Harnessing Implementation Science to Increase the Impact of Health Equity Research

Health disparities are differences in health or health care between groups based on social, economic, and/or environmental disadvantage. Disparity research often follows 3 steps: detecting (phase 1), understanding (phase 2), and reducing (phase 3), disparities. Although disparities have narrowed over time, many remain.

We argue that implementation science could enhance disparities research by broadening the scope of phase 2 studies and offering rigorous methods to test disparity-reducing implementation strategies in phase 3 studies.

We briefly review the focus of phase 2 and phase 3 disparities research. We then provide a decision tree and case examples to illustrate how implementation science frameworks and research designs could further enhance disparity research.

Most health disparities research emphasizes patient and provider factors as predominant mechanisms underlying disparities. Applying implementation science frameworks like the Consolidated Framework for Implementation Research could help disparities research widen its scope in phase 2 studies and, in turn, develop broader disparities-reducing implementation strategies in phase 3 studies. Many phase 3 studies of disparity-reducing implementation strategies are similar to case studies, whose designs are not able to fully test causality. Implementation science research designs offer rigorous methods that could accelerate the pace at which equity is achieved in real-world practice.

Disparities can be considered a "special case" of implementation challenges-when evidence-based clinical interventions are delivered to, and received by, vulnerable populations at lower rates. Bringing together health disparities research and implementation science could advance equity more than either could achieve on their own.