RESEARCHERS’ GUIDE TO VA DATA

Assessing Race and Ethnicity

May 5, 2014

Presented by: Maria Mor, PhD

Center for Health Equity Research and Promotion

VA Pittsburgh Healthcare System

1 

2014 VIReC Databases and Methods Cyberseminar Series 
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

2 
RESEARCHERS’ GUIDE TO VA DATA

Audience Poll

Have you ever used VA Race/Ethnicity 

Data?

– Yes

– No

3 
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

4 
RESEARCHERS’ GUIDE TO VA DATA

Introduction/Overview

Racial/ethnic disparities in health and health care are 

well-documented and persistent in the US

– Root causes and solutions are not well understood

– While overall quality is improving, access is getting worse 

and disparities are not changing (AHRQ 2012) 

Racial/ethnic disparities also exist in VHA, where financial 

barriers to receiving care are minimized

– Although quality has improved, significant within-facility 

disparities observed in clinical outcomes (Trivedi 2011)

More research to detect, understand, and address 

disparities in health and health care is needed

5
RESEARCHERS’ GUIDE TO VA DATA

Introduction/Overview

Accurate race/ethnicity data are essential to 

disparities research and research on clinical factors 

associated with race/ethnicity

Problems with race/ethnicity data in the VA

— Incomplete 

— Inaccuracies

— Inconsistent over time

6 
RESEARCHERS’ GUIDE TO VA DATA

Racial/Ethnic Distribution of Veterans

Approximately 80% of all Veterans are White

– 0.6% American Indian or Alaska Native

– 1.3% Asian

– 10.8% Black

– 6.0% Hispanic

– 1.4% Some other race

Use of VA health care differs by race

– Asian Veterans less likely to use (20.5 %)

– Black, AIAN, Other race more likely to use (>30%)

http://www.va.gov/vetdata/docs/SpecialReports/Minority

_Veterans_2011.pdf

7
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

8 
RESEARCHERS’ GUIDE TO VA DATA

VA Race and Ethnicity Categories

VHA Handbook 1601A.01 (2009)

9

Ethnicity

— Spanish, Hispanic, or Latino

Race (>1 may be selected)

— American Indian or Alaska Native

— Asian

— Black or African American

— Native Hawaiian or Other Pacific Islander

— White

— Unknown by Patient

Current reporting method

— 2 question format: ethnicity, race

— Self-reported

 
RESEARCHERS’ GUIDE TO VA DATA

Race and Ethnicity Data Collection Standards

OMB Directive Revision No. 15 (1997)

— Standards for maintaining, collecting, and presenting 

federal data on race and ethnicity

— Implemented in DVA in 2003

Joint Commission (2010)

— Collection of patient demographic data (e.g., race and 

ethnicity) key element of performance

Affordable Care Act (2011)

— New data collection standards for race, ethnicity, 

primary language, and sex

10
RESEARCHERS’ GUIDE TO VA DATA

Acquisition of Race/Ethnicity Data in VHA 

11

WHO: WHAT: WHEN: WHERE: HOW:

Information 

Source:

• Patient

(selfreport)

• Proxy

• VA Form 10-

10EZ, 

Application 

for Health 

Benefits 

(online, 

paper, or by 

interview)

• Enrollment

• Hospital 

admission

• Outpatient 

visit or preregistration

• Online

• Telephone 

call from 

local VHA 

facility

• In-person 

visit to local 

VHA facility

• VHA Facility 

Enrollment 

Coordinator or 

designee (e.g., 

Admission 

Interview Clerk, 

Enrollment 

Specialist) or 

• Outpatient clinic 

personnel

• Collects the 

information and 

enters into VistA
RESEARCHERS’ GUIDE TO VA DATA

Race/Ethnicity Data Collection: Historical

Method of ascertainment uncertain, primarily 

observer-reported

No option for multiple race reporting

Single question captured both race and ethnicity:

– Hispanic, White

– Hispanic, Black

– American Indian

– Black

– Asian

– White

12
RESEARCHERS’ GUIDE TO VA DATA

Race/Ethnicity Data Collection: Enrollment 

VA Form 10-10EZ (Application for Health Benefits)

Data entered into the Veterans Health Information 

Systems and Technology Architecture (VistA) 

— Race Information and Patient Information Sub-files

Demographic data (e.g., race) transmitted with 

encounter data to the Austin Information Technology 

Center

— National Patient Care Database (NPCD)

Medical SAS (MedSAS) datasets

— Extracts of NPCD data

13
RESEARCHERS’ GUIDE TO VA DATA

Race/Ethnicity Data Collection: Clinical Setting

Race and ethnicity obtained during pre-registration, 

if missing

Race and ethnicity collected directly from the patient 

(or proxy)

— Hospital admission

— Clinic registration

Data entered into VistA

— Race Information and Patient Information Sub-files

Separate VistA field for method of data collection

14
RESEARCHERS’ GUIDE TO VA DATA

Audience Poll 

What sources of VA race/ethnicity data 

have you used (check all that apply)?

– 1 Never Used

– 2 MedSAS files

– 3 CDW

– 4 VistA or regional warehouse

– 5 Other VA data sources

15
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

16
RESEARCHERS’ GUIDE TO VA DATA

Sources of Race and Ethnicity Data in VA

Medical SAS Datasets

17

Variable Name MedSAS Dataset Description

RACE Inpatient (PTF Main File) FY1970 - present

Outpatient (Visit File) FY1997 - present

Outpatient (Event File) FY1998 - present

RACE1-RACE6 Inpatient (PTF Main) FY2003 - present

RACE1-RACE7 Outpatient (Visit, Event) FY2004 - present

ETHNIC Inpatient (PTF Main) FY2003 - present

Outpatient (Visit, Event) FY2004 - present
RESEARCHERS’ GUIDE TO VA DATA

Race/Ethnicity Variables in MedSAS

Prior to FY 2003

Race and ethnicity captured jointly in the variable RACE

Single value allowed for race/ethnicity

After FY 2003

Multiple races captured in RACE1-RACE7

Single value for ethnicity captured in ETHNIC

RACE1-RACE7 and ETHNIC have a length of 2 characters

First character has race or ethnicity

Second character has method of data collection

Common format used for method of data collection

18
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Race/Ethnicity Values (Pre 2003)

RACE: Single value for race and ethnicity

 

19

Value Description

1 Hispanic, white 

2 Hispanic, black 

3 American Indian 

4 Black

5 Asian 

6 White 

7 or missing Unknown 
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Race Values (Post 2003)

RACE1-RACE7 : Race and method of data collection 

The first character specifies race

 

20

1st Character Description

3 American Indian Or Alaska Native 

8 Asian 

9 Black or African American 

A Native Hawaiian or Other Pacific Islander 

B White

C Declined to Answer

D Unknown 

**Other** Missing
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Ethnicity Values (Post 2003)

ETHNIC: Ethnicity and method of data collection 

The first character captures ethnicity

 

21

1st Character Description

D Declined To Answer 

H Hispanic or Latino

N Not Hispanic or Latino 

U Unknown 

**Other** Missing
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Race and Ethnicity Source (Post 2003)

RACE1-RACE7, ETHNIC

The second character specifies method of data 

collection

 

22

2nd Character Description

Missing 

O Observer 

P Proxy 

S Self-identification 

U Unknown By Patient 
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Completeness of Race Data

A substantial portion of patients do not have a 

“usable” race value* in the VA Medical SAS Inpatient

and Outpatient Datasets

 

* A usable race value is any value that is not ‘missing’ or ‘unknown’ or 

‘declined’ 23

FY Usable Race, % FY Usable Race, %

1997 57 2005 67

1998 57 2006 72

1999 58 2007 75

2000 58 2008 76

2001 56 2009 78

2002 55 2010 80

2003 49 2011 83

2004 62 2012 85
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets:

Completeness by Source

Visit-level data usability

 

* A usable value is any that is not ‘missing’ or ‘unknown’ or ‘declined’

24

Inpatient Outpatient

FY Race, % Ethnicity, % Race, % Ethnicity,%

2006 78.0 50.9 66.8 68.8

2007 67.9 46.3 72.0 75.7

2008 51.3 37.3 75.3 80.3

2009 43.6 32.1 78.0 83.6

2010 40.7 31.4 80.1 86.2

2011 40.8 31.8 82.3 88.5

2012 41.7 31.8 84.9 90.9

2013 41.2 32.2 86.2 92.1
RESEARCHERS’ GUIDE TO VA DATA

Medical SAS Datasets: 

Completeness of Ethnicity Data

90% of visits in FY 2012 have a “usable” ethnicity 

value* in the VA Medical SAS Inpatient and 

Outpatient Datasets

Completeness of ethnicity in the VA Medical SAS 

Inpatient Datasets is low (32% for FY 2012)

– Half of inpatient facilities have blank ethnicity data for 

at least 98% of inpatient records

– 36% of facilities have blank ethnicity data for all 

inpatient records

* A usable ethnicity value is any value that is not ‘missing’ or 

‘unknown’ or ‘declined’

25
RESEARCHERS’ GUIDE TO VA DATA

Corporate Data Warehouse (CDW)

National repository of data from VistA Patient File 

with race and ethnicity data from October 1999 - 

Contains 1 demographic record for each VA station a 

Veteran has visited

Contains standard and nonstandard race values

Stored in a view called PatSub.PatientRace 

Documentation: Best Practices Guide Race Data 

─ Send va.gov email to VIReC@va.gov for URL

26
RESEARCHERS’ GUIDE TO VA DATA

Nonstandard Race Values in CDW

6 of 31 nonstandard race values can be mapped to 

 standard races

2

4

27

Examples

Nonstandard Race Standard

AMER INDIAN OR ALASKAN NATIVE, AMERICAN INDIAN OR 

AMERICAN INDIAN, AMERICAN INDIAN / ALASKA NATIVE

ALASKAN NATIVE 

BLACK; BLACK NOT OF HISP ORIG; BLACK, BLACK OR AFRICAN 

NON HISPANIC; HISPANIC BLACK AMERICAN

WHITE NOT OF HISP ORIG; WHITE, NOT WHITE 

HISPANIC; HISPANIC WHITE; CAUCASIAN; 

PACIFIC ISLANDER NATIVE HAWAIIAN OR 

OTHER PACIFIC ISLANDER
RESEARCHERS’ GUIDE TO VA DATA

Non-Mapped Values (CDW)

5 values are not mapped to standard values

Asian or Pacific Islander

Asian Pacific Islander

Asian/Pacific Islander

Mexican American

Unknown

4.6% of data values fall into 1 of these 5 categories

28
RESEARCHERS’ GUIDE TO VA DATA

Multiple Race Values (CDW)

Approximately 1.7% of patients linked to a standard 

race have more than 1 standard race

Not possible to identify the most recent record for a 

patient

Recommendation for multiple values

Use only self-identified races, if any are recorded

Use all recorded races for patients without self-identified 

race

Documentation: CDW Race Data and Multiple Races

─ Send va.gov email to VIReC@va.gov for URL

29
RESEARCHERS’ GUIDE TO VA DATA

Race Capture (CDW)

Percent of patients with a standard race in the CDW 

varies by year of most recent healthcare activity

 

* No activity after FY 1999

30

FY Standard Race, % FY Standard Race, %

1999* 39.0 2006 63.0

2000 42.6 2007 65.9

2001 43.5 2008 66.6

2002 44.1 2009 67.2

2003 48.2 2010 68.5

2004 53.8 2011 70.2

2005 58.7 2012 84.6
RESEARCHERS’ GUIDE TO VA DATA

Ethnicity (CDW)

Ethnicity found in two CDW tables

PatSub.PatientEthnicity – new method 

‘HISPANIC OR LATINO’

‘NOT HISPANIC OR LATINO’

PatSub.PatientRace – old method (Appendix A)

HISPANIC, WHITE

WHITE NOT OF HISP ORIG

HISPANIC, BLACK

BLACK NOT OF HISP ORIG

Documentation: CDW Ethnicity Data 

─ Send va.gov email to VIReC@va.gov for URL

31
RESEARCHERS’ GUIDE TO VA DATA

Ethnicity (CDW), continued

Results

61% of all patients have ethnicity recorded

88% of those with healthcare activity in FY 2012

78% with one standard category are self-identified

1% have conflicting ethnicity categories 

Recommendations

Only use ethnicity captured through self-identification, if 

available

Otherwise, use ethnicity captured through new recording 

method (Patsub.PatientEthnicity) 

Use older collection methods (Patsub.PatientRace) when no 

other data are available

32
RESEARCHERS’ GUIDE TO VA DATA

CDW Summary 

8.3 million unique patient records with standard race

values

2.3 million patient records with nonstandard race 

values that can be mapped to standard values

Can contain multiple records per patient if patient 

visited more than 1 facility

Sample queries for CDW data contained in Best 

Practices Guide: Race Data

When multiple values are present

Use self-identified race and ethnicity

Otherwise use new collection methods (not self-identified)

Only use older collection methods if no other data

33
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

34
RESEARCHERS’ GUIDE TO VA DATA

Medicare Race/Ethnicity Data

Potentially useful source for Veterans in Medicare

— Age 65 and older (>95% of VA elderly)

— Disabled (~20% of VA patients <65 years)

— End stage renal disease

Derived primarily from Social Security Administration

— Obtained at the time of application for SSN and/or 

replacement card

— Reporting sources: Usually self or family

Distinctions from current VA race/ethnicity data

— ‘Hispanic’ is a race category

— No multiple race reporting

35
RESEARCHERS’ GUIDE TO VA DATA

Medicare Race Data from SSA

Until 1980, 4 categories only

— White 

— Black

— Other

— Unknown

In 1980, ‘Other’ replaced by

— Asian, Asian American or Pacific Islander

— Hispanic

— American Indian or Alaskan Native

36
RESEARCHERS’ GUIDE TO VA DATA

RTI Race in Medicare 

Research Triangle Institute created and implemented 

an algorithm to increase accuracy of race variable, 

especially for Hispanic and Asian individuals

RTI_RACE available in Medicare Denominator File

Algorithm uses first name, last name, preferred 

language, place of residence

Improvement in sensitivity of racial codes

– Increased from 30% to 77% for Hispanic

– Increased from 55% to 80% for Asian/Pacific Islander

37
RESEARCHERS’ GUIDE TO VA DATA

Sources of Medicare Race Data in VA

VA Vital Status File

– CMS_RACE 

– Race is in Master File only

– Master File contains one record for each SSN-date of 

birth (DOB)-gender combination found in VA data 

– Some SSNs have more than one record

Denominator file from Medicare

– RACE (same as CMS_RACE)

– RTI_RACE

38
RESEARCHERS’ GUIDE TO VA DATA

Medicare Race Data Summary

Medicare race data quality issues

— Information on most enrollees (those who obtained SSN prior 

to 1980) limited to original 4 categories

— SSN application form – single question format and no 

multiple race reporting

Initiatives to improve quality of race/ethnicity data

— Periodic updates on American Indians and Alaskan Natives 

from Indian Health Service

— 1997 survey of enrollees classified as ‘Other’, ‘Unknown’, or 

with Spanish surname, requesting race/ethnicity self-report

— RTI Race Algorithm

39
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

40
RESEARCHERS’ GUIDE TO VA DATA

 Use of Medicare and DoD Data for Improving

VA Race Data Quality

Stroupe, et al. (2010) Journal of Rehabilitation Research & Development

Aims

1. To estimate the extent to which missing “usable” 

race data in VA MedSAS files can be reduced by 

using non-VA data sources

a. Medicare

b. DoD

2. To evaluate the agreement between VA selfreported race data in MedSAS files and

a. Medicare race data

b. DoD race data

41
RESEARCHERS’ GUIDE TO VA DATA

Use of Medicare and DoD Data for Improving

VA Race Data Quality

Stroupe, et al. (2010) Journal of Rehabilitation Research & Development

Patient cohort

— 10% representative sample of VA patients who 

obtained services during FY 2004-2005

— N = 570,018

Medicare race data were obtained from Medicare 

Vital Status file

DoD race data were obtained from the VA/DoD

Identity Repository (VADIR) database for individuals 

<65 years

– VA/DoD data-sharing agreement

– Self-reported race/ethnicity obtained from service 

members 

42
RESEARCHERS’ GUIDE TO VA DATA

Use of Medicare and DoD Data for Improving

VA Race Data Quality

Stroupe, et al. (2010) Journal of Rehabilitation Research & Development

43

Patients with & without Usable 

Race Data in VA MedSAS

Usable 

Race Value

(n=275,008)

No Usable Race 

Value

(n=295,010)

Age, >65 years, % 43 45

Male, % 94 89 

Married, % 56 56 

Geographic Region, %

 Northeast 16 17 

 South 44 37 

 Midwest 23 21 

 West 17 25 
RESEARCHERS’ GUIDE TO VA DATA

Aim 1a: Improvement in Race Completeness 

with Addition of Medicare Data from 2004-2005

44
RESEARCHERS’ GUIDE TO VA DATA

Aim 1: Improvement in Race Completeness 

with Addition of Medicare and DoD Data from 2004-2005

45

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

DoD only DoD and Medicare

49.1% 49.1% 

18.9% 26.4% 

32.1% 24.5% 

Individuals with a Usable Race Value

Figure. Adding DoD or DoD and Medicare Data Improves Race Data 

Completeness Among Non-Elderly (N = 319,756)

Final Missing Race

DoD/Medicare Usable Race

VA Usable Race
RESEARCHERS’ GUIDE TO VA DATA

Aim 2: Comparison of Medicare 

with VA and DoD Data, 2004-2005 

46

VA Race Medicare Race DoD Data

Classification 

Constructed for 

Consistency 

Analysis

White White White White

Black or African 

American Black Black Black or African 

American

American Indian or 

Alaska Native

North American 

Native

American Indian or 

Alaska Native

North American 

Native

Asian Asian Asian or Pacific

Islander Asian, Pacific 

Native Hawaiian or Islander, or Other

Other Pacific 

Islander

Other Other
RESEARCHERS’ GUIDE TO VA DATA

Aim 2a: Comparison of VA with Medicare 

Data, 2004-2005

47
RESEARCHERS’ GUIDE TO VA DATA

Aim 2a: Comparison of VA with Medicare 

Data, 2004-2005

48
RESEARCHERS’ GUIDE TO VA DATA

Aim 2b: Comparison of VA with DoD 

Data, 2004-2005

49
RESEARCHERS’ GUIDE TO VA DATA

Use of Medicare and DoD Data for Improving

VA Race Data Quality

Stroupe, et al. (2010) Journal of Rehabilitation Research & Development

Conclusion 

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

50
RESEARCHERS’ GUIDE TO VA DATA

Improving Patient Demographic Information 

in VA Databases

T21-funded collaboration between Center for 

Health Equity Research and Promotion and 

Veterans Engineering Resource Center

Patients (n=173) with missing or declined race 

at VA Pittsburgh Healthcare System were 

surveyed by telephone regarding their:

– Comfort with being asked to provide 

race/ethnicity, address/telephone, and 

insurance when coming to the VA

– Preference for providing that information to a 

clerk or computer kiosk (n=48 seen at site with 

kiosks)

51
RESEARCHERS’ GUIDE TO VA DATA

Comfort in Providing Race/Ethnicity Data

52

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

86% 93% 85%

5%

4%

8%

Race/Ethnicity Address/Telephone Insurance

Information Type

Completely 

Uncomfortable

Somewhat 

Uncomfortable

Neither

Somewhat 

Comfortable

Completely 

Comfortable

Level of Comfort*

*Data values not shown for percentages less than 4

Comfort in Providing Requested Information (N=173)
RESEARCHERS’ GUIDE TO VA DATA

Preference for Collection of Race/Ethnicity Data

0%

20%

40%

60%

80%

100%

Race/Ethnicity Address/Insurance

44% 46% 

42% 33% 

10% 17% 

Kiosk

No Preference

Clerk

Preferred Mode for Updating Information (N=48)

Preferred Mode

Information Type

53
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

54
RESEARCHERS’ GUIDE TO VA DATA

Recommendations

Supplement inpatient race and ethnicity with 

outpatient data when using MedSAS files

When multiple sources of race and ethnicity exist

– Use self-identified race and ethnicity, if available

– Use data from the old collection method, only if data 

from new collection method are not available

Use the RACE variable to obtain ethnicity and race 

collected by the old method (MedSAS) 

Use Sub.PatientRace to obtain ethnicity collected by 

the old method (CDW)

55
RESEARCHERS’ GUIDE TO VA DATA

Recommendations

Use of Medicare race information will reduce the 

problem of missing race in VA studies using 

administrative data

When using VA VSF, match on date of birth and 

gender, in addition to (scrambled) SSN

—Researchers will be most likely to identify the right 

individuals in the VSF if they use all 3 elements 

when conducting their VSF-study cohort record 

match

56
RESEARCHERS’ GUIDE TO VA DATA

Recommendations

Classifying minorities as either Black/African 

American or Other in VA studies using Medicare race 

information results in higher rates of accurate 

classification than other groupings

—VA North American Natives and Hispanics 

frequently misclassified as White (and NonHispanic) in Medicare 

—Medicare White and African-American categories, 

both had high predictive values for VA race

57
RESEARCHERS’ GUIDE TO VA DATA

Recommendations

Medicare data cannot be used to identify 

Hispanics with any degree of accuracy or 

completeness

RTI_RACE in the Medicare Denominator file can 

increase the identification of Hispanics and Asians

Consider other supplementary data sources

– Department of Defense

– Special surveys

58
RESEARCHERS’ GUIDE TO VA DATA

Session Overview

Introduction

Race and Ethnicity Data Collection in VA 

Race and Ethnicity in VA Data

Race and Ethnicity in Medicare Data

Quality of VA Race/Ethnicity Data

Recommendations

Where to Go for More Help

59
RESEARCHERS’ GUIDE TO VA DATA

60

VIReC Help 

VIReC Webpage (http://www.virec.research.va.gov) 

– Information on VA data sources and how to access data

– Documentation on some VA datasets, e.g., MedSAS 

datasets 

HSRData Listserv

– Join at the VIReC Web site

– Discussion among >500 data stewards, managers, and 

users 

– Past messages in archive (on intranet)

VIReC Help Desk

– VIReC staff will answer your question and/or direct you 

to available resources on topics

– VIReC@va.gov or (708) 202-2413
Selected Recent References on 

Race/Ethnicity Data

AHRQ (Agency for Healthcare Research and Quality) (2012). National healthcare disparities report, 2012 (Rep. No. AHRQ Publication No. 13-0003). Rockville, 

MD: U.S. Department of Health and Human Services, Agency for Healthcare Research and Quality.

Baker DW, Cameron KA, Feinglass J, Thompson, JA, Georgas P, Foster S, et al. (2006). A system for rapidly and accurately collecting patients' race and ethnicity. 

Am J Public Health, 96, 532-537.

Bertolli J, LeeLisa M, Sullivan PS. (2007). Racial Misidentification of American Indians/Alaska Natives in the HIV/AIDS Reporting Systems of Five States and One

Urban Health Jurisdiction, U.S., 1984–2002. Public Health Reports, 122, 382-392.

Blustein J. (1994). The Reliability of Racial Classifications in Hospital Discharge Abstract Data. American Journal of Public Health, 84, 1018-1021.

Boehmer U, Kressin NR, Berlowitz DR, Christiansen CL, Kazis LE, Jones JA. (2002). Self-reported vs administrative race/ethnicity data and study results. Am J 

Public Health, 92, 1471-1472.

Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes and Socioeconomic Status (SES) Indicators for Medicare Beneficiaries. Final 

Report, Sub-Task 2. (Prepared by RTI International for the Centers for Medicare and Medicaid Services through an interagency agreement with the Agency 

for Healthcare Research and Policy, under Contract No.500-00-0024, Task No. 21) AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for Healthcare 

Research and Quality. January 2008

Brahan D, Bauchner H. (2005). Changes in reporting of race/ethnicity, socioeconomic status, gender, and age over 10 years. Pediatrics, 115, e163-e166.

Clegg LX, Reichman ME, Hankey BF, Miller BA. Lin YD, Johnson NJ, et al. (2007). Quality of race, Hispanic ethnicity, and immigrant status in population-based

cancer registry data: implications for health disparity studies. Cancer Causes Control, 18, 177-187.

Eicheldinger C, Bonito A. (2008). More accurate racial and ethnic codes for Medicare administrative data. Health Care Financ Rev, 29, 27-42.

Elliott MN, Fremont A, Morrison PA, Pantoja P, Lurie N. (2008). A new method for estimating race/ethnicity and associated disparities where administrative 

records lack self-reported race/ethnicity. Health Serv Res. 

Ford ME, Kelly PA. (2005). Conceptualizing and categorizing race and ethnicity in health services research. Health Serv Res, 40, 1658-1675.

Friedman DJ, Cohen BB, Averbach AR, Norton JM. (2000). Race/ethnicity and OMB Directive 15: implications for state public health practice. Am.J Public Health, 

90, 1714-1719.

Gomez SL, Kelsey JL, Glaser SL, Lee MM, Sidney S. (2005). Inconsistencies between self-reported ethnicity and ethnicity recorded in a health maintenance 

organization. Ann Epidemiol, 15, 71-79.

Gomez SL, Glaser SL. (2006). Misclassification of race/ethnicity in a population-based cancer registry (United States). Cancer Causes Control, 17, 771-781.

Hahn RA. (1992). The state of federal health statistics on racial and ethnic groups. JAMA, 267, 268-271.

Hahn RA, Stroup DF. (1994). Race and ethnicity in public health surveillance: criteria for the scientific use of social categories. Public Health Rep, 109, 7-15.

Hamilton NS, Edelman D, Weinberger M, Jackson GL. (2009). Concordance between self-reported race/ethnicity and that recorded in a Veteran Affairs electronic 

medical record. N C Med J, 70, 296-300.

Institute of Medicine. (2003). Unequal treatment: Confronting racial and ethnic disparities in health care Washington, DC: National Academies Press.

Jones CP, Truman BI, Elam-Evans LD, Jones CA, Jones CY, Jiles R, et al. (2008). Using "socially assigned race" to probe white advantages in health status. Ethn 

Dis, 18, 496-504.

Kashner TM. (1998). Agreement between administrative files and written medical records: a case of the Department of Veterans Affairs. Med Care, 36, 1324-

1336.

Kramer BJ, Wang M, Hoang T, Harker JO, Finke B, Saliba D. (2006). Identification of American Indian and Alaska Native veterans in administrative data of the 

Veterans Health Administration and the Indian Health.

Laws MB, Heckscher RA. (2002). Racial and ethnic identification practices in public health data systems in New England. Public Health Rep, 117, 50-61. 61

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Selected Recent References on 

Race/Ethnicity Data

Long JA, Bamba MI, Ling B, Shea JA. (2006). Missing race/ethnicity data in Veterans Health Administration based disparities research: a systematic review. J 

Health Care Poor Underserved. 17(1):128-40. Review.

Mays VM, Ponce NA, Washington DL, Cochran SD. (2003). Classification of race and ethnicity: implications for public health. Annu Rev Public Health, 24, 83-110.

McAlpine DD, Beebe TJ, Davern M, Call K T. (2007). Agreement between self-reported and administrative race and ethnicity data among Medicaid enrollees in 

Minnesota. Health Serv Res, 42, 2373-2388.

McBean AM. (2006). Improving Medicare's Data on Race and Ethnicity. National Academy of Social Insurance. Medicare Brief, No. 15. 

Ref Type: Serial (Book,Monograph) 

Morgan RO, Wei II, Virnig BA. (2004). Improving identification of Hispanic males in Medicare: use of surname matching. Med Care, 42, 810-816.

Office of Management and Budget Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity, Notice of Decision (Rep. No. 62).

Pan CX, Glynn RJ, Mogun H, Choodnovskiy I, Avorn J. (1999). Definition of race and ethnicity in older people in Medicare and Medicaid. J Am Geriatr Soc, 47, 730-

733.

Polednak AP. (2001). Agreement in race-ethnicity coding between a hospital discharge database and another database. Ethn Dis, 11, 24-29.

Rhoades D. (2005). Racial Misclassification and Disparities in Cardiovascular Disease Among American Indians and Alaska Natives. Circulation, 111, 1250-1256.

Saha S, Freeman M, Toure J, Tippens KM, Weeks C, Ibrahim S. (2008). Racial and ethnic disparities in the VA Health Care System: A Systematic Review. Journal 

of General Internal Medicine, 23, 654-671.

Sohn M, Zhang H, Arnold N, Stroupe K, Taylor B, Wilt T, et al. (2006). Transition to the new race/ethnicity data collection standards in the Department of Veterans 

Affairs. Population Health Metrics, 4. 

Sondik EJ, Lucas JW, Madans JH, Smith, SS. (2000). Race/ethnicity and the 2000 census: implications for public health. Am.J Public Health, 90, 1709-1713.

Stehr-Green P, Bettles J, Robertson LD. (2002). Effect of racial/ethnic misclassification of American Indians and Alaska Natives on Washington State death 

certificates, 1989-1997. American Journal of Public Health, 92, 443-444.

Stroupe KT, Tarlov E, Zhang Q, Haywood T, Owens A, Hynes DM. Use of Medicare and DoD data for improving VA race data quality. Journal of Rehabilitation 

Research & Development. 2010;47(8):781-795. 

Sugarman J, Soderberg R, Gordon J, Rivara, FP. (1993). Racial misclassification of American Indians: its effect on injury rates in Oregon, 1989

through 1990. Am J Public Health, 83, 681-684.

Sugarman J, Holliday M, Oss, A, Astorina J, Hui Y. (1996). Improving American Indian cancer data in the Washington State Cancer Registry

using linkages with the Indian Health Service and Tribal Records. Cancer, 78, 1564-1568.

The Joint Commission: Advancing Effective Communication, Cultural Competence, and Patient- and Family-Centered Care: A Roadmap for Hospitals. Oakbrook 

Terrace, IL: The Joint Commission, 2010.

Thoroughman DA, Frederickson D, Cameron D, Shelby L, Cheek, JE. (2002). Racial misclassification of American Indians in Oklahoma State Surveillance Data for 

Sexually Transmitted Diseases. American Journal of Epidemiology, 155, 1137-1141.

Trivedi AN, Grebla RC, Wright SM, Washington DL. (2011). Despite improved quality of care in the Veterans Affairs health system, racial disparity persists for 

important clinical outcomes. Health Affairs, 30, 707-715.

US Department of Veterans Affairs (2003). VHA Directive 2003-027, Capture of Race and Ethnicity Categories Washington, DC: US Department of Veterans Affairs.

US Department of Veterans Affairs (2009). VHA Handbook 1601A.01, Intake Registration Washington, DC: U.S.Department of Veterans Affairs.

Veterans Health Administration Decision Support Office (2009). National Data Extract Technical Guide Bedford, MA: U.S. Department of Veterans Affairs.

Wei II, Virnig BA, John DA, Morgan RO. (2006). Using a Spanish surname match to improve identification of Hispanic women in Medicare administrative data. 

Health Serv Res, 41, 1469-1481. 
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Questions?
RESEARCHERS’ GUIDE TO VA DATA

Upcoming Seminar

Applying Comorbidity Measures Using VA 

and Medicare Data

June 2, 2013 

James F. Burgess, PhD

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