The presentation describes efficient and effective computational methods to evaluate an interprofessional education program. Methods from natural language processing were used to assess common themes that emerged from the text of PowerPoint presentations that teams of interprofessional students created as a part of an advocacy project.
Over 700 students from nine different health professions programs across the university are grouped into teams of five to six students, and work with a community volunteer, a Health Mentor for three semesters. Each team is comprised of at least three different professions.
The advocacy project focuses on person-centered care and social determinants of health, initiated by student teams. The lighting talk will feature an assessment method to explore themes that reflect the IPEC core competencies of: values/ethics, roles and responsibilities, interprofessional communication, and teams and teamwork. The lightning talk will inform educators and clinicians on how to use natural language processing tools to identify salient words and themes in the advocacy projects; and discuss the implications of the identified themes for interprofessional teams and community members. Both of the methods described make use of word frequencies in collections of text documents to reveal hidden structure in document sets. Natural language processing can increase the efficiency of curriculum evaluation for IPEC competencies, and promote improved interprofessional education, by facilitating the analysis of large numbers of written assignments and by informing qualitative analysis.
Through natural language processing we will demonstrate how our advocacy project results in student engagement of person-centered care and social determinants health. The advocacy project is based on the Social-Ecological Model that encompasses individual, family, community, and policy factors. The presentation will use the advocacy project that is completed by the student teams that focuses on the policy factors of concern to their community volunteer.