Virtual Enumerator's Training for Time and Motion Studies Using AI Scenarios

This paper presents the implementation of a virtual training program for enumerators conducting Time and Motion Studies using the WOMBAT methodology, as part of a project assessing healthcare workflows before the adoption of an Electronic Health Record system. The training employed digital tools, including Zoom meetings, Google Forms, the WOMBAT App, and AI-generated scenario images, to simulate clinical settings. The program successfully prepared observers for data collection, with high agreement among them. Even though its limitations, this study shares a remote training approach for TMS in geographically dispersed contexts, with potential for further integration of AI tools.