National Center for Interprofessional Practice and Education IPE core data set and information exchange for knowledge...

Area of Science:

• Health Informatics
• Big Data Science
• Interprofessional Practice and Education (IPECP) Science

Background:

• Over 70 sites and 100+ Interprofessional Practice and Education (IPECP) programs in the U.S. have been supported since 2012.
• Program leaders contribute data to the National Center, informing the IPE Knowledge Generation approach.
• Advancing the science of interprofessional practice and education (IPE) is a key objective.

Purpose of the Study:

• To describe the evolution of the IPE Knowledge Generation approach.
• To explain how traditional research methods blend with health informatics and big data science.
• To promote collaboration and knowledge discovery among IPE program leaders.

Main Methods:

• Utilizing a structured process for guiding IPE program design and implementation.
• Focusing on learning and Quadruple Aim outcomes.
• Collecting a core data set and leveraging big data science for analysis.

Main Results:

• IPE Knowledge Generation integrates research, evaluation, health informatics, and big data.
• A comparable, sharable data set is collected in an information exchange.
• This enables analysis and knowledge generation to advance IPECP.

Conclusions:

• The IPE Knowledge Generation approach effectively synthesizes diverse methodologies.
• It fosters a collaborative environment for data sharing and discovery in IPECP.
• This methodology supports the advancement of IPECP science and outcomes.