Improving Student EHR Accuracy: An Analysis of Training Methods to Better Prepare Students to Volunteer at Student-Run Clinics

Abstract

Background: As many students do not have previous experience with electronic health records (EHRs), the Comprehensive Medical Care Outreach Team at the University of Central Florida repeatedly struggled to maintain an accurate and consistent record of patient visits, despite all volunteers attending a lecture-based training session prior to clinic day. This study evaluated changes in student EHR accuracy at this student-run clinic using alternative training methods. We hypothesized that small-group interactive learning would result in higher EHR accuracy than lecture-style learning.

Methods: This study examined EHR accuracy through one year (2019) of data over four clinic sessions. EHR accuracy was defined as completion and correctness of various EHR parameters, consisting of electronically signing notes, medications, allergies, diagnoses, vital signs triage, and subjective, objective, assessment, and plan notes. For the first two clinics, students were trained using large group lecture-style learning, with a lecturer to volunteer ratio of 1:70. For the latter two clinics, students were trained in small-groups based on clinic role, in rooms with an average lecturer to volunteer ratio of 1:8. In these sessions, students then actively utilized the EHR by annotating a standardized patient case before the clinic.

Results: Data shows significant differences (p<0.05) in EHR accuracy of large-group versus small-group training for 11 of 18 parameters, with all parameters demonstrating an increase in accuracy in the experimental groups.

Conclusions: These results indicate that small-group, interactive learning affords greater EHR accuracy than large group lecture-style learning, suggesting more efficient ways to perform EHR training.