Currently Viewing:
Supplements The Aligning Forces for Quality Initiative: Summative Findings and Lessons Learned From Efforts to Improve Healthcare Quality at the Community Level
The Aligning Forces for Quality Initiative: Background and Evolution From 2005 to 2015
Dennis P. Scanlon, PhD; Jeff Beich, PhD; Brigitt Leitzell, MS; Bethany W. Shaw, MHA; Jeffrey A. Alexander, PhD; Jon B. Christianson, PhD; Diane C. Farley, BA; Jessica Greene, PhD; Muriel Jean-Jacques,
Summative Evaluation Results and Lessons Learned From the Aligning Forces for Quality Program
Dennis P. Scanlon, PhD; Jeffrey A. Alexander, PhD; Megan McHugh, PhD; Jeff Beich, PhD; Jon B. Christianson, PhD; Jessica Greene, PhD; Muriel Jean-Jacques, MD, MAPP; Brigitt Leitzell, MS; Yunfeng Shi,
The Longitudinal Impact of Aligning Forces for Quality on Measures of Population Health, Quality and Experience of Care, and Cost of Care
Yunfeng Shi, PhD; Dennis P. Scanlon, PhD; Raymond Kang, MA; Megan McHugh, PhD; Jessica Greene, PhD; Jon B. Christianson, PhD; Muriel Jean-Jacques, MD, MAPP; Yasmin Mahmud, MPH; and Jeffrey A. Alexande
Reporting Provider Performance: What Can Be Learned From the Experience of Multi-Stakeholder Community Coalitions?
Jon B. Christianson, PhD; Bethany W. Shaw, MHA; Jessica Greene, PhD; and Dennis P. Scanlon, PhD
Improving Care Delivery at the Community Level: An Examination of the AF4Q Legacy
Megan McHugh, PhD; Jillian B. Harvey, MPH, PhD; Jaime Hamil, MPH; and Dennis P. Scanlon, PhD
From Rhetoric to Reality: Consumer Engagement in 16 Multi-Stakeholder Alliances
Jessica Greene, PhD; Diane C. Farley, BA; Jon B. Christianson, PhD; Dennis P. Scanlon, PhD; and Yunfeng Shi, PhD
Currently Reading
Lessons Learned About Advancing Healthcare Equity From the Aligning Forces for Quality Initiative
Muriel Jean-Jacques, MD, MAPP; Yasmin Mahmud, MPH; Jaime Hamil, MPH; Raymond Kang, MA; Philethea Duckett, MPA; and Juliet C. Yonek, MPH, PhD
Evaluating a Complex, Multi-Site, Community-Based Program to Improve Healthcare Quality: The Summative Research Design for the Aligning Forces for Quality Initiative
Dennis P. Scanlon, PhD; Laura J. Wolf, MSW; Jeffrey A. Alexander, PhD; Jon B. Christianson, PhD; Jessica Greene, PhD; Muriel Jean-Jacques, MD, MAPP; Megan McHugh, PhD; Yunfeng Shi, PhD; Brigitt Leitze
Participating Faculty
Letter From Donald M. Berwick, MD, MPP, Guest Editor
Donald M. Berwick, MD, MPP
The View From Aligning Forces to a Culture of Health
Carolyn E. Miller, MSHP, MA, and Anne F. Weiss, MPP
Leading Multi-sector Collaboration: Lessons From the Aligning Forces for Quality National Program Office
Katherine O. Browne, MBA, MHA; Robert Graham, MD; and Bruce Siegel, MD, MPH
Healthcare Reform Post AF4Q: A National Network of Regional Collaboratives Continues Healthcare Reform From the Ground Up
Elizabeth Mitchell and Dianne Hasselman, MSPH

Lessons Learned About Advancing Healthcare Equity From the Aligning Forces for Quality Initiative

Muriel Jean-Jacques, MD, MAPP; Yasmin Mahmud, MPH; Jaime Hamil, MPH; Raymond Kang, MA; Philethea Duckett, MPA; and Juliet C. Yonek, MPH, PhD
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 communitywide 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 communitywide 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.

Am J Manag Care. 2016;22:S413-S422
Eliminating health disparities has long been promoted as a key public health priority, yet healthcare systems and communities throughout the United States continue to struggle to achieve this aim.1 Aligning Forces for Quality (AF4Q), one of the Robert Wood Johnson Foundation’s (RWJF’s) foremost initiatives to improve the health and healthcare of communities across the United States, embraced the promotion of healthcare equity as a cornerstone of the program. Through the AF4Q initiative, which ran from 2006 to 2015, multi-stakeholder partnerships (hereafter referred to as alliances) of healthcare providers (hospitals and primary care centers), purchasers (health plans and large employers), and consumers (patients and community members), from each of the 16 geographically and demographically diverse communities, worked to advance the quality of care and provide models for national healthcare reform. This article provides an overview of the major activities undertaken by the 16 AF4Q multi-stakeholder alliances as they worked to reduce healthcare disparities, examines the alliance and community factors that were linked with success in advancing community capacity to address local disparities, and discusses the major lessons learned from the alliances’ experiences as they strove to simultaneously advance healthcare quality and equity.

Evolution of the Health Equity Agenda in the AF4Q Initiative

Reducing healthcare disparities was not an explicit objective of the AF4Q initiative when it launched in 2006. In the initial phase of the AF4Q program, alliances were asked to focus on advancing the overall quality of healthcare in their communities through attention to 3 main areas: healthcare system performance measurement and public reporting, implementation and dissemination of quality improvement strategies, and promotion of greater consumer engagement in healthcare.2 Reducing healthcare disparities by race, ethnicity, and primary language spoken (REL) was added as an explicit objective of the AF4Q initiative in 2008.

The alliances were expected to include stakeholders most relevant to achieving success in the original program aims of advancing public reporting, quality improvement, and community engagement, and were selected for participation in the AF4Q initiative based, in large part, on their anticipated potential to achieve success in these areas. However, because the alliances were not selected based on their anticipated potential to reduce disparities, they started the AF4Q program with variable levels of engagement with community organizations and other stakeholders that represent or serve racial and ethnic minority populations, varying levels of commitment to prioritizing efforts to reduce racial and ethnic disparities, and generally low levels of expertise combatting disparities. Few participating alliances had significant prior experience in addressing healthcare disparities, and only 1 of the AF4Q grant-holding organizations included disparities reduction as part of their mission prior to the AF4Q initiative.

A logic model outlining the assumptions and expectations of how the multi-stakeholder alliances would advance healthcare equity was developed by the evaluation team during the early years of the AF4Q initiative and is depicted in Figure 1. Briefly, to be effective, alliances were expected to engage relevant stakeholders to drive efforts aimed at reducing disparities. A focus on equity was to be integrated throughout the core AF4Q programmatic areas of performance measurement and reporting, quality improvement, and consumer engagement. Healthcare quality and outcome data stratified by REL would direct and refine the alliances’ efforts to achieve equitable health outcomes. Given the complexity of factors that contribute to health disparities, it was expected that factors internal and external to the AF4Q initiative would influence the strategies pursued by the alliance leadership and partnering stakeholders in each community.

The 16 AF4Q alliances were allowed some flexibility in addressing healthcare disparities, but they were guided by an evolving set of equity-focused directives laid out by the AF4Q National Program Office (NPO) as depicted in Figure 2. Initially, the alliances were charged with advancing the routine and standardized collection of data regarding patients’ REL by hospitals, primary care practices, and healthcare plans. These data were linked with healthcare quality and patient outcome measures to examine healthcare system performance stratified by REL. Healthcare performance data could be stratified at the hospital or primary care practice level to guide institution-level equity initiatives, or aggregated across the community to identify community-level trends and equity priorities. In 2011, the alliances were directed to focus on stratifying quality measures by REL and incorporating the reduction of healthcare disparities into their quality improvement and consumer engagement strategies. Beginning in 2013, the equity targets were expanded to include the reduction of disparities by markers of socioeconomic status (SES) (ie, privately insured vs uninsured or publicly insured) and geography (ie, rural vs urban) in addition to REL. During this final phase of the AF4Q initiative, alliances were encouraged to focus on achieving their self-determined equity objectives.


We used a qualitative approach to examine the equity-focused component of the AF4Q initiative across the 16 alliances. Our data sources included interviews with alliance directors and staff, triannual progress reports submitted by the alliances to RWJF, and alliance disparity verification reports. Six rounds of semi-structured interviews with alliance directors and disparities staff leads were conducted from 2010 to 2015. The interviews were conducted in person or by telephone, were 60 to 90 minutes in length, audio recorded, transcribed, and entered into Atlas.ti (Version 2013; Cologne, Germany), a qualitative software program. The interview transcripts were coded using a deductive and inductive approach.3 Data were initially coded using pre-identified theoretical constructs underlying disparity measurement and reduction. New codes were added during coding to capture additional themes, and this final set of disparities-related codes was applied to all transcripts. Each transcript was coded by one team member and reviewed by a different team member for quality assurance, and coding discrepancies were resolved through discussion. Qualitative data with the following codes were used to develop the verification summaries described below: activities, REL data collection, REL data use, and underserved populations. Qualitative data coded as barriers, facilitators, external forces, and advice were used to identify lessons learned. Triannual progress reports were submitted by the alliances to RWJF from 2008 through 2015. These provided information regarding activities, accomplishments, and challenges in each AF4Q program area. Based on data from the interviews and triannual reports, we drafted verification reports for each alliance that were submitted to the alliance directors and disparity staff leads from June 2015 through April 2016 for review and correction.

Our analysis consisted of a multi-step process. First, we created summary documents for each alliance detailing their activities in REL data collection, data reporting regarding local healthcare disparities, and disparities reduction interventions. Two authors independently ranked individual alliances’ efforts in each of these framework categories as high or low, and consensus was reached during team discussion. Alliances were considered to be high in disparity measurement if they produced quality reports stratified by REL or markers of SES on a repeated basis that included data from multiple providers and multiple payer types, whether or not these reports were publicly reported. Alliances were considered to be high in disparity-focused activities if they had several low-reach but high-intensity activities, or at least one high-reach activity. Low-reach activities were defined as those that involved less than 25% of hospitals, primary care practices, or healthcare consumers in the community; high-reach activities were those that involved at least 25%. Low-intensity activities were defined as those that involved a single or very small number of interactions (eg, a quarterly health fair at a church), targeted only one member of the healthcare team (eg, cultural competency training for physicians), or did not provide ongoing patient or provider support (eg, provision of language-concordant educational materials to patients with low English proficiency). High-intensity activities were defined as those that involved healthcare delivery redesign (eg, patient-centered medical home implementation), consisted of multiple members of the healthcare team (eg, care transitions program involving social work, nursing, and linkages to community resources), or included recurrent interactions with patients or care teams (eg, chronic disease management programs with patient self-management support). Activities that did not fall into one of these categories were ranked as high or low intensity based on group discussion and consensus.


Overall, from 2008 to 2015, the AF4Q alliances made low to modest gains toward routinely tracking local healthcare disparities, addressing disparities through their consumer engagement activities, and integrating attention to reducing disparities with their quality improvement strategies. This section summarizes the experiences of the 16 alliances, overall, as they worked to measure and reduce local healthcare disparities, describes the strategies and characteristics of the most successful alliances, and highlights the lessons learned from the alliances’ achievements and failures.

REL Data Collection

Most of the 16 alliances were not able to achieve high rates of standardized REL data by area hospitals and primary care practices by the end of the AF4Q initiative (Figure 3). None of the alliances succeeded in advancing the collection of REL data by healthcare plans.

Stratifying Healthcare Performance Measures by REL

Alliances struggled to advance the routine stratification of healthcare system performance measures by REL. Only 5 alliances reported that hospitals or primary care practices in their community reviewed their own quality measures stratified by REL on a regular basis. Although 7 alliances succeeded in aggregating data from multiple hospitals or primary care practices within their service area to examine community-level disparities by REL at least once, only 4 alliances produced and released these stratified quality reports, privately (to the alliance leadership and participating healthcare providers) or publicly, on a regular basis.  

Examples of Success in Tracking Local Healthcare Disparities

Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
Welcome the the new and improved, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up