Modelling the interactive behaviour of users with a medication safety dashboard in a primary care setting

Objective: To characterise the use of an electronic medication safety dashboard by exploring and contrasting interactions from primary users (i.e. pharmacists) who were leading the intervention and secondary users (i.e. non-pharmacist staff) who used the dashboard to engage in safe prescribing practices. Materials and methods: We conducted a 10-month observational study in which 35 health professionals used an instrumented medication safety dashboard for audit and feedback purposes in clinical practice as part of a wider intervention study. We modelled user interaction by computing features representing exploration and dwell time through user interface events that were logged on a remote database. We applied supervised learning algorithms to classify primary against secondary users. Results: We observed values for accuracy above 0.8, indicating that 80% of the time we were able to distinguish a primary user from a secondary user. In particular, the Multilayer Perceptron (MLP) yielded the highest values of precision (0.88), recall (0.86) and F-measure (0.86). The behaviour of primary users was distinctive in that they spent less time between mouse clicks (lower dwell time) on the screens showing the overview of the practice and trends. Secondary users exhibited a higher dwell time and more visual search activity (higher exploration) on the screens displaying patients at risk and visualisations. Discussion and conclusion: We were able to distinguish the interactive behaviour of primary and secondary users of a medication safety dashboard in primary care using timestamped mouse events. Primary users were more competent on population health monitoring activities, while secondary users struggled on activities involving a detailed breakdown of the safety of patients. Informed by these findings, we propose workflows that group these activities and adaptive nudges to increase user engagement.