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United States

Addressing Racial And Ethnic Barriers To Effective Health Care: The Need For Better Data

PROLOGUE: Improving the quality of care all Americans receive will require the elimination of racial and ethnic disparities in health. And making progress against disparities will require the collection of reliable data on race and ethnicity. Private managed care organizations enroll many persons whose care is financed by federal and state governments. This paper’s four authors, all of whom are physicians, make the case that health plans can make a valuable contribution toward eliminating racial and ethnic disparities in health by collecting and using these data for quality improvement. The authors acknowledge that the issue is not without controversy and underscore the need for consensus building among patients, providers, insurers, and public and private purchasers on how to best achieve this objective. Barriers to data collection and strategies to overcome them are discussed.

Arlene Bierman is a general internist, geriatrician, and health services researcher who joined the Agency for Healthcare Research and Quality (AHRQ) in 1997. She is senior research physician in AHRQ’s Center for Outcomes and Effectiveness Research. She received her medical degree from the University of North Carolina, where she was a Morehead Fellow; she also holds a master’s degree in clinical evaluative sciences from Dartmouth. Nicole Lurie, Alcoa Professor of Health Policy Analysis at RAND, served as the principal deputy assistant secretary of health in the Department of Health and Human Services from 1998 to 2001. She attended medical school at the University of Pennsylvania and holds a master of science in public health from the University of California, Los Angeles. Karen Scott Collins is responsible for developing the Commonwealth Fund’s program on Quality of Care for Underserved Populations, with a focus on minority and low-income populations. She earned her medical degree from Cornell University Medical College and holds a master of public health degree from the Johns Hopkins Bloomberg School of Public Health in Baltimore. John Eisenberg had been director of AHRQ since 1997 until his untimely death 10 March 2002. He received his medical degree from Washington University in St. Louis and a master of business administration degree from the Wharton School, University of Pennsylvania.

Abstract

 
Racial and ethnic disparities in health outcomes and quality of care have been observed among persons with similar health insurance, within the same system of care, and within the same health plan. National efforts to eliminate these disparities are hindered by the lack of race/ethnicity data. Collection of these data by health care providers, coupled with standards for collection, use, and privacy protection, would be a first step toward eliminating disparities. Although no national consensus exists with respect to data collection, the weight of prior research, related public and private efforts, and growing diversity of the U.S. population are likely to increase demand for accurate data on race and ethnicity in health care settings.

As major purchasers of health care, federal and state governments can play a vital role in eliminating health disparities. However, before progress can be made, public and private stakeholders (purchasers, providers, and the public) must address multiple barriers to data collection. Because many Americans, including beneficiaries of publicly funded programs, are enrolled in managed care, health plans can play a critical role in supporting efforts to eliminate disparities and in developing viable strategies to collect race/ethnicity data for this purpose.

To promote dialogue on these issues, components of the U.S. Department of Health and Human Services (HHS) and the Commonwealth Fund cosponsored a meeting in June 1999 to bring together representatives of managed care, purchasers, and federal agencies.⁴ We report on this dialogue and provide an overview of issues related to the use, collection, and interpretation of race/ethnicity data in managed care. To reflect ongoing discussions, we draw on information from multiple primary sources and discussions in other forums among the provider, purchaser, governmental, and health services communities to describe selected activities by managed care plans to collect and use race/ethnicity data, and to identify barriers to data collection and potential strategies to overcome them.

Uses And Collection Of Race/Ethnicity Data

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Uses of data. As the United States grows more diverse, health plans have an interest in improving health outcomes and patient satisfaction among diverse enrollee groups. Managed care plans can use race/ethnicity data on their enrollees to (1) inform program development, planning, and priority setting; (2) target quality improvement efforts; (3) understand differences in performance within a plan; (4) understand the health needs of specific populations and develop appropriate interventions; (5) identify the need for and deploy resources for the provision of culturally and linguistically appropriate services; and (6) evaluate and monitor the effectiveness of interventions.

Public and private purchasers can use data on care provided to various racial and ethnic groups to compare health plans and to choose plans that provide the best-quality care. Employers can use such information to assure that different segments of their workforce are receiving care of equivalent quality. This information can also help to inform individual decisions about health plan choice. Policymakers can use such data to develop policy and program strategies. These data can provide researchers with the evidence base to inform all of these activities.

Examples from the private and public sectors. Although managed care plans have not routinely collected data on race and ethnicity, they have developed a variety of strategies for obtaining these data for specific projects. Some plans view the examination of clinical performance in selected domains for various population subgroups as a logical component of quality improvement programs. Because there is no current inventory of health plans’ initiatives to address health disparities, we provide some illustrative examples of leadership by both the private and public sectors in this area.

Some health plans, including Prudential’s Center for Health Care Research and UnitedHealth Group, collect race/ethnicity data for specific quality improvement efforts.⁵ Aetna U.S. Healthcare has determined that strategies regarding both market share and the provision of high-quality care require knowledge of enrollees’ race and ethnicity.⁶ Aetna therefore has developed a set of Minority Health Initiatives, one of which focuses on collecting race/ethnicity data to increase capacity to study disparities in access and health status and to facilitate the development and implementation of culturally appropriate outreach and intervention programs. Resources have been allocated for the voluntary collection of data on new enrollees’ race/ethnicity and language preference.⁷

In the Quality Assessment and Performance Improvement requirements for 2003 under the Quality Improvement System for Managed Care (QISMC), the Centers for Medicare and Medicaid Services (CMS) requires Medicare+Choice (M+C) plans to conduct a quality improvement project that addresses either clinical health care disparities or culturally and linguistically appropriate services.⁸ The Veterans Health Administration (VHA), comparable to a large health plan, has collected race/ethnicity data together with assessment of health and functional status, using a well-validated instrument adapted for veteran populations, the SF-36 VA. The VHA thus has the capacity to assess differences in health status by race and ethnicity for quality improvement.

Approaches to data collection. Lacking a uniform data collection infrastructure, health plans use a variety of strategies to collect race/ethnicity data: electronic medical records, administrative data, enrollee surveys, data linkages, and federal and state enrollment files for Medicare and Medicaid beneficiaries, respectively.

Medical records. Some Harvard Pilgrim practices collect race and ethnicity data in their electronic medical records. However, missing data remain a challenge for several reasons: Not all providers use these electronic medical records or record race and ethnicity in the available field; data are available only for those enrollees using services; and data are reported by the clinician rather than by the enrollee. An alternative approach used by Kaiser Permanente Northern California and Harvard Pilgrim is collection of data on language preference when an appointment is made or during enrollment.

Data linkages. Several managed care organizations are working in partnership with the Commonwealth of Massachusetts to obtain race/ethnicity data by adding health plan identifiers to state databases such as birth certificates and tumor registries. Such data can then be linked to other databases. For example, information from state hospital discharge data linked to birth certificate information has provided data on low birthweight by race and health plan, as well as stratified and risk-adjusted data for cesarean sections. Massachusetts, in partnership with health plans, also asked respondents to identify the source of their health care coverage on the Behavioral Risk Factor Surveillance Survey (BRFSS) sponsored by the Centers for Disease Control and Prevention (CDC). The intent is to make health plan-specific information on enrollees’ risk behavior and prevention practices available by race and ethnicity. Because the survey is representative of the state population, comparisons between managed care and fee-for-service (FFS), as well as between insured and uninsured persons, may be possible.⁹

State Medicaid data. The CMS collects statistics from state Medicaid programs on the race and ethnicity of beneficiaries. However, there is considerable state variation in the completeness and reliability of these data. The availability of data to health plans also varies by state.¹⁰ Representatives from Harvard Pilgrim Health Plan (Massachusetts) and Access Health Systems (Tennessee) reported receiving race/ethnicity data from their state Medicaid programs.¹¹ A Minnesota health plan, Medica, examined quality of care for different conditions for different racial and ethnic groups using data on race and ethnicity from its state Medicaid program. Disparities in quality were present in some areas but not in others. Medica is taking steps to understand and address identified disparities.¹² Also, proposed rules for Medicaid managed care require states to collect data on beneficiaries’ race, ethnicity, and primary language and to make these data available to plans.¹³

Geocoding. Another approach used to examine differences in performance for different enrolled populations in the absence of person-level data is small-area analysis using area-level data, conducted by geocoding. Geocoding is a method to obtain sociodemographic characteristics about the neighborhood in which a person lives via linkages to census data. Census data can provide information on the household income, education, occupation, and race/ethnicity of residents of a given area. For example, the New York Hospital Community Health Plan studied the rate of hospital admissions for asthma according to the asthmatics’ neighborhoods of residence and designed interventions to improve asthma care based on the geographic distribution of asthma prevalence. Area-level census data have been used to assess variations in plan performance by race/ethnicity and socioeconomic status.¹⁴ This method is better for assessing socioeconomic status than for race/ethnicity, since the utility of census-derived measures as a proxy for race or ethnicity varies by the level of neighborhood integration.¹⁵

Multiple data sources. The CMS allows M+C plans to choose among several sources of race/ethnicity data for quality improvement projects under QISMC. These include primary data collection by plans at the time of or subsequent to enrollment, data from the CMS enrollment database (EDB), area-level data, and survey data on race and ethnicity obtained through the Consumer Assessment of Health Plans (CAHPS).¹⁶ The data in the EDB are supplied by the Social Security Administration. Studies have found that the EDB has a 97 percent sensitivity for identifying white and black persons but a sensitivity of less than 60 percent for other racial/ethnic groups including Hispanics, Asians, and Native Americans.¹⁷ Procedures are in place to increase the reliability of these data over time.

Barriers To Data Collection And Use

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Perceived barriers to the routine collection of race/ethnicity data include data quality, legal issues, and concerns about confidentiality and privacy, potential for misuse, public reporting, and cost. Plans reported at our June 1999 meeting that they generally do not perceive demand for these data by payers and regulators but acknowledged that there are many potential sources of demand in the near future as awareness of and commitment to eliminating health disparities grow in the private and public sectors.

The business case. Most plans did not feel that the business case for the collection of these data had been made and that this presents a major barrier to data collection. However, some plans have concluded that improving quality for all enrollees may serve to maintain or increase market share.¹⁸ It has been argued that use of these data could provide market advantage and even reduce costs. For example, improving publicly reported Health Plan Employer Data and Information Set (HEDIS) measures by targeting enrollee groups with poor performance, or reducing costs through better clinical management, could create a fiscal benefit. The business case could be created through the use of financial and other incentives, but there is no consensus in the policy community on whether or how to do this. The business case developed by HHS for inclusion of race and ethnicity as a data element under the 1996 Health Insurance Portability and Accountability Act (HIPAA) may serve as a model. A December 2001 conference sponsored by the National Institutes of Health (NIH) aimed at better articulating the business case for data collection, evidence that research and policy communities are cognizant of the need for this business case and that momentum is building toward its development.

Improving data quality. Use of existing federal standards, coupled with the application of lessons learned from the collection and use of these data in other health care settings, can inform efforts to improve the availability, quality, and comparability of these data in managed care. For example, twenty-nine of forty-four states that collect hospital discharge data also collect race and ethnicity data.¹⁹ Studies using state hospital databases have found racial and ethnic differences in the use of diagnostic and therapeutic procedures.²⁰ State hospital discharge data are limited in that misclassification errors can result when observer identification (rather than self-identification) is used and that data elements are not standardized across states. Studies have shown that the frequency of misclassification errors from observer identification varies by race and ethnicity. The Massachusetts Health Data Consortium compared assignment of race and ethnicity in its hospital discharge abstract database with the self-reported race of mothers in birth certificate data. The consortium found 97 percent agreement for whites, 93 percent agreement for blacks, and 91 percent agreement for Hispanics.²¹ The National Center for Health Statistics (NCHS) conducted a study on the quality and reliability of death rates by race and Hispanic origin in official U.S. mortality statistics and found greater than 98 percent agreement between recorded and self-reported data for blacks and whites, 89.7 percent for Hispanics, and 57 percent for Native Americans.²²

Use of a standard classification scheme, such as those developed by the Office of Management and Budget (OMB), would permit comparisons across different settings, systems of care, and geographic areas.²³ These standards recognize that data categories that go beyond minimum standards and reflect the diversity of enrolled populations may be needed to target interventions.²⁴ For example, a plan might need to distinguish among subgroups of Latinos, blacks, Asians, and Native Americans. The development of a standard classification system with standard category definitions that allows comparison of subgroups across data sources would facilitate these efforts. The ability to aggregate these sometimes small subcategories back into the standard classifications is needed for developing a national profile, for public health reporting, and for conducting comparative analyses.

Interpretation of race and ethnicity data. The use of additional data elements can foster appropriate data interpretation. To understand the role of race and ethnicity in context, other relevant factors such as socioeconomic status, language preference, acculturation, health literacy, and neighborhood characteristics need to be considered. An understanding of the independent contribution of these nonclinical determinants of health to health disparities and their interaction with race and ethnicity can facilitate quality measurement and help to guide the development of effective interventions.²⁵

Perceived legal barriers. A common misperception among health plans is that federal law prohibits the routine collection of data on their enrollees’ race and ethnicity. According to the HHS Office for Civil Rights, there is no such federal prohibition.²⁶ A review of state laws and regulations regarding the collection of race/ethnicity data by health insurers found that forty-six states and the District of Columbia place no restrictions on data collection. Among the four states where restrictions were identified, differences exist as to whether the restrictions apply before, during, or after enrollment. One state even requires health maintenance organizations (HMOs) to collect and report data on race and ethnicity.²⁷

Federal inclusion policies for the collection of race/ethnicity data mandate the collection of such data in HHS-sponsored and -maintained data collection activities.²⁸ Discussions underscore that voluntary disclosure and self-identification by enrollees are preferable. Techniques for collecting sensitive information, such as explaining what the data will be used for and providing procedural safeguards, are recommended.²⁹

Privacy and confidentiality concerns. Privacy of health information is a major consideration. An Institute of Medicine (IOM) report discusses how proposed and current efforts to protect the confidentiality of medical records could help to provide protection against misuse.³⁰ New standards for electronic data transmission under HIPAA include race/ethnicity as an optional data element for hospital discharge data.³¹ Scheduled for mandatory compliance effective 14 April 2003, the HHS Privacy Rule will protect the confidentiality of individually identifiable health information when held by health plans, clearinghouses, and providers who use specified electronic transactions.³² This rule does not preclude the collection of race/ethnicity data, and, in fact, its provisions can serve to protect confidentiality.

There is evidence that individuals are willing to provide this information when clear explanations of its use are provided. For example, the Henry Ford Health System encountered a favorable response from community leaders in efforts to collect these data, as long as data were used for improvement purposes and collected by self-identification.³³

Concerns about the misuse of race/ethnicity data. The potential for misuse of data on race and ethnicity is a concern. Enrollees might be fearful that a health plan could use this information to deny or drop coverage or to charge higher rates. Clear guidelines for the use of these data will need to be established, as will the consequences for violating them. Education for health plans and consumers about the value of data collection and the advantages that can be derived from data use can help to address these concerns.³⁴

Timing of data collection. One strategy used to limit the potential for misuse is to collect race/ethnicity data after enrollment, such as at the time of an initial health assessment. Plan representatives remarked that the costs of collecting data at enrollment are lower than the costs for data collection after enrollment. Some states have developed strategies to collect data at enrollment to guard against discriminatory enrollment decisions. For example, independent brokers may be used to enroll beneficiaries into Medicaid managed care. One state uses a separate tear sheet from the application to collect data at the time of enrollment.³⁵

Concerns about public reporting and accountability. Performance measurement is used for three distinct but related activities: quality improvement, public reporting to inform purchasers’ and consumers’ choices, and accountability through accreditation processes. While the value of using race/ethnicity data for quality improvement is recognized, there is far less consensus about public reporting because of concerns that only some of the observed disparities would be within health plans’ control. Plans stressed the need to include FFS health care in comparable performance measurement efforts.

Costs of data collection. Cost remains an important barrier to data collection. More information is needed as to what the actual costs of data collection are, as well as how to minimize them. Standardized and routine collection may reduce these costs. These data are routinely collected in other sectors: housing, education, and employment for civil rights enforcement.³⁶ Examination of these sectors may be able to provide critical information to the health sector about costs and their allocation. Further dialogue among policymakers, providers, and purchasers is needed on how to distribute the cost burden.

Related Activities

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There has been substantial activity in both the public and private sectors aimed at addressing health disparities, including calls for data collection, heightening awareness of the problem and contributing to future demand for data. AHRQ’s 1999 reauthorization requires the agency to develop annual reports to the nation on trends in health care disparities beginning in 2003. This report will be enhanced by the availability and use of race/ethnicity data to develop and report performance measures. At a recent meeting of AHRQ’s Integrated Service Delivery Research Network, which included managed care representatives, the need to disseminate information to policymakers about the use and collection of race/ethnicity data was identified as a priority. The National Committee on Vital and Health Statistics recommended the collection of uniform enrollment data, including race and ethnicity, along with other demographic factors during enrollment in Medicaid managed care.³⁷ The State Children’s Health Insurance Program (SCHIP) requires states to collect and report data on the race, ethnicity, and primary language of enrolled children.³⁸ The Minority Health and Health Disparities Research and Education Act of 2000 requests an IOM report describing the data needed to support efforts to evaluate the effects of race and ethnicity on access to and quality of health care. Two additional IOM committees are examining various aspects of the issues outlined here; these committees’ reports may form a foundation for building consensus.³⁹

There has been growing recognition in the private sector about the value of using race/ethnicity data for quality improvement. For example, the American Association of Health Plans (AAHP) developed a bimonthly insert to its newsletter called "Disparities in Care," which has included features on the importance of the collection and use of data on race and ethnicity. The Commonwealth Fund has supported the development of Minority Health Report Cards, a National Quality Forum workshop on quality measurement and disparities in care, and a comprehensive review of federal policies and practices related to data collection.⁴⁰

Future Directions

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The 2000 census has drawn attention to the growing racial and ethnic diversity of the U.S. population. At a time when the decoding of the human genome has confirmed evidence against the validity of race as a biological construct, race and ethnicity continue to be important social constructs correlated with access to and quality of care.⁴¹ There is cause for optimism that effective interventions can have an impact. The IOM’s recent report, Crossing the Quality Chasm, identifies equity as one of the six key quality dimensions on which our current health system falls short.⁴² Citing the large body of literature on health disparities, the report states that health care should be equitable and that care should not vary in quality because of personal characteristics, including race.

We conclude with the following observations drawn from multiple discussions. First, quality improvement efforts aimed at eliminating racial and ethnic disparities in health are dependent upon the availability of reliable data on race and ethnicity. However, universal data collection will require the participation and collaboration of the federal government, state governments, and the private sector, including health plans and insurers, providers, purchasers, and consumers.

Second, the quality, usefulness, and acceptability of data may be enhanced through a number of mechanisms. Data collection standards that encourage use of expanded categories of race and ethnicity locally, which can be collapsed into the OMB reporting format to assess trends and carry out comparisons nationally, can provide the level of detail needed to improve quality at the local level while providing standardized data to assess national progress. The reporting of race/ethnicity data based upon self-identification is recognized as the more accurate method of data collection. Mechanisms to safeguard the confidentiality of these data as well as guidelines for appropriate use will need to be developed. Data collection that includes information on related social factors, such as socioeconomic status and language spoken at home, will further enhance the ability to tailor quality improvement strategies and increase the likelihood of eliminating disparities in care.

Third, pilot projects to demonstrate these data’s utility for quality improvement should be able to provide valuable information for future initiatives. Collecting and analyzing race/ethnicity data in ongoing quality improvement activities, such as the Diabetes Quality Improvement Project (DQIP), can expand the current knowledge base. Partnerships that include representation of diverse population groups and different systems of care in improvement interventions will foster the generalizability of the findings from these projects.

Fourth, education of the public, insurers, purchasers, and providers about the benefits and appropriate use of these data, and education for health care personnel on how to collect these data, can help to assure that the data will be used for public benefit. Finally, careful examination of both the community benefit and the business case for data collection will be needed to inform future decision making.

The collection of race/ethnicity data by health care providers, coupled with national standards for collection, use, and privacy protection, would be a first step toward eliminating health disparities. Nevertheless, there are multiple barriers and sources of resistance to data collection, and this remains a sensitive issue. Although there is no national consensus with respect to the collection of data on race/ethnicity for performance measurement in health care settings, the weight of prior research, the goals and needs of Healthy People 2010, related public and private efforts, and the demographic changes in the U.S. population are likely to increase the demand for such data in the years to come.

Editor's Notes

 
The authors gratefully acknowledge Violet R.H. Woo, Joan Jacobs, and Olivia Carter-Pokras from the HHS Office of Minority Health; and Carolyn Clancy and Anne Elixhauser from AHRQ for their thoughtful comments and suggestions on this manuscript. The views expressed here are those of the authors and do not necessarily represent the position of AHRQ, HHS, the Commonwealth Fund, or those present at the meeting described in this paper.

NOTES

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1. See, for example, J.Z. Ayanian et al., "Quality of Care by Race and Gender for Congestive Heart Failure and Pneumonia," Medical Care 37, no. 12 (1999): 1260–1269[Medline]; P.W. Newacheck, D.C. Hughes, and J.J. Stoddard, "Children’s Access to Primary Care: Differences by Race, Income, and Insurance Status," Pediatrics 97, no. 1 (1996): 26–32[Abstract/Free Full Text]; D.B. Mukamel, A.S. Murthy, and D.L. Weimer, "Racial Differences in Access to High-Quality Cardiac Surgeons," American Journal of Public Health 90, no. 11 (2000): 1774–1777[Abstract/Free Full Text]; K.L. Kahn et al., "Health Care for Black and Poor Hospitalized Medicare Patients," Journal of the American Medical Association 271, no. 15 (1994): 1169–1174[Abstract]; L. Cooper-Patrick et al., "Race, Gender, and Partnership in the Patient-Physician Relationship," Journal of the American Medical Association 282, no. 6 (1999): 583–589[Abstract/Free Full Text]; and M. van Ryn and J. Burke, "The Effect of Patient Race and Socioeconomic Status on Physicians’ Perceptions of Patients," Social Science and Medicine 50, no. 6 (2000): 813–828.
2. M.E. Gornick et al., "Effects of Race and Income on Mortality and Use of Services among Medicare Beneficiaries," New England Journal of Medicine 335, no. 11 (1996): 791–799[Abstract/Free Full Text]; C.E. Blixen et al., "A Comparison of Asthma-Related Healthcare Use between African-Americans and Caucasians Belonging to a Health Maintenance Organization," Journal of Asthma 36, no. 2 (1999): 195–204[Medline]; E.M. Zoratti et al., "Health Service Use by African Americans and Caucasians with Asthma in a Managed Care Setting," American Journal of Respiratory and Critical Care Medicine 158, no. 2 (1998): 371–377[Abstract/Free Full Text]; and R.M. Mayberry, F. Mili, and E. Ofili, "Racial and Ethnic Differences in Access to Medical Care," Medical Care Research and Review 57, supp. 1 (2000): 108–145.[Abstract/Free Full Text]
3. K. Fiscella et al., "Inequality in Quality: Addressing Socioeconomic, Racial, and Ethnic Disparities in Health Care," Journal of the American Medical Association 283, no. 19 (2000): 2579–2584[Abstract/Free Full Text]; K.G. Keppel, J.N. Pearcy, and D.K. Wagener, "Trends in Racial and Ethnic-Specific Rates for the Health Status Indicators: United States, 1990–98," Healthy People 2000 Statistical Notes 23 (Hyattsville, Md.: Centers for Disease Control and Prevention, National Center for Health Statistics, January 2002); L.M. Martin et al., "Comparison of Mammography and Pap Test Use from the 1987 and 1992 National Health Interview Surveys: Are We Closing the Gaps?" American Journal of Preventive Medicine 12, no. 2 (1996): 82–90[Medline]; and S.A. Optenberg et al., "Race, Treatment, and Long-Term Survival from Prostate Cancer in an Equal-Access Medical Care Delivery System," Journal of the American Medical Association 274, no. 20 (1995): 1599–1605.[Abstract]
4. U.S. Department of Health and Human Services, "Performance Measurement in Managed Care and Its Role in Eliminating Racial and Ethnic Disparities in Health: Meeting Summary" (Unpublished report, 1999). The 7 June 1999 meeting in Washington, D.C., included representatives of managed care (commercial, Medicaid, and Medicare), purchasers (CMS, state agencies, and employers) and federal agencies (CMS, AHRQ, CDC, Health Resources and Services Administration, HHS Office of Civil Rights, Office of Minority Health, Office of Public Health and Science, and Assistant Secretary for Planning and Evaluation).
5. Ibid.
6. Dennis Oakes, executive director, Aetna Academic Medicine and Managed Care Forum, personal communication, April 2000.
7. U.S. Quality Algorithms, Center for Health Care Research, "Capacity to Conduct Studies on the Impact of Race/Ethnicity on the Access, Use, and Outcomes of Care," AHRQ Contract no. 290-00-0011 (Atlanta: USQA, June 2001).
8. "Medicare Managed Care Manual," chap. 5 exhibits, Appendix A–National QAPI Project Operational Policy Letters, www.hcfa.gov/pubforms/86_mmc/mc86c05exhibits.htm (9 November 2001).
9. See Note 4.
10. Center for Medicaid and State Operations, CMS, 2028 data, 1998.
11. See Note 4.
12. Meredith Mathews, medical director, Allina Health System, personal communication, April 2001.
13. Medicaid Program, Medicaid Managed Care, Proposed Rule, Federal Register 66, no. 161 (2001): 43613–43677.
14. A.M. Zaslavsky et al., "Impact of Sociodemographic Case Mix on the HEDIS Measures of Health Plan Quality," Medical Care 38, no. 10 (2000): 981–992.[Medline]
15. N. Krieger, D.R. Williams, and N.E. Moss, "Measuring Social Class in U.S. Public Health Research: Concepts, Methodologies, and Guidelines," Annual Review of Public Health 18 (1997): 341–378.[Medline]
16. "Medicare Managed Care Manual," chap. 5 exhibits, Appendix A.
17. S.L. Arday et al., "HCFA’s Racial and Ethnic Data: Current Accuracy and Recent Improvements," Health Care Financing Review 21, no. 4 (2000): 107–116.[Medline]
18. Oakes, personal communication.
19. "Statewide Encounter-Level Inpatient and Outpatient Data Collection Activities," Summary Report (Prepared by NAHDO and the MEDSTAT Group for AHCPR, 1999).
20. E.A. Mort, J.S. Weissman, and A.M. Epstein, "Physician Discretion and Racial Variation in the Use of Surgical Procedures," Archives of Internal Medicine 154, no. 7 (1994): 761–767[Abstract]; and D.M. Carlisle, B.D. Leake, and M.F. Shapiro, "Racial and Ethnic Disparities in the Use of Cardiovascular Procedures: Associations with Type of Health Insurance," American Journal of Public Health 87, no. 2 (1997): 263–267.[Abstract/Free Full Text]
21. Anne Elixhauser, testimony before the National Committee on Vital and Health Statistics, "Adding Race/Ethnicity to the HIPAA Standard for Institutional Claims," 24 June 1999.
22. H. Rosenberg et al., "Quality of Death Rates by Race and Hispanic Origin: A Summary of Current Research" (Hyattsville, Md.: CDC/NCHS, 1999).
23. D.R. Williams and J.S. Jackson, "Race/Ethnicity and the 2000 Census: Recommendations for African American and Other Black Populations in the United States," American Journal of Public Health 90, no. 11 (2000): 1728–1730[Abstract/Free Full Text]; and D.J. Friedman et al., "Race/Ethnicity and OMB Directive 15: Implications for State Public Health Practice," American Journal of Public Health 90, no. 11 (2000): 1714–1719.[Abstract/Free Full Text]
24. Office of Management and Budget, "Provisional Guidance on the Implementation of the 1997 Standards for Federal Data on Race and Ethnicity" (Washington: OMB, 15 December 2000).
25. E.C. Schneider et al., "Enhancing Performance Measurement: NCQA’s Road Map for a Health Information Framework, National Committee for Quality Assurance," Journal of the American Medical Association 282, no. 12 (1999): 1184–1190.[Abstract/Free Full Text]
26. See Note 4.
27. E. Berry et al., "Assessment of State Laws, Regulations, and Practices Affecting the Collection and Reporting of Racial and Ethnic Data by Health Insurers and Managed Care Plans" (Presentation at American Association of Health Plans Annual Meeting, Los Angeles, April 2001).
28. DHHS, "HHS Policy for Improving Race and Ethnicity Data," 24 October 1997, aspe.os.dhhs.gov/datacncl/inclusn.htm (4 May 2001).
29. See Note 4.
30. Institute of Medicine, Protecting Data Privacy in Health Services Research (Washington: National Academy Press, 2000).
31. Washington Publishing Company, "Implementation Guides Adopted for Use under HIPAA," aspe.hhs.gov/admnsimp (26 March 2002).
32. DHHS, "Standards for Privacy of Individually Identifiable Health Information," 6 July 2001, aspe.os.dhhs.gov/admnsimp/final/pvcguide1.htm (7 November 2001).
33. D.R. Nerenz et al., "Eliminating Racial/Ethnic Disparities in Health Care: Can Health Plans Generate Reports?" Health Affairs (May/June 2002): 259–263.
34. See Note 4.
35. Ibid.
36. U.S. Commission on Civil Rights, The Health Care Challenge: Acknowledging Disparity, Confronting Discrimination, and Ensuring Equality, Volume II, The Role of Federal Civil Rights Enforcement Efforts, Pub. no. 005-902-00063-1 (Washington: Commission on Civil Rights, 1999).
37. National Committee on Vital and Health Statistics, Subcommittee on Population Specific Issues, Medicaid Managed Care Data Collection and Reporting, Final Report (Washington: NCVHS, December 1999).
38. DHHS, "State Child Health: Revisions to the Regulations Implementing the State Children’s Health Insurance Program," Federal Register 66 (25 June 2001): 33810.[Medline]
39. While this paper was in press, the first of these two committees released its report 20 March 2002. This report recommends the collection of data by race, ethnicity, socioeconomic status, and where possible, by primary language and publicly funded health programs, and reporting of measures of racial and ethnic disparities by the NCQA and JCAHO for the purposes of quality improvement. B.D. Smedley, A.Y. Stith, and A.R. Nelson, eds., Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (Washington: National Academy Press, 2002).
40. R.T. Perot and M. Youdelman, Racial, Ethnic, and Primary Language Data Collection in the Health Care System: An Assessment of Federal Policies and Practices (New York: Commonwealth Fund, September 2001).
41. Williams and Jackson, "Race/Ethnicity and the 2000 Census"; and R.S. Schwartz, "Racial Profiling in Medical Research," New England Journal of Medicine 344, no. 18 (2001): 1392–1393.[Free Full Text]
42. Institute of Medicine, Crossing the Quality Chasm: A New Health System for the Twenty-first Century (Washington: National Academy Press, 2001).

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