Exploring Health Plan Perspectives in Collecting and Using Data on Race, Ethnicity, and Language

In-depth interviews were conducted with 15 health plans to explore why plans collect or forgo race, ethnicity, and language (REL) data collection efforts, and the challenges encountered with collecting and using data for quality improvement.
Published Online: July 12, 2012
Julie Gazmararian, PhD, MPH; Rita CarreĆ³n, BS; Nicole Olson, MPH; and Barbara Lardy, MPH
Objectives: To explore why health plans collect or forgo data collection efforts on race, ethnicity, and language (REL), and the challenges encountered in collecting and using data for quality improvement.

Study Design: In-depth interviews with 15 health plans were conducted between June and August 2009.

Methods: Fifteen health plans participated and were divided into 2 groups: Plans that collect and use REL data (n = 10), and plans that do not collect REL data (n = 5). A structured interview guide was developed that included questions about REL data collection efforts, leadership support, collaboration with external partners, and challenges and opportunities in the collection and use of REL information. For plans not collecting REL data, questions were also asked regarding reasons to forgo data collection and existing health equity efforts. A summary report, based on audiotapes, interview notes, and input from the research team, was developed and analyzed.

Results: The interviews highlight the need for new partnerships and coordinated efforts to improve healthcare equity through disseminating best practices and tools that help expand such activities. Barriers noted include the costs associated with adapting information technology systems to accommodate new functions, such as new data fields, appropriate software and analytical tools, and the lack of standard codes for race and ethnicity.

Conclusions: Health plans are eager to collaborate with new partners and share strategies to collect REL data as a foundation to reduce disparities. Opportunities exist to collaborate with employers and purchasers to improve the extent and quality of REL data and can ultimately lead to designing and implementing culturally appropriate programs in the workforce.

(Am J Manag Care. 2012;18(7):e254-e261)
The information gathered during these interviews provides key stakeholders with a better understanding of decisions made by health plans to collect and utilize data on race, ethnicity, and language (REL) for quality improvement and disparity reduction efforts. This research highlights:

  • The need for new partnerships and coordinated efforts to improve healthcare equity through disseminating best practices and tools to help initiate or expand such activities.

  • Barriers to REL data efforts including the cost associated with adapting information technology systems to accommodate new functions, such as new data fields, appropriate software and analytical tools, and the lack of standard codes for race and ethnicity.
Over the last few decades, there has been increasing attention by leading public and private organizations1-3 and federal agencies4,5 on improving the collection of data on an individual’s race, ethnicity, and language preference (REL), assessing the underlying differences in quality of care among diverse populations,6 and monitoring the progress of culturally and linguistically appropriate programs and services.6-8

Many entities play key roles in obtaining REL data for improving healthcare equity, including health plans, hospitals, providers, community health centers, and employers/plan sponsors.9 Collaborative efforts will be important as the healthcare sector begins to adopt new models of care and increase access based on the Patient Protection and Affordable Care Act of 2010 (PPACA).

Since 2003, America’s Health Insurance Plans Foundation (AHIPF) has collaborated with the Robert Wood Johnson Foundation (RWJF) to assess the progress a number of health plans have made in the collection and use of REL data to reduce racial and ethnic disparities and improve healthcare quality.6,7,10,11 These assessments were conducted through national health plan surveys in 2003, 2006, 2008, and 2010. Based on the 2008 survey findings, health plan in-depth interviews were conducted in 2009 to explore challenges with data collection and use and develop successful strategies to improve care. The interviews provide key stakeholders with a better understanding of the health plans’ decisions to collect and utilize REL data for quality improvement and disparity reduction efforts.


Selection of Plans

Twenty health plans were selected to participate in in-depth interviews based on specific criteria referenced in Table 1. Fifteen health plans, representing the total enrollment of almost 53 million covered lives, agreed to participate and were divided into 2 groups: Health plans that indicated in the 2008 survey that they do collect and use data on the race and ethnicity of their members (n = 10 plans), and those plans that do not collect REL data (n = 5). Participating plans were classified by product (8 commercial, 4 Medicaid, and 3 Medicare plans), as well as size of membership enrollment (Table 2).

Development of Interview Guides

The interview guides included a series of themed questions about REL data collection efforts, leadership support, collaboration with external partners, and challenges to and opportunities for the collection and use of REL information (Table 3). For health plans that were not currently collecting REL data, questions were also asked regarding their reasons to forgo data collection and any existing health equity efforts. Prompts were developed for each question so that consistent probes would be used for each interview.

How Interviews Were Conducted

Interview questions were sent in advance to prepare the appropriate person(s) for the 1-hour interview. The interviews, conducted between June and August 2009, frequently were conducted by a comprehensive team including medical directors, analysts, and communications staff. All health plans were asked if the interview could be audiotaped; 14 of the 15 plans agreed to being recorded.


A summary report for each interview identified key themes based on leadership, organizational infrastructure, data collection and use, and partnerships. Any discrepancies in the interpretation of results were resolved between team members. Since the results are based on qualitative data, the findings are not presented numerically. However, to provide some estimate of how frequently particular themes appeared, terms like most (representing more than half of the participating plans), many (just under half of plans), and several, some, and few (mentioned by at least 2 plans) are used in the Results section.


Plans That Collect REL Data

Commercial, Medicare, and Medicaid plans that collect REL data varied dramatically in population and geographic region served; from 48,000 to more than 26 million members and from a region within a state to nationwide coverage. Collection of REL data began as early as 1985 in 1 health plan and as recently as 2007 in several others (Table 4).

Organizational Leadership and Infrastructure

We found that support from senior leadership is instrumental in initiating and sustaining the health plans’ REL data collection efforts. Advances in data collection often evolved at health plans whose efforts first focused on improving their workforce diversity from activities like conducting cultural competency training or establishing language access services. From these experiences, health plans recognized the importance of gaining a better understanding of their membership, in terms of both how their members seek healthcare, and what cultural norms and beliefs influence their health behaviors and attitudes. Health plans acknowledged that obtaining REL data was an essential step toward advancing quality improvement (QI).

Most of the interviews revealed that considerable time and effort was spent researching, planning, and laying the groundwork for a plan’s REL data collection activities. These efforts included identifying health information technology (IT) capabilities, appropriate software and analytical tools, databases, and storage requirements; determining data categories; establishing privacy and protection policies; training staff to obtain data from members and through proxy methods; and developing health equity reports.

Most health plans also discussed internal policies that support their commitment and accountability to workforce diversity and health equity. For example, 1 plan incorporates health disparities improvement measures into a corporate scorecard that forms the basis of employees’ bonuses and incentives, and into the company’s overall strategic plan. Another plan has cultural competency guidelines to inform culturally appropriate services, language access services, and accommodations

for members with special healthcare needs. Many plans indicated that they have internal policies on confidentiality and use of REL data.

REL Data Collection


Health plans indicated that they used both direct methods, data self reported by members, and indirect methods, such as data available from third parties (eg, Medicaid agency) or from geocoding and surname identification softwares. A few plans mentioned working with external organizations to strengthen indirect estimation methods. All health plans indicated that they consider selfreported REL data to be the “gold standard.” However, most plans reported that it is more difficult to collect REL data directly from their membership since members often do not understand the need for and use of this information.

Health plans described various strategies used to directly collect REL data. Methods include obtaining it at enrollment; during member participation in the plan’s disease management, wellness, case management, and dental programs; in health risk assessments; during calls to obtain missing laboratory information or encourage preventive screenings; during hospital admissions; from member contacts with customer service; and through the member portal of the health plan’s website. One plan mentioned that online newsletters and pop-up messages from its website encourage members to report REL data. Several plans indicated that they provide training to employees with direct member contact (eg, customer service, disease management) to teach them how to collect data and respond to members’ concerns about providing this information. A few plans discussed their efforts to incentivize providers to collect REL data from patients.


All health plans interviewed experience both internal and external challenges to collecting REL data. These challenges include regulatory and enterprise hurdles that prevent employer/plan sponsors from sharing enrollee data; the plan’s IT system capability to store and reconcile multiple data categories; the ability to share REL information across divisions within the plan and more broadly across the healthcare system; legal issues (real and perceived); member privacy concerns; the lack of provider understanding of the importance of collecting REL data; and requirements from compliance organizations. Many plans expressed a strong desire to educate the general public about the importance of collecting REL information. Furthermore, a few plans mentioned that competing priorities for limited resources and the impact of the recent economic decline impede data collection efforts.

The health plans expressed a strong interest in having standardized categories and consistent data metrics so data would be comparable, meaningful, and actionable across the healthcare sector. Most health plans also stated that they could not accurately determine the validity or completeness of REL data from available secondary sources. The lack of accurate and reliable REL data collected or obtained by federal and state agencies diminishes the plans’ ability to use these data to effectively

identify and act on disparities.

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