Abstract
ABSTRACT Since 2012, the National Center for Interprofessional Practice and Education has worked with over 70 sites implementing over 100 interprofessional education and collaborative practice (IPECP) programs in the United States (U.S.). Program leaders have contributed data and information to the National Center to inform an approach to advancing the science of interprofessional practice and education (IPE), called IPE Knowledge Generation. This paper describes how the evolution of IPE Knowledge Generation blends traditional research and evaluation approaches with the burgeoning field of health informatics and big data science. The goal of IPE Knowledge Generation is to promote collaboration and knowledge discovery among IPE program leaders who collect comparable, sharable data in an information exchange. This data collection then supports analysis and knowledge generation. To enable the approach, the National Center uses a structured process for guiding IPE program design and implementation in practice settings focused on learning and the Quadruple Aim outcomes while collecting the IPE core data set and the contribution of contemporary big data science.
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