The scientific knowledge and products that will be disseminated from D2V include analytic methods and application, training and educational materials, data management and analytic software, and open science and reproducibility methods.
Our dissemination approach is based on principles from Diffusion of Innovation Theory, the Patient-Centered Outcomes Research Institute dissemination framework, and marketing. The first component is designing for dissemination; dissemination starts at the point of idea generation when data science discoveries are first being developed. The second component includes dissemination tactics that integrate mass and interpersonal communication methods. Identifying audiences and engaging partners are fundamental to product development and dissemination planning. Unique features of the D2V dissemination strategy include:
- Consumer-centered -- the dissemination strategy is driven by the goals of D2Vand SOM Investigators,
- Multi-modal, integrated communication -- we will strategically use mass media and interpersonal communication channels to promote awareness and reputation of the Institute, and
- Adaptive and Responsive -- the strategic dissemination plan will be reviewed annually to refine strategies and tactics, culminating in a sustainability plan for continuing activities of greatest value.
This core also includes a specific focus on Academic-Industry Collaborations (AIC) with the goal of fostering mutually beneficial collaborations between D2V and innovative companies. The AIC will help to create market based learning objectives; contribute to an innovative health data science workforce; create knowledge exchange programs; establish networking and mentoring opportunities; partner in the design, development, validation, testing, adoption and penetration of digital science applications, products and services; and co-sponsor design projects.
Scholarship: Dissemination and Implementation (D&I) Sciences is a relatively new discipline in health research. The Dissemination Core will leverage and build on current D&I scholarly products and activities on the AMC. It will develop new models for dissemination of data sciences products that accelerate translation into practice and extend existing D&I methodologies to include the dissemination of new analytic methods and advanced software tools.