Agreement between administrative data and patients’ self-reports of race/ethnicity
Open accessAbstract
Objectives. We examined agreement of administrative data with self-reported race/ethnicity and identified correlates of agreement. Methods. We used Veterans Affairs administrative data and VA 1999 Large Health survey race/ethnicity data. Results. Relatively low rates of agreement (approximately 60%) between data sources were largely the result of administrative data from patients whose race/ethnicity was unknown, with least agreement for Native American, Asian, and Pacific Islander patients. After exclusion of patients with missing race/ethnicity, agreement improved except for Native Americans. Agreement did not increase substantially after inclusion of data from individuals indicating multiple race/ethnicities. Patients for whom there was better agreement between data sources tended to be less educated, non–solitary living, younger, and White; to have sufficient food; and to use more inpatient Department of Veterans Affairs (VA) care. Conclusions. Better reporting of race/ethnicity data will improve agreement between data sources. Previous studies using VA administrative data may have underestimated racial disparities.
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Several studies found that the plausibility of patient race/ethnicity information in their dataset was questionable because the data were incomplete; plausibility was low because a patient's race was reported correctly in one area but as 'other' in another.
“For example, several studies found that the plausibility of the patient race/ethnicity information in their dataset was questionable because the data were incomplete; in other words, plausibility was low because a patient’s race was reported correctly in one area, but as “other” in another.21,86,87”
From The quality of social determinants data in the electronic health record: a systematic review (2021) · cites this paper as [86]
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Straits-tröster, K., Kahwati, L., Kinsinger, L., Orelien, J., Burdick, M. B., & Yevich, S. J. (2006) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2006.07.018 · Cited by 55 · see citing works
Grundmeier, R. W., Song, L., Ramos, M. J., Fiks, A. G., Elliott, M. N., Fremont, A., Pace, W., Wasserman, R. C., & Localio, R. (2015) · Health Services Research · doi:10.1111/1475-6773.12295 · Cited by 55 · see citing works
“…2007; Fiks et al. 2012) but requires accurate racial/ethnic data, which are often completely or partially missing in EHR data (Bierman et al. 2002; Kressin et al. 2003; Hasnain-Wynia, Pierce, and Pittman 2004; Fremont et al. 2005; Bilheimer and Sisk 2008; Smith et al. 2010;Wynia, Ivey, and…”
BackgroundHow Administrative Data Collection and Analysis Can Better Reflect Racial and Ethnic Identities
Viano, S., & Baker, D. J. (2020) · Review of Research in Education · doi:10.3102/0091732x20903321 · Cited by 54 · see citing works
“For instance, Kressin et al. (2003) found that agreement rates were 60% for African American, Hispanic, and White but 15% for American Indians.”
BackgroundInfluentialHawkins, E. J., Malte, C. A., Imel, Z. E., Saxon, A. J., & Kivlahan, D. R. (2012) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.01.003 · Cited by 49 · see citing works
Hernandez, S., Sylling, P., Mor, M., Fine, M., Nelson, K. M., Wong, E., Liu, C.-F., Batten, A. J., Fihn, S., & Hebert, P. (2020) · Military Medicine · doi:10.1093/milmed/usz322 · Cited by 49 · see citing works
Goldstein, K. M., Melnyk, S. D., Zullig, L., Stechuchak, K., Oddone, E., Bastian, L., Rakley, S. M., Olsen, M., & Bosworth, H. (2014) · Women's health issues · doi:10.1016/j.whi.2014.05.005 · Cited by 49 · see citing works
Quiñones, A. R., Thielke, S. M., Beaver, K. A., TRIVEDI, R. B., Williams, E. C., & Fan, V. S. (2013) · Psychiatric Services · doi:10.1176/appi.ps.201300057 · Cited by 50 · see citing works
“Finally, race-ethnicity data in VA patient records has been criticized as lacking in completeness (22).”
BackgroundMethodA National Study of Racial Differences in Pain Screening Rates in the VA Health Care System
Burgess, D. J., Gravely, A., Nelson, D., van Ryn, M., Bair, M., Kerns, R., Higgins, D. M., & Partin, M. R. (2013) · The Clinical Journal of Pain · doi:10.1097/ajp.0b013e31826a86ae · Cited by 49 · see citing works
Long, J. A., Bamba, M., Ling, B. S., & Shea, J. (2006) · Journal of health care for the poor and underserved · doi:10.1353/hpu.2006.0029 · Cited by 49 · see citing works
Moy, E., Arispe, I., Holmes, J., & Andrews, R. (2005) · Medical Care · doi:10.1097/00005650-200503001-00003 · Cited by 49
“An estimate for AI/ANs could be generated for only 5% of safety measures, primarily because most of these measures come from hospital administrative data, which often do not identify AI/ANs in a standard fashion.(18) For the new racial groups included in 1997 federal standards, NHOPIs and persons of more than 1 race,…”
BackgroundHerman, M. R. (2010) · Social Psychology Quarterly · doi:10.1177/0190272510361436 · Cited by 48 · see citing works
“For example, doctors often want to know the race(s) of their patients in order to make informed diagnosis and treatment decisions and to provide accurate public health data (Kressin et al. 2003; van Ryn and Burke 2000).”
BackgroundRace and the validity of self-reported cancer screening behaviors: Development of a conceptual model
Burgess, D. J., Powell, A. A., Griffin, J. M., & Partin, M. R. (2008) · Preventive Medicine · doi:10.1016/j.ypmed.2008.11.014 · Cited by 43 · see citing works
Williams, E. C., Lapham, G. T., Hawkins, E. J., Rubinsky, A. D., Morales, L. S., Young, B. A., & Bradley, K. A. (2012) · Alcoholism Clinical and Experimental Research · doi:10.1111/j.1530-0277.2012.01761.x · Cited by 49 · see citing works
“…as unknown, Asian/Pacific Islander, and American Indian/Alaskan Native were excluded due to small numbers and because documentation of race/ethnicity for these groups historically results in the lowest levels of agreement with selfreported race/ethnicity among Veterans (Kressin et al., 2003).”
BackgroundResultInfluentialHollenbach, J. A., Saperstein, A., Albrecht, M. C., Vierra‐Green, C., Parham, P., Norman, P. J., & Maiers, M. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135960 · Cited by 48 · see citing works
Ohl, M. E., Richardson, K., Kaboli, P., Perencevich, E., & Vaughan-Sarrazin, M. (2014) · Journal of Rural Health · doi:10.1111/jrh.12070 · Cited by 46 · see citing works
Koo, K. H., Hebenstreit, C. L., Madden, E., & Maguen, S. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.08.038 · Cited by 47 · see citing works
“However, selfreported race/ethnicity tends to match administrative data, except for those of Native American descent (Kressin et al., 2003).”
BackgroundRace and ethnicity as factors in mental health service use among veterans with PTSD
Spoont, M. R., Hodges, J., Murdoch, M., & Nugent, S. (2009) · Journal of Traumatic Stress · doi:10.1002/jts.20470 · Cited by 45 · see citing works
Katikireddi, S. V., & Valles, S. A. (2014) · American Journal of Public Health · doi:10.2105/ajph.2014.302279 · Cited by 43 · see citing works
Halanych, J., Wang, F., Miller, D. R., Pogach, L., Lin, H., Berlowitz, D., & Frayne, S. (2006) · Medical Care · doi:10.1097/01.mlr.0000207433.70159.23 · Cited by 44 · see citing works
“2%) and the validity of the VHA administrative data for these groups is low ( 40% agreement compared with self-report survey data).(24)”
BackgroundMethodResultInfluentialAre psychiatric disorders independent risk factors for new-onset epilepsy in older individuals?
Ettinger, A. B., Copeland, L. A., Zeber, J. E., Cott, A. C. V., & Pugh, M. J. (2009) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2009.10.010 · Cited by 44 · see citing works
“Several studies have found that categorization of race from VA administrative data was quite accurate compared with patient self-report, particularly for white, black, and Hispanic enrollees [22].”
BackgroundWilliams, E. C., Gupta, S., Rubinsky, A. D., Jones‐Webb, R., Bensley, K. M., Young, J. P., Hagedorn, H., Gifford, E. V., & Harris, A. H. S. (2016) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.12950 · Cited by 46 · see citing works
Achieving health equity: an incremental journey.
Ibrahim, S., Thomas, S. B., & Fine, M. (2003) · American Journal of Public Health · doi:10.2105/ajph.93.10.1619 · Cited by 41
Risk of Persistent Palatal Fistula in Patients With Cleft Palate
Ahmed, M. K., Maganzini, A., Marantz, P., & Rousso, J. (2015) · JAMA Facial Plastic Surgery · doi:10.1001/jamafacial.2014.1436 · Cited by 39
Aseltine, R., Wang, W., Benthien, R. A., Katz, M., Wagner, C., Yan, J., & Lewis, C. (2019) · Journal of Bone and Joint Surgery. American volume · doi:10.2106/jbjs.18.01112 · Cited by 38 · see citing works
Optimizing Data on Race and Ethnicity for Veterans Affairs Patients.
Peltzman, T., Rice, K., Jones, K. T., Washington, D. L., & Shiner, B. R. (2022) · Military Medicine · doi:10.1093/milmed/usac066 · Cited by 37
Copeland, L., Zeber, J., Sako, E., Mortensen, E., Pugh, M., Wang, C.-P., Restrepo, M., Flynn, J., MacCarthy, A., & Lawrence, V. (2015) · BMC Surgery · doi:10.1186/s12893-015-0064-7 · Cited by 37 · see citing works
“The validity of VA administrative databases has been ascertained by studies examining demographics, types of care, and diagnoses [18–20].”
BackgroundRacial disparities in the use of blood transfusion in major surgery
Qian, F., Eaton, M., Lustik, S., Hohmann, S., Diachun, C., Pasternak, R., Wissler, R., & Glance, L. G. (2014) · BMC Health Services Research · doi:10.1186/1472-6963-14-121 · Cited by 37 · see citing works
Frei, C. R., Mortensen, E., Copeland, L. A., Attridge, R., Pugh, M., Restrepo, M., Anzueto, A., Nakashima, B., & Fine, M. J. (2010) · BMC Health Services Research · doi:10.1186/1472-6963-10-143 · Cited by 37 · see citing works
“However, while VHA race data have been validated especially for Caucasian and African-American patients, [30,31] missing data on race/ethnicity is a persistent problem.”
Disparities by Race, Ethnicity, and Sex in Treating Acute Coronary Syndromes
Freund, K., Jacobs, A., Pechacek, J., White, H. F., & Ash, A. (2012) · Journal of Women's Health · doi:10.1089/jwh.2010.2580 · Cited by 36
“There are data to suggest that patients of Hispanic descent are misidentified as white, especially if they speak English, 11,12 and that the rate of misclassification of Hispanic persons is greater than that in African Americans.”
Hall, J. B., Dumitrescu, L., Dilks, H., Crawford, D., & Bush, W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099161 · Cited by 35
New‐onset geriatric epilepsy care: Race, setting of diagnosis, and choice of antiepileptic drug
Hope, O. A., Zeber, J., Kressin, N., Bokhour, B. G., Cott, A. V. V., Cramer, J., Amuan, M. E., Knoefel, J., & Pugh, M. (2009) · Epilepsia · doi:10.1111/j.1528-1167.2008.01892.x · Cited by 34
“Several studies have found that race from administrative data were quite accurate compared to patient self-report, particularly for white, black and Hispanic enrollees (Kressin et al., 2003; Sohn et al., 2006).”
ResultSelf-citationTribal Linkage and Race Data Quality for American Indians in a State Cancer Registry
Johnson, J. C., Soliman, A., Tadgerson, D., Copeland, G., Seefeld, D. A., Pingatore, N. L., Haverkate, R., Banerjee, M., & Roubidoux, M. (2009) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2009.01.035 · Cited by 34
Racial differences in the treatment of veterans with bipolar disorder.
Kilbourne, A., Bauer, M., Han, X., Haas, G., Elder, P., Good, C., Shad, M., Conigliaro, J., & Pincus, H. (2005) · Psychiatric Services · doi:10.1176/appi.ps.56.12.1549 · Cited by 34
Racialising genetic risk: assumptions, realities, and recommendations
Cerdeña, J. P., Grubbs, V., & Non, A. L. (2022) · The Lancet · doi:10.1016/s0140-6736(22)02040-2 · Cited by 44 · see citing works
An observational study of musculoskeletal pain among patients receiving bisphosphonate therapy.
Caplan, L., Pittman, C. B., Zeringue, A., Scherrer, J. F., Wehmeier, K., Cunningham, F., Eisen, S., & Mcdonald, J. (2010) · Mayo Clinic proceedings · doi:10.4065/mcp.2009.0492 · Cited by 32 · see citing works
“race variable derived from the VA Corporate Franchise Data Center has been shown to exhibit poor correlation with patient self-report.(29) However, because race may play a role in susceptibility to osteoporosis, we included race in our analyses, recognizing that this variable may not have fully controlled for the conf…”
MethodKoo, K. H., Madden, E., & Maguen, S. (2015) · Psychiatric Services · doi:10.1176/appi.ps.201300498 · Cited by 28 · see citing works
Ohl, M. E., Perencevich, E., McInnes, D., Kim, N. S., Rimland, D., Akgun, K., Fiellin, D. A., Skanderson, M., Wang, K. H., & Justice, A. (2012) · Aids and Behavior · doi:10.1007/s10461-012-0325-8 · Cited by 30
“Classification of race/ethnicity in VA administrative data is accurate for blacks and whites compared to self-report, but less accurate for other groups [21].”
BackgroundChavez, L., Liu, C.-F., Tefft, N. W., Hebert, P., Clark, B., Rubinsky, A. D., Lapham, G. T., & Bradley, K. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2015.11.008 · Cited by 29 · see citing works
“Patients for whom race was unknown/missing were categorized as nonwhite, given that patients missing race/ethnicity in administrative data more often report nonwhite race (Kressin et al., 2003).”
BackgroundPolsky, D., Lave, J., Klusaritz, H., Jha, A., Pauly, M., Cen, L., Xie, H., Stone, R., Chen, Z., & Volpp, K. (2007) · Medical Care · doi:10.1097/mlr.0b013e3180ca960e · Cited by 29
Bigback, K. M., Hoopes, M., Dankovchik, J., Knaster, E., Warren‐Mears, V., Joshi, S., & Weiser, T. (2015) · Health Services Research · doi:10.1111/1475-6773.12331 · Cited by 29 · see citing works
“AI/AN are frequently misclassified in surveillance and administrative data systems, with misclassification ranging from 30 to 70 percent (Kressin et al. 2003; Puuka, Stehr-Green, and Becker 2005; Johnson et al. 2009; Hoopes et al. 2010).”
BackgroundMethod
- Authors
- Kressin, N. R., Chang, B.-H., Hendricks, A., & Kazis, L. E.
- Affiliations
- Boston University (US)
- Venue
- American Journal of Public Health
- Publisher
- American Public Health Association
- Published
- 2003-10
- Volume
- 93
- Issue
- 10
- Pages
- 1734-1739
- ISSN
- 0090-0036 (ISSN-L)
- 1541-0048
- PMC
- PMC1448042
- OpenAlex
- W2145841259
- Cited by
- 234
- References
- 0
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 7 · 2023: 10 · 2022: 10 · 2021: 11 · 2020: 6 · 2019: 6 · 2018: 5 · 2017: 5 · 2016: 8 · 2015: 18 · 2014: 15 · 2013: 13 · 2012: 11
- FWCI
- 30.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Public Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- race and ethnicity, self-report, administrative data, data source agreement, veterans, racial disparities, Native Americans, sociodemographic correlates
- MeSH terms
- Demography, Ethnicity, Health Services Research, Hospitals, Veterans, Humans, Patients, Self Concept, Socioeconomic Factors, United States, United States Department of Veterans Affairs, Veterans, Reproducibility of Results, Databases, Factual, Public Health Informatics
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