Clinical and Translational Science Collaborative of Northern Ohio, Systems Marketing Analysis for Research Translation (SMART) Innovation Program

Case Western Reserve University, Cleveland OH

Investigators

Abstract

The Systems Marketing Analysis for Research Translation (SMART) Innovation Program brings a cutting-edge set of tools together to improve clinical and translational research effectiveness, efficiency, and scale-up to improve public health and health care delivery. The SMART Innovation Program supports CTSA Program Goals by (1) developing, demonstrating, and disseminating an operational innovation that improves the efficiency and effectiveness of clinical translational, (2) a structured, participatory method for promoting partnerships and collaborations to facilitate and accelerate translational research projects local, regionally, and nationally, and (3) creating and providing this with an explicit emphasis on addressing and deliver the benefits of translational science to all. More specifically, we build on our collective prior experience and collaboration combining community based-system dynamics as a participatory method for selection and tailoring of implementation strategies with a social marketing approach within a novel set-based concurrent engineering approach from manufacturing to accelerate translational research. Our primary hypothesis is that the integration of participatory system dynamics modeling with social marketing analysis can improve clinical and translational research effectiveness, efficiency, and population health by reducing the complexity of translational research. The SMART Innovation program is designed to work with clinical researchers at any stage of the translational research continuum with an emphasis on the design of implementation strategies that maximize implementation outcomes of fidelity, reach, and sustainability of innovations that promote population health. More specifically, SMART innovation program begins with group model building to understand the context of a population health gap and innovation, identifies strategies for scaling up one or more innovations, and applies concepts from social marketing to optimize the fit between innovations and the social context. Results include a systematic approach for reducing the complexity of translational research, improved dynamic fit between innovations and local and organizational contexts, and advances in program evaluation methods for continuous quality improvement in dynamic environments.