***** To join INSNA, visit http://www.insna.org *****
The Center on Network Science at the University of Colorado Denver’s School of Public Affairs would like to share our upcoming trainings on building, managing, and evaluating collaborative networks. We hope you can join us in cultivating a community of network leaders!
Registration Now Open for the 5th Annual Network Leadership Training Academy
April 26-28, 2017, University of Colorado Denver
Many people today find themselves engaged in the “network way of working”- building, managing, and evaluating networks of people and organizations. Often as a way to leverage the collective knowledge
and resources of multiple organizations and communities to address complex social problems. However, traditional approaches to managing these processes primarily include practices that hinder our ability to foster new ways of working across boundaries.
The Network Leadership Training Academy (NLTA) is a 3-day interactive workshop for network leaders and members from across sectors to develop skills that reflect the adaptive and innovative needs of managing a diverse group of stakeholders. The NLTA creates a space for conversations about network leadership, activities to learn and demonstrate ideas and skills, and practical tools to more effectively manage your individual organization in a network context and lead inter-organizational networks.
For more information and the registration link visit: www.spa.ucdenver.edu/nlta Early registration pricing ends Friday, March 17 and event registration will close April 17. Discounted rates and scholarships (application due March 10) are available. Connect with us on Facebook: https://www.facebook.com/NetworkLeadershipTrainingAcademy
- A Mixed Methods Approach to Assess a Network Intervention of Public and Private Sector Partners: The Example of Million Hearts
Presenters: Dr. Malcolm Williams, RAND Corporation & Dr. Danielle Varda, Center on Network Science- CU Denver
Click here to register: https://ucdenver.zoom.us/webinar/register/06653495fc59ebd47c24e00bf0acd2b8
More and more a “network intervention” is the chosen approach for addressing complex public health issues. A network intervention “describes the process of using social network data
to accelerate behavior change or improve organizational performance; . . . social networks can be leveraged to accelerate behavior change, improve organizational efficiency, enhance social change, and improve dissemination and diffusion of innovations” (Valente
The Centers for Disease Control and Prevention (CDC) and Centers for Medicare and Medicaid Services (CMS) have implemented Million Hearts (MHI), an unprecedented initiative to coordinate efforts across the United States, with a goal to prevention of “1 million heart attacks and strokes by 2017.” A key strategy to achieving these goals is to implement policies to coordinate the public, private, and nonprofit sectors around these shared goals. This type of coordination could scale up the adoption and dissemination of proven clinical and community strategies to prevent heart disease and stroke, through relationship building, resources and knowledge exchange, program development, data sharing, and identification of best practices. Thus, there is a need to develop information and a data-informed evidence base about the success and challenges of the MHI, and methods for how this initiative might grow and strengthen to reach the goal of improving heart health and reducing heart disease.
In 2016 the RAND Corporation and the University of Colorado Denver implemented a qualitative and social network analysis to develop information and a data-informed evidence base about the success and challenges of the MHI, and methods for how this initiative might grow and strengthen to reach the goal of improving heart health and reducing heart disease. This webinar will report on the methods and results of the work.
Learn more about the Network Leadership Webinar Series and access recordings & slides from previous webinars at:
Network Leadership Training Academy, Center on Network Science, University of Colorado-Denver