Literature DB >> 10366176

Definition of race and ethnicity in older people in Medicare and Medicaid.

C X Pan1, R J Glynn, H Mogun, I Choodnovskiy, J Avorn.   

Abstract

BACKGROUND: Race and ethnicity are important predictors of health care access and outcomes, but quality of their documentation in the healthcare system is often problematic.
OBJECTIVES: To study the agreement between Medicare and Medicaid descriptions of race and ethnicity in older beneficiaries.
DESIGN: Quasiexperimental design in a natural practice setting.
SETTING: New Jersey. PARTICIPANTS: 153,241 dually enrolled participants in Medicare and Medicaid. MEASUREMENTS: Agreement rates between administrative databases on recipients' race and ethnicity.
RESULTS: Agreement between Medicare and Medicaid on the recipients' race and ethnicity was modest (kappa = .58; 95% CI, .57-.58) for men and women alike and across different age groups. Depending on whether Medicare or Medicaid was used as the reference standard, the relative agreement rates for race and ethnic group assignments varied. For example, using Medicare as the reference, the relative agreement rate was 84% for whites, 74% for blacks, 61% for others, 23% for Hispanics, and only 5% for Asians. Using Medicaid as the reference, a different pattern emerged. However, such gradients of agreement rates across racial groups were observed in both programs. Medicare and Medicaid reported different percentages of all race and ethnicity groups, with Medicaid reporting greater proportions of White and Black beneficiaries, and Medicare reporting greater proportions of Hispanic, Asian, and Other groups.
CONCLUSIONS: Depiction of race and ethnicity data in large government health insurance programs is approximate at best and often contradictory from one program to another. This can impede efforts to study the relationship between these important characteristics and health care utilization and outcomes.

Entities:  

Mesh:

Year:  1999        PMID: 10366176     DOI: 10.1111/j.1532-5415.1999.tb01599.x

Source DB:  PubMed          Journal:  J Am Geriatr Soc        ISSN: 0002-8614            Impact factor:   5.562


  16 in total

1.  Methods for using Medicare data to compare procedure rates among Asians, blacks, Hispanics, Native Americans, and whites.

Authors:  José J Escarce; Thomas G McGuire
Journal:  Health Serv Res       Date:  2003-10       Impact factor: 3.402

2.  A system for rapidly and accurately collecting patients' race and ethnicity.

Authors:  David W Baker; Kenzie A Cameron; Joseph Feinglass; Jason A Thompson; Patricia Georgas; Shawn Foster; Deborah Pierce; Romana Hasnain-Wynia
Journal:  Am J Public Health       Date:  2006-01-31       Impact factor: 9.308

3.  Performance of the U.S. Office of Management and Budget's Revised Race and Ethnicity Categories in Asian Populations*

Authors:  Joan L Holup; Nancy Press; William M Vollmer; Emily L Harris; Thomas M Vogt; Chuhe Chen
Journal:  Int J Intercult Relat       Date:  2007-09

4.  Standardized data collection practices and the racial/ethnic distribution of hospitalized patients.

Authors:  Rosette J Chakkalakal; Jeremy C Green; Harlan M Krumholz; Brahmajee K Nallamothu
Journal:  Med Care       Date:  2015-08       Impact factor: 2.983

5.  Does race predict stroke readmission? An analysis using the truncated negative binomial model.

Authors:  Byron S Kennedy
Journal:  J Natl Med Assoc       Date:  2005-05       Impact factor: 1.798

6.  Agreement between self-reported and administrative race and ethnicity data among Medicaid enrollees in Minnesota.

Authors:  Donna D McAlpine; Timothy J Beebe; Michael Davern; Kathleen T Call
Journal:  Health Serv Res       Date:  2007-12       Impact factor: 3.402

7.  Hospitalization Rates for Acute Myocardial Infarction Among Asian-American Subgroups: Have We Been Underestimating the Problem?

Authors:  Rosette J Chakkalakal; Justin P Fox; Jeremy C Green; Marcella Nunez-Smith; Brahmajee K Nallamothu; Romana Hasnain-Wynia
Journal:  J Immigr Minor Health       Date:  2018-02

8.  Estimation of ancestry using dental morphological characteristics.

Authors:  Heather J H Edgar
Journal:  J Forensic Sci       Date:  2012-10-15       Impact factor: 1.832

9.  Angiotensin-converting enzyme inhibitor, angiotensin receptor blocker use, and mortality in patients with chronic kidney disease.

Authors:  Miklos Z Molnar; Kamyar Kalantar-Zadeh; Evan H Lott; Jun Ling Lu; Sandra M Malakauskas; Jennie Z Ma; Darryl L Quarles; Csaba P Kovesdy
Journal:  J Am Coll Cardiol       Date:  2013-11-21       Impact factor: 24.094

10.  Elective and isolated carotid endarterectomy: health disparities in utilization and outcomes, but not readmission.

Authors:  Byron S Kennedy; Stephen P Fortmann; Randall S Stafford
Journal:  J Natl Med Assoc       Date:  2007-05       Impact factor: 1.798

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.