Mechanisms to enhance racial equity in health care: Developing a model to facilitate translation of the ACCURE intervention

Background:As medical and public health professional organizations call on researchers and policy makers to address structural racism in health care, guidance on evidence-based interventions to enhance health care equity is needed. The most promising organizational change interventions to reduce racial health disparities use multilevel approaches and are tailored to specific settings. This study examines the Accountability for Cancer Care through Undoing Racism and Equity (ACCURE) intervention, which changed systems of care at two U.S. cancer centers and eliminated the Black-White racial disparity in treatment completion among patients with early-stage breast and lung cancer. Purpose:We aimed to document key characteristics of ACCURE to facilitate translation of the intervention in other care settings. Methods:We conducted semi-structured interviews with participants who were involved in the design and implementation of ACCURE and analyzed their responses to identify the intervention's mechanisms of change and key components. Results:Study participants (n = 18) described transparency and accountability as mechanisms of change that were operationalized through ACCURE's key components. Intervention components were designed to enhance either institutional transparency (e.g., a data system that facilitated real-time reporting of quality metrics disaggregated by patient race) or accountability of the care system to community values and patient needs for minimally biased, tailored communication and support (e.g., nurse navigators with training in antiracism and proactive care protocols). Conclusions:The antiracism principles transparency and accountability may be effective change mechanisms in equity-focused health services interventions. The model presented in this study can guide future research aiming to adapt ACCURE and evaluate the intervention's implementation and effectiveness in new settings and patient populations.