Converting to Connect: A Rapid RE-AIM Evaluation of the Digital Conversion of a Clerkship Curriculum in the Age of COVID-19

Abstract

Background: With the advent of the 2019 coronavirus pandemic, a decision was made to remove medical students from clinical rotations for their own safety. This forced students on a core emergency medicine (EM) rotation at McMaster University to immediately cease all in-person activities. An urgent need for a virtual curriculum emerged.

Methods: A virtual curriculum consisting of asynchronous case-based learning on Slack, ask-me-anything webinars, and online e-modules was created to fill the need. We describe a program evaluation using the RE-AIM framework and a social networking analysis of participants.

Results: Medical students (n = 23) and 11 facilitators (five residents, six faculty members) participated in this pilot study. Faculty members sent a mean (±SD) of 115 (±117) messages (n = 6), and mean (±SD) message counts for students and residents were 49.96 (±25; n = 23) and 39 (±38; n = 5), respectively. A total of 62,237 words were written by the participants, with a mean of 1,831 per person. Each message consisted of a mean (±SD) of 25 words (±29). Students rapidly acquitted themselves to digital technology. Using the RE-AIM framework we highlight the feasibility of a virtual curriculum, discuss demands on faculty time, and reflect on strategies to engage learners.

Conclusions: The use of asynchronous digital curricula creates opportunities for faculty-resident interaction and engagement. We report the successful deployment of a viable model for undergraduate EM training for senior medical students in the COVID-19 era of physical distancing.

Figure 1

Three depictions of our digital clerkship’s reach. (A) Histogram for message frequency based on the time (2‐hours slots) of the day cases sent (i.e., how messages sent after each message based on the duration). (B) Highlights how often each of our user types checked the Slack interface within a given 24‐hour period. (C) Depicts the interactions network in Slack case‐based asynchronous learning.