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

09/01/2013

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

LGBT

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	X	X		X	X		X
LGBT	X	X				X	X
Adolescents on the autism spectrum	X	X			X	X	X
Rural populations	X	X	X	X	X		X

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)	19xx-2011	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	N/A	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	N/A	Activity/functional limitations, work disability	State, super-PUMA, PUMA, metro status, metro area, Appalachian region, county sample drawn from
National Health Interview Survey (NHIS)	1997-2011	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: http://www.hhs.gov/news/press/2011pres/06/20110629a.html	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)	19xx-2010	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	N/A	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	N/A	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)	1999-2012	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: http://www.cdc.gov/NCHS/nhanes/variable_tables/sexual_behavior.htm Cognitive testing report: http://wwwn.cdc.gov/qbank/report/Miller_NCHS_2001NHANESSexualityReport.pdf	See documentation: Medical examination data, health status, health conditions, behavioral health, etc…	National
National Survey of Family Growth	2006-2010	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 attraction: http://www.cdc.gov/nchs/nsfg/abc_list_s.htm#sexualorientationandattraction	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)	1995-2011	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)	1994-2011	~60,000	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	1994-2012	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	N/A	N/A	National, State, and selected large urban areas
SLAITS - Survey of Adult Transition and Health	2001, 2007	1,865	N/A (“derived”?)	Hispanic	N/A	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	Hispanic	N/A	Various disabilities and conditions, including autism, Asperger’s disorder, pervasive developmental disorder, or autism spectrum disorder	State, MSA
Medicare Current Beneficiary Survey	1991-	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.	Hispanic	N/A	Self-reported general health, functional limitations	National
National Latino and Asian American Study	2002-2003	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	N/A	Various psychiatric disorders	National
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	2009-2010	118,581	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)	Hispanic	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.

Survey	Ages	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. http://www.iom.edu/Reports/2011/The-Health-of-Lesbian-Gay-Bisexual-and-Transgender-People.aspx 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	18+	6.8	4.5	—	—	—	—
General Social Survey, 2008	18+	2.9	4.6	—	—	—	—
General Social Survey, 2008	18 - 44	4.1	4.1	10.0	10.0	—	—
National Survey of Family Growth, 2002	18 - 44	4.1	4.1	6.2	11.5	7.1	13.4
National Health and Social Life Survey, 1992	18 - 59	2.8	1.4	7.1	3.8	7.7	7.5

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

Taxonomy	Unit	Urban Definition (rural is what’s left)	Limitation
Source: Summarized from Hart 2005.²⁰⁵
OMB Metropolitan and Nonmetropolitan Taxonomy	Counties	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)	Counties	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	Census-tract	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)	Census-tract	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

Population	Subpopulation	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
Asian subpopulation	Filipino	Diabetes	Difficulty disaggregating Filipino and self-report of diabetes diagnosis
Lesbian, Gay, Bisexual, Transgender	Lesbian women	Obesity	Limited data collected on sexual identity and self-reported weight
Lesbian, Gay, Bisexual, Transgender	LGBT Youth	Mental health	Limited data collected on sexual identity or potential unwillingness to respond to survey questions around mental health
Rural	Minorities	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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The Feasibility of Using Electronic Health Data for Research on Small Populations. Appendix to Part I

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