Appendix G
Racial and Ethnic Data Collection by Health Plans

Carmella Bocchino*

INTRODUCTION

Access to quality health care services is a prominent focus of health care organizations, researchers, and policymakers in America today. For culturally diverse populations, access to quality health care is often hampered by a variety of socioeconomic and cultural factors.

Reports such as Diverse Communities, Common Concerns: Assessing Health Care Quality for Minority Americans (Collins et al., 2002), have demonstrated how race, ethnicity, and English proficiency can affect access to quality health care as the United States becomes a more racially and ethnically diverse nation.

Health plans have recognized the importance of responding to patients’ varied perspectives, beliefs, and behaviors about health and well-being, as well as the considerable health consequences that will result in a failure to value and manage cultural and communal differences in the populations they serve. Through the emerging field of culturally competent care, health plans are developing strategies to reduce disparities in access to and quality of health care services. The collection of data on race and ethnicity is a first step in designing and advancing such strategies.

Health plans generally are supportive of the collection of racial and ethnic data on their members. They see these data as having great utility in

*  

Carmella Bocchino is vice president for Medical Affairs of America’s Health Insurance Plans.



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Eliminating Health Disparities: Measurement and Data Needs Appendix G Racial and Ethnic Data Collection by Health Plans Carmella Bocchino* INTRODUCTION Access to quality health care services is a prominent focus of health care organizations, researchers, and policymakers in America today. For culturally diverse populations, access to quality health care is often hampered by a variety of socioeconomic and cultural factors. Reports such as Diverse Communities, Common Concerns: Assessing Health Care Quality for Minority Americans (Collins et al., 2002), have demonstrated how race, ethnicity, and English proficiency can affect access to quality health care as the United States becomes a more racially and ethnically diverse nation. Health plans have recognized the importance of responding to patients’ varied perspectives, beliefs, and behaviors about health and well-being, as well as the considerable health consequences that will result in a failure to value and manage cultural and communal differences in the populations they serve. Through the emerging field of culturally competent care, health plans are developing strategies to reduce disparities in access to and quality of health care services. The collection of data on race and ethnicity is a first step in designing and advancing such strategies. Health plans generally are supportive of the collection of racial and ethnic data on their members. They see these data as having great utility in *   Carmella Bocchino is vice president for Medical Affairs of America’s Health Insurance Plans.

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Eliminating Health Disparities: Measurement and Data Needs a number of areas, which are delineated in this paper. Barriers, however, do exist—collection is not consistent across the industry and often fragmented—which make it difficult to evaluate the quality of such data and subsequently determine solutions to advance culturally competent care. Even so, some strong examples of data collection and related innovative strategies for use are emerging. To date, several organizations, notably the Agency for Healthcare Research and Quality (AHRQ), the Commonwealth Fund, and the National Quality Forum, have identified many uses for the collection of data on race and ethnicity. They include: Understanding the scope of health disparities affecting health plan members and stimulating action. Identifying and tracking similarities and differences in performance and quality of care in various geographic, cultural, and ethnic communities. Revealing socioeconomic and other demographic characteristics that contribute to differing proportions of disparities. Creating and using reports that focus on quality of care issues for minority group patients. Understanding etiologic processes and identification of points of intervention. Designing targeted quality improvement activities. Facilitating the provision of culturally and linguistically appropriate health care. Health plans view the collection of data on the race and ethnicity of their members as having great utility in a number of areas, such as evaluating the differences in care being received by plan members; designing culturally appropriate educational and other member communications; and implementing clinical and service quality improvement activities. What follows is a description of interviews conducted across a sample of AAHP’s1 member health plans, assessing their efforts to collect racial and ethnic data; offering examples of some current and potential methods of collection; identifying real and perceived barriers to data collection; and detailing the usefulness of such data for health plan programs. REPORT ON INTERVIEWS OF AAHP MEMBER HEALTH PLANS The American Association of Health Plans (AAHP), now known as AHIP, was asked by the National Research Council of the National Acad- 1   AAHP merged with the Health Insurance Association of America in November 2003; the new organization is called the America’s Health Insurance Plans (AHIP).

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Eliminating Health Disparities: Measurement and Data Needs emy of Sciences to provide information to the panel on DHHS Collection of Race and Ethnicity Data. The panel was convened to examine the adequacy of data on race and ethnicity collected or used by DHHS programs, and will issue guidance to the DHHS regarding the following: What data on race and ethnicity are private organizations and providers collecting? What is the availability and quality of the data collected? How can private organizations benefit from the collection of these data? How are the data used? What are the barriers to collecting these data? AAHP was asked to evaluate whether and how health plans collect racial and ethnic data. The panel believed there would be value in using an interview method that provided for and encouraged interactive questioning. AAHP conducted telephone interviews with a sample of member health plans across the country to identify and highlight the issues surrounding such data collection and summarize these efforts. Methodology A sample of 30 health plans was selected for interviews using a twostep methodology. Step 1. Sixteen AAHP member health plans were chosen, because these plans were known to have initiated activities related to this project. Step 2. Fourteen health plans were selected from the pool of health plans responding to the 2002 AAHP Industry Survey (n = 194). A subset was created from these 194 health plans using the following criteria: current AAHP membership and enrollment of at least 100,000 members. A random selection of 14 plans was chosen from the subset.2 2   The list of responders to the 2002 AAHP Annual Industry Survey was used as the sampling frame for this project because it contained health plans verified as eligible to participate and had current contact information. The 2002 industry survey sampling methodology used the following selection criteria: five large national plans were sampled with certainty, because to exclude them from the sample would distort the national data, as they represent a large population of health plan members. A subsequent sample of additional plans was selected in a randomly stratified manner as to enrollment: very large (≥6 million members), large (>370,000 but <6 million members), medium (130,000 to <370,000 members), and small (<130,000 members).

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Eliminating Health Disparities: Measurement and Data Needs RESULTS Demographics and Composition of Health Plans Interviewed Of the 30 plans in the sample, 24 (80 percent) completed the interviews. Collectively, the 24 health plans served approximately 49 million people and provided services in all 50 states, Washington, DC, the Commonwealth of Puerto Rico, and the Territory of Guam. The health plans represented approximately 30 percent of the total health plan enrollment in the United States. In terms of enrollment, nearly 63 percent of the health plans interviewed were defined as very large (≥6 million members) or large (>370,000 but <6 million members). An additional 38 percent of the health plans were defined as medium-sized (130,000 to <370,000 members) or small (<130,000 members). Fifty percent of health plans interviewed offered two lines of business (commercial and Medicare); 42 percent offered three lines of business (commercial, Medicaid, and Medicare); one health plan offered only Medicaid and Medicare; and one plan offered only a commercial product. The majority of the respondents interviewed for this study were responsible for either quality management/accreditation (50 percent) or market research/sales (21 percent) activities within the plans. Staff responsible for customer service, human resources/strategic planning, data and statistics, and health/disease/case management also participated in these interviews. The majority of respondents interviewed have been with their current health plan for 4 or more years, while less than a quarter of respondents were with health plans fewer than 4 years. Summary of Findings and Trends The health plans surveyed uniformly agree that the collection of racial and ethnic data is a part of good business practice. Such data allow for the identification of populations that may benefit from a customized approach to working with providers who can deliver culturally competent care. Health plans also identify information on sex, age, education, and geographic location as additional elements that contribute to the ability to meet perceived and real health care needs. Minority populations identified and served by the health plans interviewed were African American (the largest minority population identified), followed by Hispanic/Latino, and Chinese, Native American, Hmong, Korean, Russian, and Japanese. While health plans use a number of sources for the collection of racial and ethnic data, including both directly from members and indirectly from other sources, the most commonly used are census data (88 percent). Health plans use these data to match the Zip Codes of their members to Zip Codes

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Eliminating Health Disparities: Measurement and Data Needs within census blocks and then make a determination, based on the demographics of the census block, as to member race or ethnicity. This method is followed in frequency by individual self-identification on member satisfaction surveys—e.g., the Consumer Assessment of Health Plans Survey (CAHPS) or other plan-initiated surveys—(79 percent) and Medicare/Medicaid enrollment files (29 percent). Although 25 percent of health plans ask for race and ethnicity on their enrollment forms, the questions are voluntary and frequently left unanswered. It is for this reason that most health plans use “indirect methods” for data collection, such as census tracking or questions on primary language spoken as a proxy for racial and ethnic data. Health plans perceive that members may be reluctant to share their race and ethnicity, but that members tend to view information about language as a benign request. Language preferences, at a minimum, indicate how best to communicate to the member about access, services, and health education materials. Additionally, it often provides reasonable insight into ethnicity. Finally, health plans may receive additional information about race and ethnicity from members enrolled in health plan disease management programs. For example, as case managers conduct outreach to individual members enrolled in disease management programs, the need for special services, such as interpretation or translation, may be identified. Information about individual providers (e.g., language capabilities) is frequently used to assist members in provider selection or to “match” members with specific health professionals who can best meet their linguistic and cultural needs and thus enhance the quality of care and improve patient outcomes. At present, health plans are using racial and ethnic data in two major areas: to address preventive care issues within specific populations, and to identify populations at higher risk for certain chronic conditions. Other uses identified by health plans include the ability to apply a “loose evaluative” process to determine the consistency with which care is being delivered across different racial and ethnic groups—especially with regard to specific conditions; to assess the “representativeness” of the data collected in member surveys (i.e., how accurately the data reflect the populations served); to design culturally appropriate educational and other member communications; to implement clinical and service quality improvement programs that address the unique needs of racial and ethnic subpopulations; and ultimately to serve populations better by identifying and responding to their unique needs. All of the health plans interviewed indicated that they generally target the most prominent segments of diverse populations within their service areas for personalized health care offerings (e.g., translated materials, inter-

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Eliminating Health Disparities: Measurement and Data Needs preters). Health plans use the services of interpreters and translators (e.g., AT&T) as requested or as the need is identified to enhance the quality of health care services and outcomes. These services, however, have major constraints: they are expensive and have limitations; the translators are equipped for conversational translation, not trained in medical terminology; and they are available only by telephone. Translation needs often are augmented through the use of health plan or provider office staff with appropriate language skills. Differences in dialect and place of origin, however, can decrease the accuracy of translation. For example, people from Mexico may use different dialects than individuals from Puerto Rico, although both are categorized as being of Hispanic/Latino descent. At this time there appears to be no consistent approach to collecting racial and ethnic data within and between health plans, or throughout the health care system. Although frequently such data are recorded as a result of customer service logs or membership interactions, they are seldom shared “systemwide” (for example, consumer service log entries are not integrated into the membership database). Racial and ethnic data are, however, routinely targeted for specific program use, e.g., disease management or quality improvement programs or customer service. In many cases these findings mirror those of a Commonwealth-HRSA pilot study (Nerenz et al., 2002), which concluded that such data can be obtained through one or more “work-around” methods until more direct methods of data collection are implemented. Additionally, plans participating in the Medicare+Choice (now called Medicare Advantage) program are required to take part in a special national project on culturally and linguistically appropriate services (CLAS) or clinical health care disparities (CHCD). Initiated by the Centers for Medicare and Medicaid Services (CMS) in 2003, the CLAS project focuses on language access and organizational support in such areas as providing oral language translation services, assessing the diversity of health plan members and the community, assessing the cultural and linguistic competence of health plan, and developing a diverse workforce. The CHCD project requires Medicare Advantage plans to focus on diabetes, pneumonia, congestive heart failure, or mammography for any one or more of the following populations: American Indians/Alaska Natives, Asians, Black/African Americans, Native Americans/Pacific Islanders, and Hispanic/Latinos. These projects provide a strong incentive to better understand how to collect such data and, hopefully, will produce some templates for data collection that can be applied throughout the health plan community and the health care industry.

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Eliminating Health Disparities: Measurement and Data Needs Availability and Quality of Data Collected Health plans may have more racial and ethnic data available—at least of a general nature—than first recognized. Multiple sources for collection do exist within health plans and in many cases are being used, such as Medicaid/Medicare enrollment files, medical records data, self-reported items in surveys (CAHPS or plan-initiated), and customer service records. Publicly available data and software, such as census data and surname-recognition software, have been purchased and used to enhance existing data sources. Leveraging the race, ethnicity, socioeconomic status (SES), and other public health data in state databases through file linkages with health plan data is an infrequently used strategy due to confidentiality and funding constraints, but is worthy of further consideration. It is generally acknowledged that the difficulty of integrating the information across various databases and systems, as well as the time and human resources required for initiative development, presents major and often insurmountable challenges, especially for smaller health plans. Health plans also cite their lack of confidence in the quality of self-reported racial and ethnic data. As a result, health plans have found that multiple approaches to the collection of such data may be necessary. Health plans have collected primary language data on their members for years; however, it is an optional field on enrollment forms and the vast majority of members leave it blank. One approach that several health plans have used and many others are considering is the application of geocoding to members’ residential address information in health plan enrollment files. Geocoding permits health plans to use census data to create proxy variables for a member’s race and ethnicity based on the prevailing characteristics of the census block in which a member resides. Geocoding also can provide information on other important socioeconomic variables that can affect health risks and medical care delivery, such as education and income. While geocoding is not 100 percent accurate, it is reasonably reliable and has been found useful for identifying high-risk members and for identifying potential disparities in care. Consumer Benefits Derived from the Use of this Information The health plans interviewed identified specific benefits and applications for the collection of racial and ethnic data. As might be expected, given their emphasis on preventive care, health plans most frequently responded that they use these data for addressing preventive care issues within specific populations and identifying populations at higher risk for chronic conditions. The interviewees also realized that these data would be extremely helpful for evaluating the consistency and “patient centeredness”

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Eliminating Health Disparities: Measurement and Data Needs with which care is delivered and for designing clinical and service quality improvement programs that address the unique needs of racial and ethnic subpopulations. In addition, designing culturally appropriate educational and other member communications (written, voice, and electronic) and developing other effective initiatives were cited. Health plans stated that valid and reliable racial and ethnic data also could be used for assessing the “representativeness” of the data collected in member surveys. Health plans could use these data to determine the racial and ethnic make-up of respondents—as well as nonrespondents—to member surveys, to assess how close their response rates (or nonresponse rates) were compared with the overall demographic of the health plan. Finally, health plans recognized that, ultimately, these data can assist them in better serving their populations by identifying their unique cultural needs. Identified Barriers to Data Collection Legal statutes and regulatory mandates, at any level of government, can serve as barriers to the collection of racial and ethic data. For those health plans that operate in several states, multiple considerations increase the level of complexity. Although perceived otherwise by the public and across the health care industry, legal barriers to data collection on the race and ethnicity of their members are generally absent except in four states that have laws or regulations restricting health plans from collecting such data (see the review of both federal and state policies and regulations concerning the collection of racial and ethnic data at the end of this appendix). Almost 63 percent of the respondents cited legal concerns (perceived or real) as the most frequent barrier to data collection. Negative member reaction/response to such data collection—the perception of potential discrimination, distrust, lack of understanding of the purpose(s) (often exacerbated by language barriers)—and/or simple noncompliance also were stated as barriers to data collection. Seventy-five percent of interviewees indicated that negative responses could be reduced if health plan members better understood the positive aspects of such data collection. Incomplete information from members or lack of confidence in the accuracy of self-reported racial and ethnic data was an additional concern voiced by health plans (Arday et al., 2000). If these perceived barriers are removed, through educational and informational efforts, the result would, most likely, be helpful in advancing both the collection and use of the data to identify populations and design programs to reduce health care disparities. To have any lasting influence, these efforts must be directed at both the member population and the health care industry in general.

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Eliminating Health Disparities: Measurement and Data Needs Additional findings suggest that while health plans acknowledge the increased diversity and varying health needs of the populations they serve, “going it alone” in terms of data collection presents some barriers that may be difficult for a single health plan to overcome. Limited resources (financial as well as human) for data collection and for the design and implementation of programs for specific populations were identified by the majority of health plans as a major obstacle. Also, system changes required to capture and share the data require tailoring of any “off-the-shelf” technology—an added expense. Health plans also cited specific examples of potential implementation barriers to data collection. Plans are discouraged by the “hassle factor” of policies and procedures required by governing agencies (e.g., the state-level Department of Insurance) to revise enrollment forms to collect racial and ethnic data. The Health Insurance Portability and Accountability Act (HIPAA) enrollment transaction form (834) and HIPAA claims/encounter form (837) also were identified as problematic. Health plans, health care providers, and employers use a variety of methods to complete claims/encounter and enrollment transactions. For electronic claims/encounter transactions, health care providers use the HIPAA 837 form to submit requests for payment and transmit information about health care being provided when there are no direct claims under a provider’s contract. For claims submitted on paper, health care providers submit either the Health Care Financing Administration (HCFA [now CMS]) 1500 form to bill for professional services or the HCFA 1450 form to bill for institutional services. For electronic enrollment transactions, employers may use the HIPAA 834 form to transmit enrollment and disenrollment information to a health plan in order to establish or terminate an individual’s health insurance coverage. The HIPAA standard enrollment transaction form (834) designates racial and ethnic data as a “situational field,” but restricts collection to that done by an employer. Most claims/encounters are submitted electronically and the HIPAA 837 claims/encounter transaction does not include fields for race and ethnicity. For claims submitted on paper, neither the institutional claim form (HCFA 1450) nor the professional services claim form (HCFA 1500) contains a field for racial and ethnic data. Similarly, health plans are increasingly relying on electronic submission of enrollment data, yet HIPAA requires the use of the standard enrollment transaction (834) only by employers who self-insure under an Employee Retirement Income Security Act (commonly known as ERISA) plan; for others it is voluntary. Many of these employers may continue to submit enrollment data in proprietary electronic formats or on their own unique paper forms, which may or may not include data on race and ethnicity or may not capture and code the data in a consistent manner. For those self-insured employers covered under HIPAA,

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Eliminating Health Disparities: Measurement and Data Needs the Implementation Guide for the 834 enrollment transaction designates race and ethnicity as a “situational” data element, for which collection is dependent both on mutually agreed upon contractual reporting requirements between an employer and health plan and on the collection of these data not being prohibited by federal or state regulations. Furthermore, racial and ethnicity data are required only if the enrollee is the subscriber unless the contract between the plan sponsor and the payer requires such reporting for dependents. Until a strong business case for reporting data on race and ethnicity can be made for employers, securing such contractual agreements may prove difficult. Health plans may be reluctant to push the issue with employers if the additional “hassle factor” might put them at a competitive disadvantage relative to a plan that doesn’t request such reporting. Even if the HIPAA standard enrollment transaction were modified to make race and ethnicity required data elements and employers were to voluntarily adopt the modified standard, an enrollment transaction is usually generated only for new members in a health plan option and for those who change or terminate their coverage options. Therefore, collection of racial and ethnic data in the enrollment transaction alone will not provide information on the vast majority of health plan members who have not recently joined the plan or changed their coverage during a given year. Since the large majority of these enrollees are likely to use at least one covered service in a given year, collection of race and ethnicity on the 837 claims encounter transaction would be a viable way to consistently capture race and ethnicity for these members. As part of any future modifications to the HIPAA standard administrative transactions, some health plans advocate making race and ethnicity a required field on HIPAA standard enrollment transactions, as well as for claims/encounter transactions. Their objective is to achieve uniformity across data transactions, not only in how information is captured but also in how data are represented. Using Racial and Ethnic Data Although there are good data demonstrating disparities in care, there are limited strategies on how to reduce the existing gaps in health care outcomes for diverse populations. As health plans work on strategies to collect racial and ethnic data, they also are assessing how to best utilize the data to improve health outcomes. While we know there are some targeted interventions to improve access through outreach and understanding, unlike disease-specific interventions, effective population-specific interventions have not been identified. Many health plans—while acknowledging the potential value of racial and ethnic data—do not have a specifically defined program in mind for the use of such data.

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Eliminating Health Disparities: Measurement and Data Needs Our interviews demonstrated that there are many health plans incorporating—some in a more structured form than others—the conclusions of a report entitled Cultural Competence in Health Care: Emerging Frameworks and Practical Approaches (Betancourt, Green, and Carillo, 2002). The report outlined three levels of promising practices—organizational, systemic, and clinical—used by health care organizations to increase cultural competence. Practices such as providing on-site interpreters and involving community (member) representatives in quality improvement efforts, as well as integrating cultural competence into training for health care providers, are being discussed and incorporated in increasingly larger numbers into the health plan structure. Although health plans have implemented many changes in data collection efforts, there is no universal approach to the initiation of racial and ethnic data collection and cultural competence activities. Forty-two percent of the health plans interviewed indicated they had a CEO-level task force/ directive; 33 percent stated that racial and ethnic data collection and cultural competence efforts were simply integrated into the “daily activities” of the health plan; 13 percent replied that they used both processes; and 13 percent indicated that they had no “formal” program in place. As previously stated, some innovative health plan models are emerging that demonstrate the industry’s efforts to better understand the unique needs of the members and communities they serve, as well as the sociocultural influences on individual health beliefs and behaviors. The following section offers a few examples. Generic Examples of Health Plan Efforts to Collect and Use Racial and Ethnic Data One health plan is beginning to collect racial and ethnic data from its members via the enrollment form and in its disease management programs. This information is used for population-specific health improvement efforts, such as increasing Pap smear rates and the development of a maternity management program to decrease premature deliveries, as well as specific disease management programs. Through racial and ethnic data provided on membership satisfaction surveys, one health plan determined that members of Hmong descent showed lower than average levels of satisfaction. Subsequent interviews with the Hmong members revealed gaps in understanding of the workings/ process of the health system and cultural expectations of cures that resulted in frequent switching of providers. Peer education was initiated to communicate Hmong cultural expectations to providers and explanations of the health care system to Hmong members.

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Eliminating Health Disparities: Measurement and Data Needs A nationwide health plan is collecting information from indirect sources—such as requests from members for health plan materials in languages other than English, for providers with specific language capabilities, and for physician notes and medical records—to identify and recruit members for focus groups among specific diverse populations that will add to the body of knowledge in the literature on cultural approaches to health care promotion and chronic condition management. Another health plan uses the “primary language preference” information obtained from member enrollment forms, combined with efforts to identify members with more common Chinese names, to send Chinese language materials and to inform these members about services available through their plan’s Asian Initiative. Four large health plans in one market have collaborated with the state department of public health both to link member files with state public health data files on a project-specific basis (e.g., prenatal care and birth outcomes, stage of cancer at diagnosis) and to collaborate on state-funded surveys (e.g., Behavioral Risk Factor Surveillance System [BRFSS], Diabetes Control Program survey). These plans then have been able to assess access to and utilization of services as well as clinical quality measures for member subpopulations using the racial, ethnic, and SES data collected in the state databases and surveys. CONCLUSIONS Health plans recognize that cultural diversity and beliefs offer numerous challenges for the health care industry, as well as opportunities. Plans are interested in participating in a coordinated, directed effort to accelerate the collection of accurate racial and ethnic data. But obstacles to achieving this goal do exist. Currently, health plans have collected some racial and ethnic data, mainly through a number of indirect methods. Although these sources frequently are not sufficiently recognized or consistently utilized by health plans, health plans are working to improve access to appropriate, culturally sensitive health care and to decrease health disparities. Many of the barriers discussed in this paper could be removed through collaborative efforts to simplify, streamline, and coordinate methods of data collection as well as through agreement on racial and ethnic categories. Such efforts must then be coupled with a public education initiative, focused on the great utility and positive health effects that racial and ethnic data collection will provide. At the core of this effort is instilling (perhaps renewing) a sense of public trust that this information will be used with respect and only for the benefit of health plan members, that is will not place them in any jeopardy. Including champions from designated populations at all stages of racial and

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Eliminating Health Disparities: Measurement and Data Needs ethnic data collection efforts—from inception, to design, to implementation, application, and evaluation—has helped to achieve this goal in several communities. The use of racial and ethnic data in health plans’ disease management programs also has demonstrated the benefits of this information—improving the prevention or control of disease through targeted outreach, education, and follow-up. Regarding specific implementation efforts, while larger organizations have more flexibility in control of the human resources needed for change and to assemble task forces for this purpose, “going it alone” is not a viable option for the majority of health plans. For this reason, our respondents stated that the efforts they believed would be well received and prove most effective would include: regional collaborations; “mentorship” with smaller plans; coordinated public/private efforts toward the education of health plans and the health care industry regarding legal issues; information sharing and confidence building/assurances to the public about the intended and specific use of racial and ethnic data; and standardization of data collection methods. The collection of racial and ethnic data on the populations served by health plans is an initial step toward the development of a truly culturally competent health care system. Understanding the factors that prevent minorities from obtaining quality health care and how those factors interact with the health care system is key to closing the gap in health care access and outcomes between majority and minority populations. Race and ethnicity data collection offers opportunities for health plans and providers to focus on their members’ diverse values, beliefs, and behaviors, and to tailor the structuring of their health care services to meet each patient’s social, cultural, and linguistic needs. Through these efforts, reaching the goal of quality health care that is effective, safe, patient-centered, and equitable for all Americans can be achieved. Recommendations Based on our findings, we make the following recommendations: Development of a coordinated, uniform approach across the health care industry to accelerate the collection of accurate racial and ethnic data, which would include input and active participation from health plans, employers, and federal and state governments. Efforts that would be most effective and well received may include: Community-based collaborations that simplify, streamline, and coordinate methods of data collection. Mentorship initiatives with “smaller” health plans. Development of a strong business case for reporting by employers.

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Eliminating Health Disparities: Measurement and Data Needs Public/private efforts to educate the health plans and industry about legal issues. Information sharing and confidence building to instill public understanding and trust in proper use of collected data. Standardizing data collection methods developed with leadership from the federal government (HIPAA—or similar national approach—would move this effort beyond the type of plan within which an individual may be enrolled). Recognition, designation, and support of “champions” from designated populations to lead and guide the collection of racial and ethnic data at all stages. Identification of models that work to balance the extensive research concentrating on gaps in health care quality linked to race and ethnicity. Funding of new research directed at specific methods of how to reduce or eliminate “gaps” in medical care experienced by some racial and ethnic minorities. This would include identification of specific factors that prevent culturally diverse populations from obtaining quality health care and how these factors interact with the health care system. Review of Federal Policies and Practices and State Laws Regarding Racial and Ethnic Data Collection Federal Level A study by The Commonwealth Fund (Perot and Youdelman, 2001) delineated the context in which health-related data collection and reporting by race, ethnicity, and primary language takes place at the federal level, particularly within the U.S. DHHS. The authors conducted a survey of the statutes, regulations, policies, and procedures of federal agencies to identify when the collection and reporting of such data are required and assessed the interpretation and implementation of existing laws and regulations, as expressed by 60 respondents associated with the administration of health care services. Four major findings emerged from the investigation: Collection and reporting of data on race, ethnicity, and primary language are legal and authorized under Title VI of the Civil Rights Act of 1964. No federal statutes prohibit this collection, although very few require it. An increasing number of federal policies emphasize the need for obtaining racial and ethnic data. There is high-level agreement that primary language data should be collected as well.

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Eliminating Health Disparities: Measurement and Data Needs General agreement prevails that racial, ethnic, and primary language data are critical to promote health and quality health care for all Americans. Despite these findings, federal data collection is not uniform. Data requirements and methods for collection and reporting vary across federal agencies and do not fully reflect consensus on the value of gathering this information (Perot and Youdelman, 2001). State Level Four states—(California, Maryland, New Hampshire, and New Jersey)—have laws or regulations barring health plans from collecting data on race and ethnicity. This prohibition has a significant impact on racial and ethnic data collection, as these states have high HMO penetration rates: California, 48.5 percent; Maryland, 27.8 percent; New Hampshire, 25.9 percent; and New Jersey, 27 percent. The regulations are summarized in the following sections: California3 California has a provision in its insurance code that prohibits health insurers from identifying or requesting an applicant’s race, color, religion, ancestry, or national origin on an insurance application. Since managed care organizations (other than Preferred Provider Organizations [PPO]) are not subject to the insurance code, they are not bound by this provision. Note: The DMHC has collected information from MCOs to determine how they address any cultural and linguistic barriers faced by their members. The Office of the Patient Advocate surveyed all the MCO chief executive officers in the state concerning their cultural and linguistic access policies. The responses were voluntary and the results were incorporated into a recently published consumer report card. A table showing some of the services HMOs provide for their members in other languages or in American Sign Language, such as interpreter services and written materials, is available at the California Office of the Patient Advocate’s Web site at http://www.opa.ca.gov/report_card/. Maryland4 Maryland has a statute that prohibits the collection of certain racial or ethnic data. The statute states that “an insurer … may not make an in- 3   Cal. Ins. Code $$ 20, 688.5, 700, 740, 742, 10141, and 12921; Cal. Health and Safety Code $ 1341. 4   Md. Code Ann. [Insurance] $27-501 (c).

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Eliminating Health Disparities: Measurement and Data Needs quiry about race, color, or national origin in an insurance form, questionnaire, or other manner of requesting general information that relates to an application for insurance.” New Hampshire5 The New Hampshire Insurance Department (NHID) regulation provides that “questions of race or color are prohibited” with regard to all “application forms used in connection with an insurance contract, whether or not attached to that contract.” New Jersey6 The New Jersey Department of Banking and Insurance (DBI) has certain regulations that prohibit the collection of racial and ethnic data under certain circumstances. Per the regulation, application forms for individual health insurance “shall not include questions that pertain to race, creed, color, national origin or ancestry of the proposed insured.” The DBI prohibition is applied only in the narrow realm of insurance application forms and not at any other point of the process of providing coverage. REFERENCES Arday, S.L., D.R. Arday, S. Monroe, and J. Zhang 2000 HCFA’s racial and ethnic data: Current accuracy and recent improvements. Health Care Finance Review 21(4):107-116. Betancourt, J.R., A.R. Green, and J.E. Carrillo 2002 Cultural Competence in Health Care: Emerging Frameworks and Practical Approaches. New York: The Commonwealth Fund. Collins, K.S., D.L. Hughes, M.M. Doty, B.L. Ives, J.N. Edwards, and K. Tenney 2002 Diverse Communities, Common Concerns: Assessing Health Care Quality for Minority Americans. (Findings from the Commonwealth Fund 2001 Health Care Quality Survey.) New York: The Commonwealth Fund. Nerenz, D.R., V.L. Bonham, R. Green-Weir, C. Joseph, and M. Gunter 2002 Eliminating racial/ethnic disparities in health care: Can health plans generate reports? Health Affairs 21(3):259-263. Perot, R.T., and M. Youdelman 2001 Racial, Ethnic, and Primary Language Data Collection in the Health Care System: An Assessment of Federal Policies and Practices. New York: The Commonwealth Fund. 5   N.H. Admin. Rules, Ins. 401.01(i) (5). 6   N.J.A.C. $ 11:4-16.7(a)(1); N.J. Stat. $17B:27A-2.