Larry R. Hearld, PhD; Jeffrey A. Alexander, PhD; Jeff Beich, PhD; Jessica N. Mittler, PhD; and Jennifer L. O’Hora, BA
Healthcare alliances (ie, multi-stakeholder community partnerships) may be defined as voluntary organizations that bring together a diverse array of stakeholders (eg, physicians, hospitals, insurers, employers and other purchasers, consumers) to work collaboratively on a variety of health-related issues in a community. Healthcare alliances are increasingly being examined as a potential solution for problems of fragmentation that undermine coordination across the continuum of care and contribute to poor-quality care.1,2
However, because alliances are by definition composed of stakeholders from different industry sectors, balancing the diverse and sometimes divergent goals of stakeholders with the goals of the alliance can be a challenging endeavor. Weiner and Alexander suggest that reconciling “turf issues” is a critical governance activity that requires alliance-governing bodies to engage in 2 key tasks: (1) aligning the interests of partner organizations with the interests of the partnership; and (2) resolving conflict arising from diverging interests or role ambiguity.3
Alignment is defined in this study as a shared understanding about the alliance’s vision, strategic goals, and sense of commitment, collaboration, and cooperation among stakeholders. In practical terms, stakeholder alignment facilitates more efficient and effective coordination of activity and serves as an important precursor to action.4,5
Despite the importance assigned to alignment in multi-stakeholder alliances, less attention has been devoted to identifying environmental and organizational conditions and activities that may facilitate or impede alignment.
The purpose of this study of 14 alliances participating in the Aligning Forces for Quality (AF4Q) initiative, a national program of the Robert Wood Johnson Foundation (RWJF) designed to help targeted communities improve the overall quality of healthcare, reduce racial and ethnic health disparities, and provide models for national reform, was to identify barriers to stakeholder alignment as well as strategies used by alliances to overcome these barriers. We use a mixed method analysis to compare and contrast alliances that have achieved different levels of stakeholder alignment. The findings of this study are likely to be of interest to alliance leaders and participants interested in identifying ways to promote alignment among diverse stakeholder groups. The findings are also likely to be of importance to policy makers and program designers (eg, funding agencies) interested in developing or supporting collaborative efforts to improve healthcare in local communities.Background and Conceptual Framework
In an alliance context, the combination of knowledge, skills, and resources of a diverse membership is believed to stimulate the alliance to think in different ways about how to achieve its goals, plan more comprehensive and integrated programs, and strengthen its relationship with the broader community.6 Analysts have proposed several important determinants of an alliance’s ability to combine these unique skills and knowledge bases in ways that can stimulate different ways of thinking about and achieving its goals. These determinants include stakeholder characteristics (eg, heterogeneity, level of involvement), relationships among stakeholders (eg, trust, respect, conflict), alliance characteristics (eg, leadership, governance), and the external environment of the alliance (eg, community characteristics, policy/political environment).6,7
Others have emphasized the contextual nature of alliances, particularly the temporal, emergent aspects of an alliance’s structure and management processes that influence how the component parts of the alliance are brought together.8-12
Based on the literature, we propose that there are 4 primary domains of activity that form the building blocks for stakeholder alignment in multi-sector alliances. Market context refers to factors outside the alliance that shape an alliance’s activities and programs. Alliance structure and governance refers to characteristics of the alliance that reflect and affect how an alliance is designed to function (eg, committee structure) and the processes used to manage alliance activities. Leadership relates to activities, attributes, or style of leaders. Alliance climate is the recurring patterns of behavior, attitudes, and feelings among stakeholders that characterize life in the alliance and shape interactions with other alliance participants. An overview of these domains and how they relate to one another is provided in the Figure
.Design and MethodsQuantitative Data Used to Determine the Level of Alignment
Quantitative data were drawn from an Internet-based survey of individuals and organizational representatives who were formal members (ie, leaders, staff, members-at-large) of 14 AF4Q alliances (data from additional alliances that joined the initiative in 2009-2010 are not included in this analysis). The survey was fielded over a 4-week period in each alliance between October 2008 and October 2009. The response rate was 48.6% (623 of 1283 possible respondents).
Alliances were categorized as more or less highly aligned based on an alignment index constructed from questions regarding alliance governance, leadership, and their participation in the alliance (eg, level, costs, and benefits). Based on our definition of alignment, 6 items were selected to assess the level of alignment achieved by alliances: (1) alliance vision (“The members of the alliance have a clear and shared vision of health in our community.”); (2) alliance purpose/ mission (“The purpose for which the alliance was formed is clear to me.”); (3) alliance strategy (“The alliance members are in agreement on the best strategies to achieve our priorities.”); (4) collaboration and cooperation among alliance members (“The alliance decision makers willingly collaborate and cooperate with each other.”); (5) commitment (“Based on my observations, the alliance members appear to be strongly committed to its success.”); and (6) differences of opinion (“Serious differences of opinion among the alliance members are rare.”). All 6 items were measured on a 5-point scale ranging from “strongly disagree” (1) to “strongly agree” (5). “Do not know” responses were coded as missing and dropped from the analysis.
To construct the alignment index, we first conducted an exploratory factor analysis (varimax rotation) on a half sample of survey respondents using the 6 survey items. The results of this analysis indicated a 2-factor structure, with the vision, mission, and strategy items loaded on 1 factor and the collaboration, commitment, and difference of opinion items loaded on the second factor. To confirm the factors identified in the exploratory factor analysis, we conducted a confirmatory factor analysis on the other half sample of respondents, which again indicated support for a 2-factor structure for the alignment construct (root mean squared error of approximation = 0.04; comparative fit index = 0.99). However, both analyses (factor loadings and modification indices) suggested that the purpose/mission item should not be incorporated in the alignment index; thus, this item was dropped from subsequent analysis.
Next, we used reliability (intraclass correlation coefficient 1; intraclass correlation coefficient 2) and inter-rater agreement (rwg; average deviation) statistics to assess whether individual-level responses could be reliably aggregated to the alliance level. Both sets of statistics supported aggregating the individual responses to the alliance level. Therefore, individual-level responses within an alliance were averaged separately for each alignment factor, with all items given equal weight. The alliances were then rank-ordered using the 2 scales. Because the 2 scales were highly correlated (r = 0.56), alliances that ranked highly on 1 scale also ranked highly on the second scale. Therefore, the final rank ordering was based on a composite alignment score that averaged the scores for the 2 factors, with both factors given equal weight.
Six of the 14 AF4Q alliances—the 3 alliances in the top quartile and the 3 alliances in the bottom quartile of the composite alignment score—were selected for more in-depth analysis with qualitative data. The average composite score for the 3 alliances in the bottom quartile was 3.4 compared with an average of 4.1 for the 3 alliances in the top quartile (range = 3.3-4.2). Composite scores for 2 of the 3 alliances in the top quartile were significantly greater than the composite scores for the alliances in the bottom quartile. Because we view alignment as a process that is measured on a continuum, rather than a discrete event measured in absolute terms, we describe these 2 groups of alliances as “more highly aligned alliances” (top quartile) and “less highly aligned alliances” (bottom quartile) in the remaining sections of this article.Qualitative Data Collection and Comparative Case Analysis
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