasper; Hong J Kan; Jonathan P Weiner
Journal:  J Aging Health       Date:  2019-05-31

Review 7.  Measuring frailty using claims data for pharmacoepidemiologic studies of mortality in older adults: evidence and recommendations.

Authors:  Dae Hyun Kim; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2014-06-24       Impact factor: 2.890

8.  Publication of quality report cards and trends in reported quality measures in nursing homes.

Authors:  Dana B Mukamel; David L Weimer; William D Spector; Heather Ladd; Jacqueline S Zinn
Journal:  Health Serv Res       Date:  2008-01-31       Impact factor: 3.402

9.  Performance evaluation of medical service for breast cancer patients based on diagnosis related groups.

Authors:  Xinkui Liu; Furong Liu; Lin Wang; MengFan Wu; LinPeng Yang; Le Wei
Journal:  BMC Health Serv Res       Date:  2021-05-24       Impact factor: 2.655

10.  The DEMATEL method explores the interdependent relationship structure and weights for diagnosis-related groups system.

Authors:  Tong Zou; Yanjun Jin; Yen-Ching Chuang; Ching-Wen Chien; Tao-Hsin Tung
Journal:  Front Public Health       Date:  2022-08-04
  10 in total

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