Summary
The goal of eliminating disparities in health care in the United States remains elusive. The findings of the
National Healthcare Disparities Report reveal that even as quality improves on specific measures, disparities often
persist (AHRQ, 2008a, 2008b). Addressing these disparities must begin with the fundamental step of bringing
the nature of the disparities and the groups at risk for those disparities to light by collecting health care quality
information stratified by race, ethnicity and language data. Then attention can be focused on where interventions
might be best applied, and on planning and evaluating those efforts to inform the development of policy and the
application of resources. A lack of standardization of categories for race, ethnicity, and language data has been
suggested as one obstacle to achieving more widespread collection and utilization of these data. Many types of
entities participate in initiatives to improve the quality of health care; health plans, hospitals, other providers, and
health systems can and should obtain race, ethnicity, and language data so these data can be used to identify gaps
and improve care for all individuals.
The purpose of this report is to identify standardized categories for the variables of race, ethnicity, and
language that can be used to facilitate the sharing, compilation, and comparison of quality data stratified by the
standard categories. The Institute of Medicine, under a contract with the Agency for Healthcare Research and
Quality (AHRQ), Department of Health and Human Services (HHS), formed the Subcommittee on Standardized
Collection of Race/Ethnicity Data for Healthcare Quality Improvement to identify current models for collecting and
coding race, ethnicity, and language data; to ascertain the challenges involved in obtaining these data in health care
settings; and to make recommendations for improvement. The language in the statement of task (Box S-1)—"in
healthcare quality improvement" and "assess and report on quality of care"—led the subcommittee to focus its
discussion and recommendations on data collection in the domain of health care services.
Existing Guidance On Race, Ethnicity, And Language Categories
The concepts of race and ethnicity are defined socially and culturally and, in the case of federal data collection,
by legislative and political necessity (Hayes-Bautista and Chapa, 1987). With the aim of identifying important
cultural and social groups for statistical reporting and civil rights monitoring, the Office of Management and Budget
(OMB) has developed a minimum set of standardized categories for reporting on race and Hispanic ethnicity by
federal agencies and recipients of federal funds (OMB, 1977, 1997b). The five race categories are now Black or
African American, White, Asian, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander.
| Box S-1. Statement of Task: Subcommittee on Standardized Collection of
Race/Ethnicity Data for Healthcare Quality Improvement
A subcommittee of experts will report to the IOM Committee on Future Directions for the National
Healthcare Quality and Disparities Reports regarding the lack of standardization of collection of race and
ethnicity data at the federal, state, local, and private sector levels due to the fact that the federal government
has yet to issue comprehensive, definitive guidelines for the collection and disclosure of race and
ethnicity data in healthcare quality improvement. The subcommittee will focus on defining a standard set of
race/ethnicity and language categories and methods for obtaining this information to serve as a standard
for those entities wishing to assess and report on quality of care across these categories. The subcommittee
will carry out an appropriate level of detailed, in-depth analysis and description which can be included
in the overall report by the committee and as a separate stand alone report. |
OMB describes these categories as the minimum set and encourages the collection of more detailed data provided
those data can be aggregated back to the minimum categories (OMB, 1997a). Progress has been made in incorporating
these categories into the collection and presentation of data in health care settings. However, some health
care-related data collection efforts still do not employ these basic standard categories.
While OMB has not established a list of language categories, the collection of language data has been pivotal
in determining whether there has been discrimination by "national origin" under Title VI of the Civil Rights Act
of 1964,1,2 and federal policies state that "reasonable steps" need to be taken so that persons of limited English
proficiency can have "meaningful access" to programs or activities without charge for language services.3Additionally
in 2000, HHS released its National Standards on Culturally and Linguistically Appropriate Services (CLAS),
which encourage all health care organizations and individual providers "to make their practices more culturally
and linguistically accessible," including the use of race, ethnicity, and language data in program assessments and
incorporation of these data into health records and organizational management systems (HHS, 2007).
Categorizing Race And Ethnicity Data
The OMB race and Hispanic ethnicity categories represent broad population groups used for an array of statistical
reporting and analytic purposes, including health care quality assessment and identification of disparities
(AHRQ, 2008a; Cohen, 2008; Flores and Tomany-Korman, 2008; IOM, 2008; Kaiser Family Foundation, 2009).
Chapter 2 illustrates that these categories alone, however, are insufficient to illuminate many disparities and to
target quality improvement efforts where they may be most needed. Since disparities can exist within those broad
OMB categories, there is value in collecting and utilizing data incorporating more fine-grained categories than
those of OMB (Blendon et al., 2007; Jerant et al., 2008; Read et al., 2005; Shah and Carrasquillo, 2006). The
subcommittee recommends a separate question to collect data on granular ethnicity—defined as "a person's ethnic
origin or descent, 'roots,' or heritage, or the place of birth of the person or the person's parents or ancestors..."
(U.S. Census Bureau, 2008)—in addition to soliciting data in the OMB race and Hispanic ethnicity categories
(Figure S-1). Research also shows that not all individuals identify with the current OMB race categories so the
subcommittee recommends expanding the race categories to six choices by including a "Some other race" option to provide a response category for those Hispanics and others who do not relate to the current choices. Additionally,
the subcommittee favors the collection and retention for analysis of specific multiple-race combinations (i.e.,
having data on each race that an individual selects), rather than losing that detail by only offering the more general
category of "multiracial," whenever possible.
In Chapter 3, the subcommittee considers whether a national "OMB Plus" set of 10 to 15 granular ethnicity
categories, similar to the Census Bureau approach, should be identified that would be optimal for collection by
all health care entities. However, such a set would not be specific to and appropriate for the diverse communities
in which health care entities operate. Instead, the subcommittee concludes that individual entities should
select the granular ethnicity categories representative of their service population selected from a national list of
standardized categories. Whenever a limited list of categories is offered to respondents, the list should include
an open-ended response option of "Other, please specify:—" so that each individual who desires to do so can
self-identify.
Recommendation 3-1: An entity collecting data from individuals for purposes related to health and
health care should:
- Collect data on granular ethnicity using categories that are applicable to the populations it
serves or studies. Categories should be selected from a national standard list (go to Recommendation
6-1a) on the basis of health and health care quality issues, evidence or likelihood
of disparities, or size of subgroups within the population. The selection of categories
should also be informed by analysis of relevant data (e.g., Census data) on the service or
study population. In addition, an open-ended option of "Other, please specify:—" should
be provided for persons whose granular ethnicity is not listed as a response option.
- Elicit categorical responses consistent with the current OMB standard race and Hispanic
ethnicity categories, with the addition of a response option of "Some other race" for persons
who do not identify with the OMB race categories.
While several organizations provide lists of granular ethnicities (e.g., Centers for Disease Control and Prevention
[CDC]/Health Level 7 [HL7] and the Commonwealth of Massachusetts/Brookings Institution), none of these lists is
sufficient for a standard national set from which locally relevant choices could be made (CDC, 2000; Taylor-Clark
et al., 2009). A merged list provides a template from which such a national standard set can be developed (go to Appendix E). When a person does not check off an OMB race or Hispanic ethnicity and provides only a granular
ethnicity response, a process for rolling granular ethnicity categories up to the OMB categories will, in some cases,
be necessary for analysis and reporting purposes. However, some ethnicities do not correspond to a single OMB
race category, necessitating a "no determinate OMB race classification" for analytic purposes (go to Appendix F).
Recommendation 3-2: Any entity collecting data from individuals for purposes related to health
and health care should collect granular ethnicity data in addition to data in the OMB race and
Hispanic ethnicity categories and should select the granular ethnicity categories to be used from a
national standard set. When respondents do not self-identify as one of the OMB race categories or
do not respond to the Hispanic ethnicity question, a national scheme should be used to roll up the
granular ethnicity categories to the applicable broad OMB race and Hispanic ethnicity categories
to the extent feasible.
Eliciting accurate and reliable race, Hispanic ethnicity, and granular ethnicity data depends on the ways in
which the questions are asked, the instructions provided to respondents (e.g., "Select one or more"), and the format
of the questions (i.e., OMB one-question versus two-question format). This latter issue is especially relevant to
how Hispanic populations self-identify. Pilot projects and further study are necessary to confirm the best ways to
collect accurate data that are useful for health care quality improvement.
Recommendation 3-3: To determine the utility for health and health care purposes, HHS should
pursue studies on different ways of framing the questions and related response categories for collecting
race and ethnicity data at the level of the OMB categories, focusing on completeness and
accuracy of response among all groups.
- Issues addressed should include use of the one- or two-question format for race and Hispanic
ethnicity, whether all individuals understand and identify with the OMB race and
Hispanic ethnicity categories, and the increasing size of populations identifying with "Some
other race."
- The results of such studies, together with parallel studies by the Census Bureau and other
agencies, may reveal the need for an OMB review across all agencies to determine the best
format for improving response among all groups.
Improving The Collection Of Data On Language
Compelling evidence exists that having limited English proficiency (LEP) affects the delivery and quality of
health care and can result in significant disparities in access to care (Hu and Covell, 1986; Weinick and Krauss,
2000), a decreased likelihood of having a usual source of care (Kirkman-Liff and Mondragon, 1991; Weinick and
Krauss, 2000), an increased probability of receiving unnecessary diagnostic tests (Hampers et al., 1999), more
serious adverse outcomes from medical errors (Divi et al., 2007), and more drug-related complications (Gandhi
et al., 2000). To achieve safe, effective, patient-centered communication, attention must be paid to the language
needs of patients, as addressed in Chapter 4.
Language Questions
Assessing each individual's language need is an essential first step toward ensuring effective health care
communication. The subcommittee concludes that spoken language need can best be assessed by asking two
questions: one aimed at determining whether an individual speaks English less than very well and a second aimed
at identifying the individual's preferred spoken language during a health care encounter (Figure S-1). Having this
information for each individual allows its use to ensure the quality of services in subsequent encounters, in analysis
of health care disparities, and in system-level planning (e.g., determining the need for interpreters and matching
patients to language-concordant providers).
The subcommittee establishes a hierarchy among the possible language questions, with questions about English
proficiency and preferred spoken language identified as a higher priority than questions on language spoken at
home or on preferred language for written materials. On average, 55 percent of those who speak another language
at home speak English very well (Shin and Bruno, 2003), but asking about language spoken at home helps provide
a window into the health beliefs and practices of the home environment. The correlation between those who need
spoken and written language assistance appears to be high in many settings.
Recommendation 4-1: To assess patient/consumer language and communication needs, all entities
collecting data from individuals for purposes related to health and health care should:
- At a minimum, collect data on an individual's assessment of his/her level of English proficiency
and on the preferred spoken language needed for effective communication with
health care providers. For health care purposes, a rating of spoken English-language proficiency
of less than very well is considered limited English proficiency.
- Where possible and applicable, additionally collect data on the language spoken by the
individual at home and the language in which he/she prefers to receive written materials.
When the individual is a child, the language need of the parent/guardian must be determined. Similarly, if an adult
has a guardian/conservator, that individual's language need must be assessed.
Languages in Use
More than 600 languages are in use in the United States although a smaller number may be in use in health
care contexts. In Chapter 4 the subcommittee evaluates options for determining what language categories entities
should use for data collection (e.g., a uniform set for all entities, percentage or numerical thresholds based on the
presence of languages in a service area, or local choice). Local choice informed by data on the languages spoken
most frequently in the service area by persons with LEP is the preferred option. A single list does not suit all areas
given that the top non-English languages vary greatly from area to area (for instance, Spanish is in the top 10 languages
in 3,122 of 3,141 counties in the United States, while Turkish is in the top 10 in 12 counties, Laotian in 125,
Navaho in 74, SerboCroatian in 58, and Portuguese in 229) (U.S. English Foundation, 2009). The aim is to have data
on each individual's specific language need, but when an entity designs its collection instruments, whether paper or
electronic, it may, because of space considerations, have to use a limited number of response categories. Therefore,
such a response list should always include an "Other, please specify:___" option. Some electronic data collection
systems are more sophisticated, and by using keystroke recognition can accommodate hundreds of languages.
Recommendation 4-2: The choice of response categories for spoken and written language questions
should be informed by analysis of relevant data on the service area (e.g., Census data) or service
population, and any response list should include an option of "Other, please specify:___" for persons
whose language is not listed.
The subcommittee has developed a template of languages used in the United States based on Census data and
the experiences of certain health care providers. This template can serve as a basis for the national standard set
called for in recommendations in Chapter 6 (go to Appendix I for template). A uniform set of codes can facilitate
sharing of data. Two possible language coding systems already exist (the Census and International Organization
for Standardization [ISO] code sets) (SIL International, 2009; U.S. Census Bureau, 2007).
Recommendation 4-3: When any health care entity collects language data, the languages used as
response options or categories for analysis should be selected from a national standard set of languages
in use in the United States. The national standard set should include sign language(s) for
spoken language and Braille for written language.
Improving Data Collection Across The Health Care System
As discussed in Chapter 5, while each of the entities involved in the nation's health care system has some
capability for the collection of race, ethnicity, and language data, some are better positioned than others to collect
these data through self-report, the generally agreed-upon best way to define a person's racial and ethnic identity.
In the future, information infrastructure may enable integrated data exchange so that all entities will not need to
collect all data. For now, however, all health and health care entities have roles to play in collecting these data
directly from individuals. Hospitals, community health centers, physician practices, health plans, and local, state,
and federal agencies can all identify next steps toward improving or implementing direct data collection by understanding
the unique contexts in which they operate. Across all these entities, these data must be collected and stored
responsibly. Training of staff, upgrades to health information technology (Health IT) systems, and communication with
patients and enrollees are potential avenues for improved data collection and building of trust.
In the subcommittee's proposed framework, optional categories are offered (e.g., declined, unavailable,
unknown, self-reported, observer-reported); these are not for patient response, but for tracking the portion of the
patient population for which an entity has been able to collect data or the nature of the data collection. Until directly
collected data are sufficient for analytic and quality improvement purposes, indirect estimation of race and ethnicity
through techniques such as geocoding and surname analysis is useful for bridging data gaps.
Recommendation 5-1: Where directly collected race and ethnicity data are not available, entities
should use indirect estimation to aid in the analysis of racial and ethnic disparities and in the development
of targeted quality improvement strategies, recognizing the probabilistic and fallible
nature of such indirectly estimated identifications.
- Race and ethnicity identifications based on indirect estimation should be distinguished from
self-reports in data systems, and if feasible, should be accompanied by probabilities.
- Interventions and communications in which race and ethnicity identifications are based on
indirect estimation may be better suited to population-level interventions and communications
and less well suited to use in individual-level interactions.
- An indirectly estimated probability of an individual's race and ethnicity should never be
placed in a medical record or used in clinical decision making.
- Analyses using indirectly estimated race and ethnicity should employ statistically valid
methods that deal with probabilistic identifications.
Implementing Collection of Standardized Data
Now is an opportune time for action on standardization of the categories used to collect race, ethnicity, and
language data. Efforts to share and evaluate quality data across states, regions, or payers would be facilitated by
standardized categories.
HHS is a prime locus of the subcommittee's recommendations in Chapter 6 for implementation of improved
collection of standardized data because of its focus on resolving health and health care disparities and its history
of promoting the collection of race, ethnicity, and language data to ensure compliance with applicable statutes
and regulations. National development of standardized categories and coding by HHS, along with a responsive
updating process, would relieve each state and entity of having to develop its own set of categories and coding
scheme, which could be incompatible with others. The subcommittee templates of categories along with an updated
CDC/HL7 Code Set can form the basis for standardized race, Hispanic ethnicity, and granular ethnicity data while
a determination will have to be made on coding for languages.
Recommendation 6-1a: HHS should develop and make available national standard lists of granular
ethnicity categories and spoken and written languages, with accompanying unique codes and rules
for rollup procedures.
- HHS should adopt a process for routine updating of those lists and procedures as necessary.
Sign languages should be included in national lists of spoken languages and Braille in lists
of written languages.
- HHS should ensure that any national hierarchy used to roll up granular ethnicity categories
to the broad OMB race and Hispanic ethnicity categories takes into account responses
that do not correspond to one of the OMB categories.
Standardization would support achievement of the goal set forth in the American Recovery and Reinvestment
Act of 20094 (ARRA) of having a national electronic health record (EHR)5 for each individual by 2014
that incorporates collection of data on the person's race, ethnicity, and primary language. Having the standards
adopted by the other components of the health care industry, including the makers of Health IT systems, would help
ensure that a sufficient set of data fields are available to accommodate each element recommended for collection
by the subcommittee.
Recommendation 6-1b: HHS and the Office of the National Coordinator for Health Information
Technology (ONC) should adopt as standards for including in electronic health records the variables
of race, Hispanic ethnicity, granular ethnicity, and language need identified in this report.
Recommendation 6-1c: HHS and ONC should develop standards for electronic data transmission
among health care providers and plans that support data exchange and possible aggregation of
race, Hispanic ethnicity, granular ethnicity, and language need data across entities to minimize
redundancy in data collection.
Performance incentive programs tend not to be designed with reduction of disparities in mind, yet can have
positive or negative effects on disparities in health care and on underresourced primary care safety net providers
(Chien et al., 2007; Rust and Cooper, 2007; Williams, 2009). The subcommittee does not take a stand on whether
incentive payments in Health IT programs should exist, but when they do exist, the collection of race, ethnicity, and
language data would be one activity for which positive incentives should be offered.
Recommendation 6-1d: The Centers for Medicare and Medicaid Services (CMS), as well as others
sponsoring payment incentive programs, should ensure that the awarding of such incentives takes
into account collection of the recommended data on race, Hispanic ethnicity, granular ethnicity,
and language need so these data can be used to identify and address disparities in care.
Numerous past and present legislative and policy efforts stress the importance of collecting race, ethnicity,
and language data in federal programs. HHS administers programs supporting the health care delivery system to
provide care to persons at risk of receiving suboptimal care, and these programs present opportunities to influence
the quality of care delivered to millions of Americans. Because the subcommittee's charge relates to health
care, the following recommendation focuses on the HHS programs that deliver health cares services, pay for those
services through insurance mechanisms, or administer surveys that increase knowledge on health care needs and
outcomes. The Secretary, however, may find it useful to extend the standardized approach of this report to other
HHS health-related programs or other data gathering activities.
Recommendation 6-1e: HHS should issue guidance that recipients of HHS funding (e.g., Medicare,
the Children's Health Insurance Program [CHIP], Medicaid, community health centers) include
data on race, Hispanic ethnicity, granular ethnicity, and language need in individual health records
so these data can be used to stratify quality performance metrics, organize quality improvement
and disparity reduction initiatives, and report on progress.
Having quality-of-care information from large federal delivery systems such as the Department of Veterans
Affairs, the Department of Defense, and other federally funded programs, such as community health centers, stratified
by the same variables and categories recommended in this report would provide rich sources for comparative
analysis.
Recommendation 6-2: HHS, the Department of Veterans Affairs, and the Department of Defense
should coordinate their efforts to ensure that all federally funded health care delivery systems collect
the variables of race, Hispanic ethnicity, granular ethnicity, and language need as outlined in
this report, and include these data in the health records of individuals for use in stratifying quality
performance metrics, organizing quality improvement and disparity reduction initiatives, and
reporting on progress.
Accreditation organizations and other professional and standards-setting bodies can play a key role in fostering
the collection of race, ethnicity, and language data. Hospitals, health plans, and physicians have reported that a
lack of standardization has been a barrier to using these data in quality improvement efforts (Bilheimer and Sisk, 2008; Lurie et al., 2008; NCQA, 2009; Siegel et al., 2008). The Joint Commission, the National Committee for
Quality Assurance (NCQA), and URAC have developed CLAS-like standards for their organizational reviews.
Formerly known as the Utilization Review Accreditation Commission.
The National Quality Forum (NQF) encourages the collection of race, ethnicity, and language data in accordance
with the Health Research & Educational Trust (HRET) Toolkit (NQF, 2008); the subcommittee's recommendations
include modifications to that toolkit. The American Medical Association, the National Medical Association,
and the National Hispanic Medical Association's Commission to End Health Care Disparities have reaffirmed
their collective commitment to bringing an end to health care disparities by increasing awareness in the physician
community and promoting better data collection (AMA, 2005, 2009).
Recommendation 6-3: Accreditation and standards-setting organizations should incorporate the
variables of race, Hispanic ethnicity, granular ethnicity, and language need outlined in this report
and associated categories (as updated by HHS) as part of their accreditation standards and performance
measure endorsements.
- The Joint Commission, NCQA, and URAC should ensure collection in individual health
records of the variables of race, Hispanic ethnicity, granular ethnicity, and language
need as outlined in this report so these data can be used to stratify quality performance
metrics, organize quality improvement and disparity reduction initiatives, and report on
progress.
- NQF should review and amend its recommendations on the collection and use of data on
race, Hispanic ethnicity, granular ethnicity, and language need to accord with the categories
and procedures outlined in this report.
- Medical societies and medical boards should review and endorse the variables, categories,
and procedures outlined in this report and educate their members on their use for quality
improvement.
States have an opportunity to shape the level of detail of race, ethnicity, and language data collected in their
programs whether for use in reporting on quality measures by insurance programs, in disease registries, in hospital
discharges, in health care surveys, in patient safety reporting, or in other activities. Through Medicaid and CHIP
programs, states have leverage with managed care organizations and providers to require collection of the recommended
data and their use in quality improvement. Medicaid provides coverage for a large portion of minority
groups, and states have an interest in ensuring that the population covered is receiving appropriate quality care
(Angeles and Somers, 2007).
Recommendation 6-4: Through their certification, regulation, and monitoring of health care providers
and organizations within their jurisdiction, states should require the collection of data on the
race, Hispanic ethnicity, granular ethnicity, and language need variables as outlined in this report
so these data can be used to stratify quality performance metrics, organize quality improvement
and disparity reduction initiatives, and report on progress.
Conclusion
Efforts are under way to establish national standards for health care technology, performance measurement, and
data aggregation and exchange that complement local data collection and experiences with performance improvement
and reporting (Roski, 2009). To date, it has been difficult to either combine or compare performance data
stratified by race, ethnicity, or language need across payment and delivery systems, which has limited the utility
of such data for assessing the performance of the health system as a whole or in specific geographic regions with
respect to disparities. Yet, these analyses have implications for the design of appropriate interventions by federal,
state, and local policy makers and health care plans and providers.
Standardization of the categories used to collect these data would promote greater comparability of patientfocused
data collected directly by care providers or health plans, or, for instance, transferred from providers to
multiple plans. Standardization would also eliminate the need for all health care entities to develop their own
categorization schemes. Still, additional resources and leadership at the local, state, and national levels will be
required to implement these recommendations. Although broad application of EHRs will take a number of years,
the data collection issues for current systems do not differ significantly from those involved in future EHR applications,
so providers could institute today the processes for the capture and sharing of race, ethnicity, and language
data proposed in this report.
There is strong evidence that the quality of health care varies by race, ethnicity, and language. Quality metrics
stratified by race, Hispanic ethnicity, granular ethnicity and language need can inform point-of-care services,
application of resources, and decisions in patient-provider interactions in ways that can assist in improving overall
quality and reducing disparities.
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1 The Civil Rights Act of 1964, Public Law 88-352, 78 Stat. 241, 88th Cong., 2nd sess. (July 2, 1964).
2 Lau v Nichols, 414 U.S. 563 (1974).
3 Improving Access to Services for Persons with Limited English Proficiency, Executive Order 13166, August 11, 2000.
4 American Recovery and Reinvestment Act of 2009, Public Law 111-5 §3002(b)(2)(B)(vii), 111th Cong., 1st sess. (February 17, 2009).
5 In this document, EHR means a patient record owned and maintained by a provider entity; a personal health record is a medical or health
record owned and maintained by a patient him- or herself.
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