A Roadmap and Best Practices for Organizations to Reduce Racial and Ethnic Disparities in Health Care

Abstract

Over the past decade, researchers have shifted their focus from documenting health care disparities to identifying solutions to close the gap in care. Finding Answers: Disparities Research for Change, a national program of the Robert Wood Johnson Foundation, is charged with identifying promising interventions to reduce disparities. Based on our work conducting systematic reviews of the literature, evaluating promising practices, and providing technical assistance to health care organizations, we present a roadmap for reducing racial and ethnic disparities in care. The roadmap outlines a dynamic process in which individual interventions are just one part. It highlights that organizations and providers need to take responsibility for reducing disparities, establish a general infrastructure and culture to improve quality, and integrate targeted disparities interventions into quality improvement efforts. Additionally, we summarize the major lessons learned through the Finding Answers program. We share best practices for implementing disparities interventions and synthesize cross-cutting themes from 12 systematic reviews of the literature. Our research shows that promising interventions frequently are culturally tailored to meet patients' needs, employ multidisciplinary teams of care providers, and target multiple leverage points along a patient's pathway of care. Health education that uses interactive techniques to deliver skills training appears to be more effective than traditional didactic approaches. Furthermore, patient navigation and engaging family and community members in the health care process may improve outcomes for minority patients. We anticipate that the roadmap and best practices will be useful for organizations, policymakers, and researchers striving to provide high-quality equitable care.

Using Patient Race, Ethnicity, and Language Data to Achieve Health Equity

“…1 In this month's issue of JGIM, Klinger et al report important inaccuracies in REL data in electronic health records (EHRs) in 13 primary care clinics. 2 For example, 3 % and 6.6 % of patients who self-identified as Hispanic and African American, respectively, were not recorded as such in the EHR, and 20 % of persons documented in the EHRs as English-speaking elected to take a survey in Spanish.…”

“…REL data are useful for stratifying clinical performance measures to identify disparities and thus increase an organization's motivation and ability to address these disparities. 1 However, while over 90 % of American Hospital Association member hospitals reported collecting REL data in 2013, only 23 % declared that they used these data to identify disparities in clinical quality indicators. 6 Moreover, stratified clinical performance data alone generally do not improve clinical outcomes such as hemoglobin A1c control in patients with diabetes.…”

“…6 Moreover, stratified clinical performance data alone generally do not improve clinical outcomes such as hemoglobin A1c control in patients with diabetes. 1 Health care organizations should stratify clinical performance data by REL and then implement culturally tailored quality improvement interventions.…”

“…7 Several steps should be concomitant with improving REL data collection-and, in fact, facilitate this process-such as creating a culture of equity and getting buy-in for reducing disparities across all levels of the organization. 1 In addition, while organizations are developing the capability to accurately collect REL data, they can begin quality improvement interventions to reduce disparities. Organizations can ask their providers, staff, and patients to suggest areas that are the most important qualitatively to work on, pick low-hanging fruit, and work with enthusiastic early adopters.…”

“…We have to catch up in implementing proven methods for the accurate collection of REL data, and go beyond. 4 We must view REL data collection as one step in a comprehensive roadmap for reducing disparities, 1 and a building block for evolving analytical tools to improve health outcomes. 10 Today's opportunities for reducing health disparities are great.…”