Recent research by first author Seunghwan (Nigel) Kim, MS, BIDS PhD student, and supporting authors Benjamin Warner, MS, Daphne Lew, PhD, MPH, Sunny Lou, MD, PhD, and Thomas Kannampallil, PhD, introduces “action entropy” as a measure to assess cognitive effort in electronic health record (EHR) tasks. By analyzing EHR audit logs, neural language models were used to train and validate the measure. Attention switching scenarios showed higher action entropy compared to non-switching scenarios, indicating increased cognitive burden. This LM-based metric has potential as a screening tool for evaluating cognitive effort in EHR workflows. Exciting progress in understanding cognitive load in healthcare.
PhD student develops novel EHR cognitive effort measure
