Barriers and facilitators to intraorganizational collaboration in public health: Relational coordination across public health services targeting individuals and populations.

BACKGROUND: Modern public health emphasizes population-focused services, which may require collaborative work both across and within organizations. Studies have explored interorganizational collaborations, but there are little data regarding collaborations within public health organizations. PURPOSE: We measured intraorganizational collaboration and identified barriers and facilitators to collaboration within a large public health department through a mixed-methods study. METHODOLOGY/APPROACH: Our study occurred at the Maricopa County (Arizona) Department of Public Health, the third largest local public health jurisdiction in the United States. To measure collaboration, we surveyed staff using the relational coordination tool. To identify barriers and facilitators to collaboration, we performed key informant interviews with department personnel. RESULTS: Relational coordination scores varied according to the focus of the service; clinical services had significantly lower levels of relational coordination than population-focused services (p < .01). We found high levels of mutual respect and lower levels of shared knowledge across services. Facilitators to collaboration included purposive cross-program meetings around specific topics, the organization's structure and culture, and individuals' social identities. Barriers included raised expectations for collaboration, low slack resources, member's self-interest, and trust. CONCLUSION: The relational coordination of services varied significantly according to the focus of the service. Population-focused public health services had higher levels of relational coordination than individually focused services. Collaboration was facilitated and impeded by both well-known and potentially emergent factors, such as purposive cross-service meetings and organizational culture. PRACTICE IMPLICATIONS: Population-focused services possessed higher levels of collaboration than individually focused services. Intraorganizational collaboration for improved population health relies on deliberate support from senior management and structured activities to increase shared knowledge and mutual respect.

Partnership capacity for community health improvement plan implementation: findings from a social network analysis.

BACKGROUND: Many health departments collaborate with community organizations on community health improvement processes. While a number of resources exist to plan and implement a community health improvement plan (CHIP), little empirical evidence exists on how to leverage and expand partnerships when implementing a CHIP. The purpose of this study was to identify characteristics of the network involved in implementing the CHIP in one large community. The aims of this analysis are to: 1) identify essential network partners (and thereby highlight potential network gaps), 2) gauge current levels of partner involvement, 3) understand and effectively leverage network resources, and 4) enable a data-driven approach for future collaborative network improvements. METHODS: We collected primary data via survey from n = 41 organizations involved in the Health Improvement Partnership of Maricopa County (HIPMC), in Arizona. Using the previously validated Program to Analyze, Record, and Track Networks to Enhance Relationships (PARTNER) tool, organizations provided information on existing ties with other coalition members, including frequency and depth of partnership and eight categories of perceived value/trust of each current partner organization. RESULTS: The coalition's overall network had a density score of 30 %, degree centralization score of 73 %, and trust score of 81 %. Network maps are presented to identify existing relationships between HIPMC members according to partnership frequency and intensity, duration of involvement in the coalition, and self-reported contributions to the coalition. Overall, number of ties and other partnership measures were positively correlated with an organization's perceived value and trustworthiness as rated by other coalition members. CONCLUSIONS: Our study presents a novel use of social network analysis methods to evaluate the coalition of organizations involved in implementing a CHIP in an urban community. The large coalition had relatively low network density but high degree centralization-meaning key organizations link organizations otherwise not tightly partnering. Coalition members rated each other highly on trust, a positive sign for future partnership development efforts. Examination of network maps reveal key organizations that can be targeted for future partnership facilitation and expansion. Future network data collection will enable exploration of longitudinal trends and exploration of network characteristics versus health behavior, status, and outcome changes.