Task, Usability, and Error Analyses of Ambulance-based Telemedicine for Stroke Care

Abstract

Past research has established that telemedicine improves stroke care through decreased time to treatment and more accurate diagnoses. The goals of this study were to 1) study how clinicians complete stroke assessment using a telemedicine system integrated in ambulances, 2) determine potential errors and usability issues when using the system, and 3) develop recommendations to mitigate these issues. This study investigated use of a telemedicine platform to evaluate a stroke patient in an ambulance with a geographically distributed caregiving team comprised of a paramedic, nurse, and neurologist. It first determined the tasks involved based on 13 observations of a simulated stroke using 39 care providers. Based on these observational studies, a Hierarchical Task Analysis (HTA) was developed, and subsequently, a heuristic evaluation was conducted to determine the usability issues in the interface of the telemedicine system. This was followed by a Systematic Human Error Reduction and Prediction Approach (SHERPA) to determine the possibility of human error while providing care using the telemedicine work system. The results from the HTA included 6 primary subgoals categorizing the 97 tasks to complete the stroke evaluation. The heuristic evaluation found 123 unique violations to heuristics, with an average severity of 2.38. One hundred and thirty-one potential human errors were found with SHERPA, the two most common being miscommunication and selecting an incorrect option. Several recommendations are proposed, including improvement of labeling, consistent formatting, rigid or suggested formatting for data input, automation of task structure and camera movement, and audio/visual improvements to support communication.