The Feasibility of Using Electronic Health Data for Research on Small Populations. Appendix to Part I


Table I.1. Key Informant Interviews


Pre-Interviews (to identify target populations)

Agency for Healthcare Research & Quality

  • Steve Cohen, PhD, Harvey Schwartz, PhD, Cecilia Casale, PhD, Ed Lomotan, MD, Gurvaneet Randhawa MD, Jim Branscome, Joel Cohen, PhD

National Center for Health Statistics

  • Virginia Cain, PhD, Vicki Burt, Don Malec, PhD

Maternal and Child Health Bureau, Health Resources and Services Administration

  • Bonnie Strickland, PhD, Michael Kogan, PhD, Mary Kay Kenney, PhD, Marie Mann, MD

Office of Rural Health Policy, Health Resources and Services Administration

  • Aaron Fischbach, Curt Mueller, PhD, Michelle Goodman, Tom Morris, Michael McNeely, Sarah Bryce

Target Population Interviews


  • Judith Bradford, PhD, The Fenway Institute
  • Gary Gates, PhD, UCLA School of Law’s Williams Institute
  • Stewart Landers, JD, John Snow, Inc.
  • Harvey Makadon, MD, National LGBT Health Education Center, The Fenway Institute
  • Shane Snowdon, Human Rights Campaign

Asian Americans

  • Priscilla Huang, JD, Asian & Pacific Islander American Health Forum
  • Latha Palaniappan, MD, Palo Alto Medical Foundation
  • Marguerite Ro, DrPH, Public Health Dept., Seattle and King County, WA
  • Chau Trinh-Shevrin, DrPH, Center for the Study of Asian American Health, Department of Medicine, NYU

Adolescents with Autism Spectrum Disorders

  • Debra Lotstein, MD, UCLA School of Medicine
  • Margaret (Peggy) McManus, National Alliance to Advance Adolescent Health
  • Megumi Okumura, MD, UCSF School of Medicine
  • Julie Lounds Taylor, PhD, Vanderbilt University School of Medicine

Individuals Living in Rural Areas

  • Amy Brock-Martin, DrPH, South Carolina Rural Health Research Center
  • David Hartley, PhD, University of Southern Maine
  • Erika Ziller, PhD, University of Southern Maine
  • Ira Moscovice, PhD, University of Minnesota
  • Keith Mueller, PhD, University of Iowa

Table I.2. Limitations of National Surveys for Small Populations

Population General Problem: Small n relative to frame General Problem: Lack of approaches to increase sample Frame Problem:* Telephone number frame Frame Problem:* Area frame samples Data Collection Problem: Unit nonresponse Data Collection Problem: Item nonresponse Data Collection Problem: Instrumen-tation
* These frame problems refer to specific challenges to constructing sampling frames based on telephone numbers or geographic areas. See the “Limitations in Survey Data” section for more information on general problems obtaining an adequate frame for small sample size groups relative to the rest of the population.

Asian Americans
















Adolescents on the autism spectrum








Rural populations








Table I.3. The Ability of Key National Surveys to Study Four Target Populations

Data Set Avail-ability Sample Size Population #1 Race Population #1 Ethnicity/Nativity Population #2 Sexual Orientation/Behavior Population #3 Health/Disability Status Population #4 Geographic Identifier

Current Population Survey (CPS)


2011, 19-64: 121,520

White, Black, American Indian /Aleut /Eskimo, Asian, Hawaiian /Pacific Islander, and two or more races. Asian can be further classified into subgroups.

Hispanic origin (detailed), birthplace (state or country), mother’s birthplace, father’s birthplace, year of immigration, citizenship status


Self-reported health status, work disability, activity/functional limitations

State identifier; metro status; metro area identifier; some counties identified

American Community Survey (ACS)

Years with health insurance question: 2008-2011

2010, 19-64: 1,806,189

White, Black, American Indian or Alaska Native, Asian Indian, Chinese, Filipino, Korean, Vietnamese, Japanese, Other Asian or Pacific Islander, Other Race, two major races, three or more major races

Hispanic origin (detailed), birthplace (state or country), parent’s birthplaces, ancestry, year of immigration, year naturalized, citizenship status, language spoken at home, English fluency


Activity/functional limitations, work disability

State, super-PUMA, PUMA, metro status, metro area, Appalachian region, county sample drawn from

National Health Interview Survey (NHIS)


2010, 19-64: 54,177 full file; 21,396 sample adults

White, Black, American Indian, Alaska Native, Asian (subgroups: Chinese, Japanese, Vietnamese, Filipino, Asian Indian, Korean, other), Native Hawaiian or other Pacific Islander (Guamanian, Samoan, other). Asians were oversampled in the 2006-2009 surveys.

Hispanic ethnicity (detailed), number of years in U.S., citizenship status, global region of birth

Starting in 2013:

See NHIS documentation: Various health status, health condition, activity limitation, and health behavior variables

Region identifiers on public use; access to Census tract/block level and state identifiers at RDC

Medical Expenditure Panel Survey (MEPS)


2010, 19-64: 21,596

Race/ethnicity data collected during the NHIS interview are available (MEPS draws sample from persons interviewed in prior NHIS survey).

Hispanic ethnicity (detailed), born in U.S., number of years in U.S., citizenship status


See MEPS documentation: Self-reported health status, health condition, activity limitation, and health behavior variables

Region only on public use; access to more detailed level at RDC

SLAITS-National Survey of Children with Special Health Care Needs

July 2009 - March 2011;

2009-11, 0-17: 40,242 detailed CSHCN interviews

White, Black, other, multiple (In some states, Hawaiian/PI, Asian, American/Alaskan Native can be identified)

Hispanic ethnicity, citizenship, child born in U.S. and number of years, parents born in U.S. and number of years


See documentation: health condition/limitation/disability; behavioral, developmental, and emotional health variables; special health care needs

State, MSA status

National Health and Nutrition Examination Survey (NHANES)


2009-10, 19-64: 4,861

White, Black, American Indian/Alaska Native, Asian, Native Hawaiian/Pacific Islander, other. Respondents asked to classify themselves as Asian Indian, Chinese, Filipino, Korean, Vietnamese, Japanese, Other Asian or Pacific Islander

Hispanic ethnicity, country of birth, citizenship status, length of time in U.S.

Yes: Cognitive testing report:

See documentation: Medical examination data, health status, health conditions, behavioral health, etc…


National Survey of Family Growth


2006-2010: ~10,000 men and 12,000 women, 15-44 years old

White, Black, Hispanic, Asian, Pacific Islander

Hispanic ethnicity (Mexican vs. all other)

Sexual identity and

Men’s and women’s health as related to family life, marriage and divorce, pregnancy, infertility, use of contraception.

The geographic scope of the study is national. Detailed geographic identifiers are available on the restricted access contextual data file.

Behavioral Risk Factor Surveillance System (BRFSS)


2010, 19-64: 292,502

White, Black, Hispanic, American Indian or Alaska Native, and Asian or Pacific Islander

Hispanic ethnicity

About 19 states have had a question one time or other, but not necessarily every year. In 2014 there is an approved optional module on sexual orientation and gender identity.

Self-reported health status, condition specific measures, diet, physician activity, functional limitations

State (typically), MSA

National Survey on Drug Use and Health (NSDUH)



White, Black, Hispanic, American Indian or Alaska Native, Native Hawaiian, other Pacific Islander, Chinese, Filipino, Japanese, Korean, Indian, Vietnamese, other Asian

Hispanic ethnicity

1996: “During the past 12 months, have you had sex with only males, only females, or with both males and females?”  

Currently testing 2 questions on sexual orientation to be added in 2015204

Drug and alcohol use, health care use, health conditions, mental health, health insurance

State (typically), urban/rural

National Immunization Survey


2010: 17,004

White, Black/African American, American Indian, Alaska Native, Asian, Native Hawaiian, Pacific Islander, Other

Hispanic, Mexican, Mexican-American, Central American, South American, Puerto Rican, Cuban/Cuban American, Spanish-Caribbean, Other Spanish/Hispanic



National, State, and selected large urban areas

SLAITS - Survey of Adult Transition and Health

2001, 2007


N/A (“derived”?)



Self-reported health status, disability, special health care needs, activity limitations,

State, region, MSA

SLAITS - National Survey of Children’s Health

2003, 2007-2008, 2011-2012

2011-2012: 91800

White/Caucasian, Black/African-American, American Indian/Native American, Alaska Native, Asian, Native Hawaiian, Pacific Islander, Other



Various disabilities and conditions, including autism, Asperger’s disorder, pervasive developmental disorder, or autism spectrum disorder

State, MSA

Medicare Current Beneficiary Survey


16,000 per year

American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, White, Some Other Race. More granular racial/ethnic categories will be added in 2014.



Self-reported general health, functional limitations


National Latino and Asian American Study


2,554 Latinos and 2,095 Asian Americans

Chinese, Vietnamese, Filipino, Other Asians (others subpopulations collected but too small for subgroup analysis)

Puerto Rican, Cuban, Mexican, Other Latinos


Various psychiatric disorders


National Longitudinal Study of Adolescent Health (Add Health)

1994-95, 1996, 2001-02, 2007-08

2008: 15,701



Same-sex relationships, sexual behavior

Self-reported health status and physical exam


National Adult Tobacco Survey



Non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, non-Hispanic other (including American Indian or Alaska Native, Native Hawaiian or Pacific Islander, multiracial, or some other race)


Heterosexual-straight; esbian, gay, bisexual, or transgender (LGBT); or not specified.

A new version of this survey is in the field that no longer captured transgender after 2010.

General health, cigarette smoking, other tobacco use,smoke, cessation, secondhand chronic diseases

National, State

Table I.4. Estimated Percentage of People by Sexual Orientation and Behavior from Selected Federal and Non-Federal Sample Surveys

This table does not display the most recent estimates, but rather is presented to illustrate how federal and non-federal survey-based estimates of numbers of lesbian, gay, bisexual, and transgender people have varied by gender, over time, and according to survey methods and question wording. For more discussion, see the “Population #2: Lesbian, Gay, Bisexual, and Transgender People” section in Part I.



Percent of Men Identifying as Homosexual, Gay, Lesbian, or Bisexual

Percent of Women Identifying as Homosexual, Gay, Lesbian, or Bisexual

Percent of Men Reporting Same-Sex Partners

Percent of Women Reporting Same-Sex Partners

Percent of Men Reporting Some Same-Sex Desire or Attraction

Percent of Women Reporting Some Same-Sex Desire or Attraction

Notes: Estimates are based on small sample sizes, resulting in large confidence intervals around the estimates; see the text for details. Also, differences in estimates can occur because of sampling error (that is, the estimates in the table are based on probability samples) and nonsampling error, errors due to differential nonresponse and coverage, differences in the target population (the cohorts surveyed), differences in the survey questionnaires used, year of implementation, mode of administration, and the survey respondent.

ORIGINAL SOURCE: Institute of Medicine. “The Health of Lesbian, Gay, Bisexual, and Transgender People.” March 31, 2011.

Table Sources: Herbenick et al. (2010), Table 1, for results from the NSSHB; Gates (2010), Figures 1 and 7, for results from the GSS; Mosher et al. (2005), Tables 12 and 13, for results from the NSFG; Laumann et al. (1994a), Table 8.2, for results from the 1992 NHSLS.

National Survey of Sexual Health and Behavior, 2010




General Social Survey, 2008




General Social Survey, 2008

18 - 44





National Survey of Family Growth, 2002

18 - 44







National Health and Social Life Survey, 1992

18 - 59







Table I.5. Common Rural Taxonomies Used by the Federal Government



Urban Definition (rural is what’s left)


Source: Summarized from Hart 2005.205

OMB Metropolitan and Nonmetropolitan Taxonomy


Defines metropolitan areas as counties with 1 or more urbanized area (based on population size) and counties economically tied to that core, measured by commuting to work.

County boundaries may over- or under-bound urban core

USDA Economic Research Service Urban Influence Codes (UIC)


Builds on OMB metro and nonmetro dichotomy to create continuum based on population size and adjacency/nonadjacency to metro counties

Frequently used for research but not for federal or state policy

Census Bureau Rural and Urban Taxonomy


Urban clusters based on population size

Limited health-related data available at the census tract level, which is not stable over census years

Rural/Urban Commuting Area Taxonomy (RUCA)


Based on work commuting flows

Difficult to link to health data, often collected at the county or zip code level. A zip-code based version has been developed for this purpose, but is complex to use.

Table I.6. Potential Areas for Further Research




Health Issue

Challenges in Studying with Existing Federal Survey Data

Asian subpopulation

Vietnamese women

Cervical cancer

Difficulty disaggregating Vietnamese women and self-report of cervical cancer diagnosis



Difficulty disaggregating Filipino and self-report of diabetes diagnosis

Lesbian, Gay, Bisexual, Transgender

Lesbian women


Limited data collected on sexual identity and self-reported weight

LGBT Youth

Mental health

Limited data collected on sexual identity or potential unwillingness to respond to survey questions around mental health



Access to care

Language barriers prevent adequate representation

Autism spectrum disorders

Adolescents in transition to adulthood

Transition to adulthood

Lack of longitudinal data and inconsistent definitions of disability between children and adulthood


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