Utilizing Social Network Data for Quality Improvement through Strategic Network Management: Simulation Exercise

Today's public health conceptual orientation has shifted to a systems framework that considers connections among different components requiring multi-disciplinary collaborative thinking and active engagement of those who have a stake in the outcome. This shift presents new challenges for public health administrators, particularly managers of programs and people in this new “networked system”. Specifically, this has left administrators asking “How can we demonstrate our collaborative efforts?” and further, “How can we translate data and information into practical management strategies?” Although collaboration with the public health sector, operationalized in this research as “networks”, can be highly beneficial, resulting in communities of practice, shared learning, resource, exchange, increased community capacity, among other examples and has been widely accepted, they are complex forms, and thus, difficult to understand, manage, and lead. People are used to working and managing within hierarchies rather than across them, leading to problems and challenges that limit the potential of networks.

While there are forums for discussing how organizational effectiveness might be improved, organizational administrators and network leaders have little guidance on how best to effectively design and manage a network. Specifically, public health departments are looking for resources on how to evaluate their collaborative processes and use these data and information systems to systematically inform management decisions. Although the increased use of network data is evident, management strategies based on these data are lacking. There is a growing need within the public health sector for literature, research, and tools on how to use network data to engage in strategic collaborative management. Public health departments are seeking input from strategists, consultants, and academics to help them engage in evaluation and planning. The time is ripe for a guiding piece on how to use network data as an informative approach to improving collaboration in the sector. This is particularly true for the collection and growing use of social network analysis, a method that is rather new in the area of public health, and outside the technical capability of most administrators and facilitators. Social Network Analysis (SNA) is the study of the structural relationships among interacting units and the resulting effect on the network. Structural relationships refer to the number and quality of connections among the members of a network. For example, the strength of relationships between network members or the types and levels of resources exchanged can explain the structural relationships. The fundamental property of this method is the ability to determine how connected actors in a network influence one another. SNA provides a way, through mathematical algorithms, to measure the number and lengths of ties in order to index these tendencies. Although the use of network analysis as a way to assess collaboration is more common now than ever, the question of how to use these types of data to make improvements to collaborative activity, specifically by developing action steps for performance improvement of the public health system has been left unanswered. This course introduces the concept of Strategic Collaborative Management (SCM) and how it can assist public health administrators and facilitators engaged in collaboration to understand how and why networks develop, what conditions influence success, how the benefits of networks can be improved while the minimizing drawbacks, and how to more effective be a leader within a network.

The objective of this course is to demonstrate a data-driven management approach to effectively implement quality improvement (QI) in public health collaboratives, in turn providing basis for an strategic management approach. QI efforts include four basic phases – Plan, Do, Study, Act. Strategic Collaborative Management takes a QI approach by providing public health personnel with a framework to study their collaborative efforts by collecting network data using existing tools and act upon this data by strategically using data to develop action steps for performance improvement. These steps loop back into the Plan and Do stages of QI. Using a modeled simulation, this course will utilize network data to demonstrate how SCM can be implemented and informed by data.