Literature DB >> 21110252

Use of Medicare and DOD data for improving VA race data quality.

Kevin T Stroupe1, Elizabeth Tarlov, Qiuying Zhang, Thomas Haywood, Arika Owens, Denise M Hynes.   

Abstract

We evaluated the improvement in Department of Veterans Affairs (VA) race data completeness that could be achieved by linking VA data with data from Medicare and the Department of Defense (DOD) and examined agreement in values across the data sources. After linking VA with Medicare and DOD records for a 10% sample of VA patients, we calculated the percentage for which race could be identified in those sources. To evaluate race agreement, we calculated sensitivities, specificities, positive predictive values (PPVs), negative predictive values, and kappa statistics. Adding Medicare (and DOD) data improved race data completeness from 48% to 76%. Among older patients (≥65 years), adding Medicare data improved data completeness to nearly 100%. Among younger patients (<65 years), combining Medicare and DOD data improved completeness to 75%, 18 percentage points beyond that achieved with Medicare data alone. PPVs for white and African-American categories were 98.6 and 94.7, respectively, in Medicare and 97.0 and 96.5, respectively, in DOD data using VA self-reported race as the gold standard. PPVs for the non-African-American minority groups were lower, ranging from 30.5 to 48.2. Kappa statistics reflected these patterns. Supplementing VA with Medicare and DOD data improves VA race data completeness substantially. More study is needed to understand poor rates of agreement between VA and external sources in identifying non-African-American minority individuals.

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Mesh:

Year:  2010        PMID: 21110252     DOI: 10.1682/jrrd.2009.08.0122

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  20 in total

1.  Trends in anemia management in lung and colon cancer patients in the US Department of Veterans Affairs, 2002-2008.

Authors:  Elizabeth Tarlov; Kevin T Stroupe; Todd A Lee; Thomas W Weichle; Qiuying L Zhang; Laura C Michaelis; Howard Ozer; Margaret M Browning; Denise M Hynes
Journal:  Support Care Cancer       Date:  2011-09-20       Impact factor: 3.603

Review 2.  Race/Ethnicity and overuse of care: a systematic review.

Authors:  Nancy R Kressin; Peter W Groeneveld
Journal:  Milbank Q       Date:  2015-03       Impact factor: 4.911

3.  Racial Differences in Association of Serum Calcium with Mortality and Incident Cardio- and Cerebrovascular Events.

Authors:  Jun Ling Lu; Miklos Z Molnar; Jennie Z Ma; Lekha K George; Keiichi Sumida; Kamyar Kalantar-Zadeh; Csaba P Kovesdy
Journal:  J Clin Endocrinol Metab       Date:  2016-09-15       Impact factor: 5.958

4.  Age and Outcomes Associated with BP in Patients with Incident CKD.

Authors:  Csaba P Kovesdy; Ahmed Alrifai; Elvira O Gosmanova; Jun Ling Lu; Robert B Canada; Barry M Wall; Adriana M Hung; Miklos Z Molnar; Kamyar Kalantar-Zadeh
Journal:  Clin J Am Soc Nephrol       Date:  2016-04-21       Impact factor: 8.237

5.  Impact of a Pay-for-Performance Program on Care for Black Patients with Hypertension: Important Answers in the Era of the Affordable Care Act.

Authors:  Laura A Petersen; Kate Simpson Ramos; Kenneth Pietz; LeChauncy D Woodard
Journal:  Health Serv Res       Date:  2016-06-22       Impact factor: 3.402

6.  Thyroid Status and Death Risk in US Veterans With Chronic Kidney Disease.

Authors:  Connie M Rhee; Kamyar Kalantar-Zadeh; Vanessa Ravel; Elani Streja; Amy S You; Steven M Brunelli; Danh V Nguyen; Gregory A Brent; Csaba P Kovesdy
Journal:  Mayo Clin Proc       Date:  2018-05       Impact factor: 7.616

7.  Geographic Accessibility Of Food Outlets Not Associated With Body Mass Index Change Among Veterans, 2009-14.

Authors:  Shannon N Zenk; Elizabeth Tarlov; Coady Wing; Stephen A Matthews; Kelly Jones; Hao Tong; Lisa M Powell
Journal:  Health Aff (Millwood)       Date:  2017-08-01       Impact factor: 6.301

8.  Probability of an abnormal screening prostate-specific antigen result based on age, race, and prostate-specific antigen threshold.

Authors:  Roxanne Espaldon; Katharine A Kirby; Kathy Z Fung; Richard M Hoffman; Adam A Powell; Stephen J Freedland; Louise C Walter
Journal:  Urology       Date:  2014-01-16       Impact factor: 2.649

9.  Predicting 30-day all-cause hospital readmissions.

Authors:  Mollie Shulan; Kelly Gao; Crystal Dea Moore
Journal:  Health Care Manag Sci       Date:  2013-01-27

10.  Association of Systolic Blood Pressure Variability With Mortality, Coronary Heart Disease, Stroke, and Renal Disease.

Authors:  Elvira O Gosmanova; Margit K Mikkelsen; Miklos Z Molnar; Jun L Lu; Lenar T Yessayan; Kamyar Kalantar-Zadeh; Csaba P Kovesdy
Journal:  J Am Coll Cardiol       Date:  2016-09-27       Impact factor: 24.094

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