Validity of Race and Ethnicity Codes in Medicare Administrative Data Compared With Gold-standard Self-reported Race Collected During Routine Home Health Care Visits. Issue 1 (January 2020)
- Record Type:
- Journal Article
- Title:
- Validity of Race and Ethnicity Codes in Medicare Administrative Data Compared With Gold-standard Self-reported Race Collected During Routine Home Health Care Visits. Issue 1 (January 2020)
- Main Title:
- Validity of Race and Ethnicity Codes in Medicare Administrative Data Compared With Gold-standard Self-reported Race Collected During Routine Home Health Care Visits
- Authors:
- Jarrín, Olga F.
Nyandege, Abner N.
Grafova, Irina B.
Dong, XinQi
Lin, Haiqun - Abstract:
- Abstract : Background: Misclassification of Medicare beneficiaries' race/ethnicity in administrative data sources is frequently overlooked and a limitation in health disparities research. Objective: To compare the validity of 2 race/ethnicity variables found in Medicare administrative data [enrollment database (EDB) and Research Triangle Institute (RTI) race] against a gold-standard source also available in the Medicare data warehouse: the self-reported race/ethnicity variable on the home health Outcome and Assessment Information Set (OASIS). Subjects: Medicare beneficiaries over the age of 18 who received home health care in 2015 (N=4, 243, 090). Measures: Percent agreement, sensitivity, specificity, positive predictive value, and Cohen κ coefficient. Results: The EDB and RTI race variable have high validity for black race and low validity for American Indian/Alaskan Native race. Although the RTI race variable has better validity than the EDB race variable for other races, κ values suggest room for future improvements in classification of whites (0.90), Hispanics (0.87), Asian/Pacific Islanders (0.77), and American Indian/Alaskan Natives (0.44). Discussion: The status quo of using "good-enough for government" race/ethnicity variables contained in Medicare administrative data for minority health disparities research can be improved through the use of self-reported race/ethnicity data, available in the Medicare data warehouse. Health services and policy researchers shouldAbstract : Background: Misclassification of Medicare beneficiaries' race/ethnicity in administrative data sources is frequently overlooked and a limitation in health disparities research. Objective: To compare the validity of 2 race/ethnicity variables found in Medicare administrative data [enrollment database (EDB) and Research Triangle Institute (RTI) race] against a gold-standard source also available in the Medicare data warehouse: the self-reported race/ethnicity variable on the home health Outcome and Assessment Information Set (OASIS). Subjects: Medicare beneficiaries over the age of 18 who received home health care in 2015 (N=4, 243, 090). Measures: Percent agreement, sensitivity, specificity, positive predictive value, and Cohen κ coefficient. Results: The EDB and RTI race variable have high validity for black race and low validity for American Indian/Alaskan Native race. Although the RTI race variable has better validity than the EDB race variable for other races, κ values suggest room for future improvements in classification of whites (0.90), Hispanics (0.87), Asian/Pacific Islanders (0.77), and American Indian/Alaskan Natives (0.44). Discussion: The status quo of using "good-enough for government" race/ethnicity variables contained in Medicare administrative data for minority health disparities research can be improved through the use of self-reported race/ethnicity data, available in the Medicare data warehouse. Health services and policy researchers should critically examine the source of race/ethnicity variables used in minority health and health disparities research. Future work to improve the accuracy of Medicare beneficiaries' race/ethnicity data should incorporate and augment the self-reported race/ethnicity data contained in assessment and survey data, available within the Medicare data warehouse. … (more)
- Is Part Of:
- Medical care. Volume 58:Issue 1(2020)
- Journal:
- Medical care
- Issue:
- Volume 58:Issue 1(2020)
- Issue Display:
- Volume 58, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 58
- Issue:
- 1
- Issue Sort Value:
- 2020-0058-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-01
- Subjects:
- race -- ethnicity -- misclassification -- Medicare data -- disparities research -- study design -- methods
Economics, Medical -- Periodicals
Insurance, Health -- Periodicals
Santé, Services de -- Administration -- Périodiques
Soins médicaux -- Périodiques
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Health insurance -- Periodicals
Medical economics -- United States -- Periodicals
Health insurance -- United States -- Periodicals
Comprehensive Health Care -- Periodicals
Personal Health Services -- Periodicals
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Économie de la santé -- Périodiques
Santé, Services de -- Périodiques
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Medical economics
United States
Periodicals
362.10973 - Journal URLs:
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http://www.jstor.org/journals/00257079.html ↗
http://www.lww-medicalcare.com ↗
http://www.jstor.org/journals/00257079.html ↗
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http://journals.lww.com ↗ - DOI:
- 10.1097/MLR.0000000000001216 ↗
- Languages:
- English
- ISSNs:
- 0025-7079
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