Journal des soins infirmiers et des soins

Heuristic Evaluation of Data Integration and Visualization Software Used for Continuous Monitoring to Support Intensive Care: A Bedside Nurses Perspective

Abstract

Ying Ling Lin, Anne-Marie Guerguerian, Peter Laussen and Patricia Trbovich

The Intensive Care Unit (ICU) is a complex and technologically advanced healthcare setting. Technologies enable continuous monitoring through patient signals that are sensed, recorded and displayed at the bedside. Although such technologies have significantly decreased mortality rates in the ICU, the large amounts of data have contributed to clinician information overload. Critical care nurses spend more than half of their time scanning and assimilating information from disparate monitors, at the bedside to assess the patient status. Software that integrates and allows visualization of large data sets on a single screen are now available. In the present study, we evaluated software entitled T3™ (Tracking, Trajectory and Triggering). Such computationally powerful software has great potential to support nurses’ monitoring and decision-making tasks but the usability, efficiency, and effectiveness of the software are key to end-user adoption. As such, we conducted a Heuristic Evaluation, where the study’s evaluators interacted with the software interfaces and were asked to comment on it by describing the usability issues and if they were in compliance with established usability principles, or heuristics, specifically for medical device interfaces. A total of 50 usability issues associated with 194 heuristic violations were found. Identified issues included difficulty with choosing the time period of the patient data signals, distinguishing between several patient signals and appearance of patient values which were imperceptible to evaluators; both issues could lead nurses to misinterpret the timing and/or the physiological status of the patient (e.g., time of shock and exact value of vitals). Heuristic evaluation, an efficient and inexpensive method, was successfully applied to the T3™ software to identify usability problems that if left unresolved could lead to patient safety issues. These findings may have broad implications for the design of the T3™ and other continuous monitoring systems.