Improved Patient Monitoring with a Novel Multisensory Smartwatch Application

Abstract

The design of medical alarms has been heavily criticized in the past decade. Auditory medical alarms have poor learnability, discernibility, and relevance, leading to poor patient outcomes, and alarm fatigue, and overall poor informatic system design. We developed a novel trimodal patient monitoring smartwatch application for patient monitoring. Participants completed two phases: (1) control and (2) our novel trimodal system while identifying alarms (heart rate, oxygenation, and blood pressure) and completing a cognitively demanding task. Alarms were auditory icons presented as either solo or co-alarms. Participant performance was assessed by accuracy and response time (RT) of alarm identification. Using the novel system, accuracy was significantly improved overall (p < 0.01) and in co-alarm situations (p < 0.01), but not for solo alarms (p = 0.484). RT was also significantly faster (p < 0.01) while using the novel system for all alarm types. Participants reported decreased mental workload using the novel system. This feasibility study shows that our novel alarm system performs better than current standards. Improvements in accuracy, RT and perceived mental workload indicate the potential of this system to have a positive impact on medical informatic systems and clinical monitoring, for both the patient and the clinician.