Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement

6. Implementation (continued)

Standards-Setting and Professional Organizations

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 collecting these data for quality improvement efforts (Bilheimer and Sisk, 2008; Lurie et al., 2008; NCQA, 2009; Siegel et al., 2008).

Joint Commission, NCQA, and URAC

Accrediting organizations such as the Joint Commission, National Committee for Quality Assurance (NCQA), and URAC14 either have developed or are developing CLAS-like standards for their accreditation reviews or for voluntary self-analysis by organizations. These standards do not always cover all demographic variables (e.g., those of the Joint Commission cover language and communication needs but not race or ethnicity), or they may not go beyond requiring the collection of demographic data, leaving the use of those data for performance improvement optional (The Joint Commission, 2008; NCQA, 2008a; URAC, 2007).

For many years, the Joint Commission's accreditation standards for hospitals and other accredited entities (including, for example, those providing ambulatory health care, behavioral health care, home care, and hospice care) have required that patients' culture, ethnicity, race, and religious preferences and needs be respected and that their communication needs be met. To facilitate this patient-centered approach, in 2005 the Joint Commission proposed a standard that would have required documentation in each patient's health record of the patient's race, ethnicity, and language and other communication needs. The response from the field, while supportive of recording this information for each patient, argued that unless race and ethnicity data were recorded in standardized categories, their use for performance improvement would be limited. In light of this feedback, in January 2006 the Joint Commission began requiring that language and other communication needs be recorded in each patient's record, but it delayed requiring recording of race and ethnicity until a widely accepted standardized approach became available. As of this writing, the Joint Commission is again proposing a requirement that race and ethnicity be recorded and that these data be used in planning services to meet the needs of persons in the community and in performance improvement (The Joint Commission, 2009). The Joint Commission anticipates the response the field to be that standardized categories are needed.15

At this point, NCQA is planning to address CLAS as a voluntary accreditation module, to be available in 2010. It is expected that the module will address the use of race, ethnicity, and language data in stratifying quality performance data to identify both disparities in health care and problems in meeting language needs, as well as the use of those findings to drive quality improvement. Currently, NCQA has a program that rewards health plans for demonstrating innovative practices in providing for culturally and linguistically appropriate services (NCQA, 2006, 2007, 2008b). Previously, NCQA, with funding from The California Endowment, provided grants and technical assistance to small physician practices serving minority populations to learn about their needs for conducting and sustaining quality improvement activities. As a result of this initiative, the need for standardized collection of race, ethnicity, and language data in EHR systems was brought to light (NCQA, 2009).

National Quality Forum (NQF)

NQF is a membership organization whose mission is to "promote a common approach to measuring health care quality and fostering system-wide capacity for quality improvement" through endorsement of consensus standards (NQF, 2009). NQF recently released a framework for culturally and linguistically responsive services and encourages the collection of race, ethnicity, and language data in accordance with the Hospital Research & Education Trust (HRET) Toolkit (NQF, 2008). The subcommittee has suggested changes to elements of the HRET Toolkit, in particular incorporating separate collection of a granular ethnicity variable, adding "Some other race" to the Office of Management and Budget (OMB) category set, and having a more expansive list of language categories. The subcommittee also favors the collection and retention for analysis of specific multiple-race combinations (i.e., having data on each race that an individual selects when given the option to select one or more races), rather than losing that detail by only offering patients the more general response option of "multiracial" as delineated in the Toolkit.

Commission to End Health Care Disparities

A collaborative partnership involving the medical community, the American Medical Association (AMA), the National Medical Association, and the National Hispanic Medical Association's Commission to End Health Care Disparities brings together 35 state and specialty medical societies. As a group, they have reaffirmed their collective commitment to ending disparities in health and health care by taking steps to (AMA, 2009b):

  • Increase awareness of disparities in their own practices within the physician community.
  • Promote better data collection.
  • Promote workforce diversity.
  • Increase education and training.

The Commission is considering continuing medical education activities and exploration of core curriculum on health disparities for medical students that might be considered a criterion for medical school accreditation. The Commission also notes that race, ethnicity, and language proficiency data should be utilized for clinical quality performance measurement, with disparities an appropriate area for the Physician Consortium for Performance Improvement to focus its efforts (AMA, 2009a).

The AMA Code of Ethics guides physicians to examine their practices to ensure that differences in care are based on clinical necessity or patient preference and do not constitute inequitable treatment. The code also states that physicians should take steps to minimize language barriers so as to enhance both patient and physician understanding of medical needs (AMA, 2005). Collection of race, ethnicity, and language data would allow stratification of quality measures in physician practices to create awareness of differential practice patterns or response among patient populations and accordingly identify opportunities for quality improvement. The ARRA provision for "meaningful use" of EHRs applies to enabling the exchange of health information and reporting on clinical quality measures to CMS, medical boards, private plans, and others. Medicare staff observed that CMS sees "in legislation and in operation, . a future for measuring quality in physician offices" (McGann, 2009). CMS sponsors quality improvement research projects at the practitioner level, such as the Generating Medicare Physician Quality Performance Measurement Results (GEMS) program which tracked 12 HEDIS (Healthcare Effectiveness Data and Information Set) ambulatory care measures in a physician group practice fee-for-service environment using an amalgam of Part A, B, and D claims data and race and ethnicity data from the enrollment database (McGann, 2009; Reilly, 2009a). Having race, ethnicity, and language data for their own patients would also enable providers to review performance at the point of care (Kmetik, 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.

State Action

States have an opportunity to shape the level of detail of race, ethnicity, and language data collected in their programs by establishing which categories of granular ethnicity and language should be used in addition to the basic OMB categories of race and Hispanic ethnicity. Each state organizes its own programs into different administrative units, so no attempt is made in this report to identify all state actors that have important roles in ensuring quality improvement in health care. State health or other departments have important responsibilities related to protecting and improving the health and health care of the population statewide, and are key players in ensuring the adoption of standards and collection of data. However, providers and plans have reported that they receive conflicting data requests from different agencies within the same state. Categories for race, ethnicity, and language can be selected at the state level, with careful consideration of local as well as national stakeholder needs when categories are defined for statewide aggregation and reporting for insurance program quality measures, disease registries, birth and death vital statistics, hospital discharges, health care surveys, patient safety reporting, and other activities. State-level aggregation and reporting can help illuminate the health care issues of population groups whose disparities may not be apparent because of small sample sizes at the local level.

As large purchasers of care through Medicaid and CHIP programs, states have leverage with managed care organizations and providers. States can use this leverage to ensure that health care entities collect the recommended race, ethnicity, and language data and use findings from analyses of these data to design quality improvement efforts. Medicaid provides coverage for a large portion of minority groups; thus, states have an interest in ensuring that the population covered is receiving appropriate levels of care (Angeles and Somers, 2007). Currently, some states report their HEDIS measures by race and ethnicity, and others do not (Michigan Department of Community Health, 2009; NC Department of Health and Human Services, 2009).

The subcommittee concludes that state entities can play a central role as aggregators and disseminators of provider, plan, community, and state-level quality improvement data.

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.

Although it was beyond the scope of the subcommittee's deliberations to determine the extent of the need, representatives of state data agencies noted that one of the greatest barriers to state health departments, Medicaid agencies, and regulatory agencies in fulfilling responsibilities related to certification, regulation, and monitoring activities has been the lack of funding to expand and improve state data collection activities. The collection of race, ethnicity, and language data across providers and plans in a community and state requires resources for rulemaking, provider training, implementation of reporting, and assurance of data quality, yet many states are cutting back their data reporting initiatives, including a reduction in workforce, because of state budget limitations (NRC, 2003).16


Efforts are under way to institute national standards for technology, performance measurement, and data aggregation and exchange that complement local data collection and experiences with performance improvement and reporting (HHS, 2009c; Roski, 2009). To date, it has been difficult to either combine or compare performance data stratified by race, ethnicity, or language across payment and delivery systems, which has limited the utility of such data for assessing the performance of the health care system as a whole or in specific geographic areas with respect to disparities in care. Standardization of the categories of race, ethnicity, and language data will promote greater comparability of data collected directly by providers or health plans or, for instance, transferred from providers to plans. Estimates of health care disparities derived through indirect estimation techniques, such as geocoding and surname analysis, can provide a helpful bridge until directly collected demographic data are more universally available.

The subcommittee has proposed a framework for the collection of race, ethnicity, and language data that it believes would facilitate the collection of data by individual entities, the comparison of quality of care received by specific groups across entities and regions, and the combination of data for purposes of analyzing health care needs and identifying disparities. While important disparities in quality of care can be identified among the race and ethnicity groups captured by the OMB categories, those categories often are not sufficiently descriptive of local and state populations because of the diversity of ethnic groups in different parts of the country, states, or specific communities. A number of analyses have identified disparities among members of more granular ethnic categories that are masked by the aggregate OMB categories. More discrete population data could be used to identify opportunities for quality improvement and outreach without inappropriate or inefficient targeting of interventions to an entire broad racial or ethnic category.

The subcommittee recommends for quality improvement purposes: (1) the collection and use of data on granular ethnicity and language need, allowing local providers, communities, or states to select sets of categories from national standard lists that are most informative about the populations they serve, and (2) the continued collection of data in the OMB race and Hispanic ethnicity categories to support consistency across as many complementary data collection efforts as possible (e.g., poverty statistics, educational attainment). The national categories should be consistently coded to foster exchange among systems of like data categories across providers, states, plans, or payers for aggregation or comparison purposes. Given space constraints of paper forms or intake screens, local category lists may be limited in the number of choices; electronic collection systems can often be designed to collect many more categories than would be optimal on paper forms. The categories used should be descriptive of the population served, reflect quality issues related to the health and health care of that population, and take into account evidence or the likelihood of disparities among ethnic groups within the population. To ensure that each individual has the opportunity to self-identify and that these identifiers will be captured, there should always be an opportunity to add ethnicities and languages not contained on a list of check-off boxes. Therefore, an open-ended "Other, please specify:—" response option should be incorporated for both granular ethnicity and language when a limited list of categories is presented for response. These responses can help identify when additional categories may need to be added to prespecified lists on data collection instruments.

Many actors play a role in health care delivery and quality assessment, and each has a role to play in furthering the collection of meaningful race, ethnicity, and language data for quality improvement. National development of standardized categories 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 collection of these data in accordance with the framework proposed in this report should be reflected in guidance to recipients of HHS and state funding, incorporated into the accreditation standards and performance measurement endorsements of accreditation and standards-setting organizations, and coordinated across federal health care delivery systems.

Collecting race, ethnicity, and language data using standard categories can help promote equity through enhanced patient-provider communication and the provision of evidence-based quality care. Achieving the goals of quality care requires monitoring to ensure that all populations receive patient-centered, safe, effective, timely, efficient, and equitable care.


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1 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. The Office of the National Coordinator's definition is included in the following section on Electronic Health Records.
2 Personal communication, S. Ganesan, Centers for Disease Control and Prevention, June 3, 2009.
3 In addition to the numerical codes, the CDC/HL7 Code Set includes an alphanumeric hierarchical code that places each category in a hierarchical position related to the OMB categories of race and Hispanic ethnicity.
4 The Library of Congress is the registration authority for the ISO-639-2 codes, while SIL is the registration authority for the ISO-639-3 codes.
5 Personal communication, D. Pollack, Centers for Disease Control and Prevention, May 7, 2009.
6 Personal communication, S. Ganesan, Centers for Disease Control and Prevention, and B. Hamilton, National Center for Health Statistics, June 3, 2009.
7 Personal communication, H. Shin, Census Bureau, July 13, 2009.
8 American Recovery and Reinvestment Act of 2009, Public Law 111-5 � 3002(b)(2)(B)(vii), 111th Cong., 1st sess. (February 17, 2009).
9 D. Blumenthal, ONC, HHS at the IOM Meaningful Use Workshop, July 13, 2009.
10 PQRI incentive payments are only currently authorized through 2010.
11 44.8 million Medicare beneficiaries in 2008 and 58.7 million Medicaid and CHIP recipients in 2006 with dual enrollment at about 10 million, plus 8.9 million of the 16 million served by health centers are uninsured or have insurance other than Medicare or Medicaid. The U.S. population, as of July 1, 2008, was 304 million (HRSA, 2008; Kaiser Family Foundation, 2005, 2008, 2009; U.S. Census Bureau, 2008).
12 Children's Health Insurance Program Reauthorization Act of 2009, Public Law 111-3, 111th Cong., 1st sess. (February 4, 2009).
13 ARRA authorizes $20 billion for health information technology.
14 Formerly known as the Utilization Review Accreditation Commission.
15 Personal communication, P. Schyve, The Joint Commission, May 11, 2009.
16 Personal communication, D. Love, National Association of Health Data Organizations, and B. Rudolph, The Leapfrog Group, January 13, 2009.

Page last reviewed October 2014
Page originally created September 2012
Internet Citation: 6. Implementation (continued). Content last reviewed October 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/research/findings/final-reports/iomracereport/reldata6a.html