Objective: The Robert Wood Johnson Foundation's (RWJF's) Aligning Forces for Quality (AF4Q) initiative aimed to advance healthcare quality and equity in 16 communities across the United States through multi-stakeholder alliances of healthcare payers, providers, and consumers. Our objectives are (1) to summarize the major approaches and activities undertaken by the AF4Q alliances that were most successful in tracking and implementing programs that aimed to reduce local healthcare disparities by race, ethnicity, and primary language spoken (REL), and socioeconomic status (SES); and (2) to identify the major lessons learned from the successes and failures of the AF4Q alliances to inform other equity-focused initiatives.
Methods: We analyzed data from 6 rounds of key informant interviews conducted between 2010 and 2015, and triannual progress reports submitted by the alliances to RWJF between 2008 and 2015.
Results: Of the 16 AF4Q alliances, 2 succeeded in developing community wide systems to track local healthcare disparities, 5 alliances implemented substantive programs that aimed to reduce local disparities, and 3 alliances were successful in disparity measurement and program implementation. The alliances that were most active in addressing disparities tended to have long-established relationships with relevant community organizations, focused on improving the quality of care provided by safety-net providers, and shifted quickly toward working to address disparities even if their initial efforts to stratify performance measures by REL failed.
Conclusion: Few alliances were able to develop community wide systems to track local healthcare disparities or implement large-scale initiatives to reduce disparities during the 7 years that these objectives were advanced by the AF4Q initiative. Establishing robust local disparity-tracking systems and establishing productive relationships with key community stakeholders took substantial time. The AF4Q experience suggests that efforts to reduce disparities should not be held up by disparity measurement challenges.