Getting Better Hospital Alarm Sounds Into a Global Standard

Abstract

<jats:p> The reserved set of audible alarm signals embodied within the global medical device safety standard, IEC 60601-1-8, is known to be problematic and in need of updating. The current alarm signals are not only suboptimal, but there is also little evidence beyond learnability (which is known to be poor) that demonstrates their performance in realistic and representative clinical environments. In this article, we describe the process of first designing and then testing potential replacement audible alarm signals for IEC 60601-1-8, starting with the design of several sets of candidate sounds and initial tests on learnability and localizability, followed by testing in simulated clinical environments. We demonstrate that in all tests, the alarm signals selected for further development significantly outperform the current alarm signals. We describe the process of collecting considerably more data on the performance of the new sounds than exists for the current sounds, which ultimately will be of use to end users. We also reflect on the process and practice of working with the relevant committees and other practical issues beyond the science, which also need constant attention if the alarms we have developed are to be included successfully in an updated version of the standard. </jats:p>

The Importance of Testing Sets of Clinical Alarm Sounds and Navigating Tradeoffs to Translate Research Findings into Implementation

“…The collection of perceptual, attentional, collaborative, and workload issues that comprise the alarm problem are all well understood by the human factors and systems engineering communities (Cvach, 2012;Woods, 1995), even if the guidance from these communities is not often incorporated into commercially available clinical alarms. Clinical alarms have been shown to have chronically low discriminability (Edworthy et. al, 2018;Sanderson, Wee, & Lacherez, 2006), poor learnability (Sanderson, Wee, & Lacherez, 2006;Wee & Sanderson, 2006;Williams & Beatty, 2005), low informativeness (Rayo & Moffatt-Bruce, 2015), and an inability to convey appropriate meaning (Patterson, 1989).…”

“…Although the low performance of the majority of clinical alarms is well-known, the path to designing and implementing high-performing alarms is unclear. Despite the abundance of available knowledge, efforts to effectively resolve the clinical alarm problem have proven unsuccessful over the last 30 years (Block, 2008;Cvach, 2012;Edworthy et. al, 2018;Edworthy & Hellier, 2006;Rayo & Moffat-Bruce, 2015;Sanderson et.…”

“…Given over 65% of organizational change efforts fail (Beer & Nohria, 2000;Burnes, 2004) regardless of their scientific backing, it comes as no surprise that successful clinical alarm implementations of any kind are rare. This implementation task becomes nearly impossible when trying to utilize the strongest science available due to the expertise gaps (Edworthy et. al, 2018) and folk models (Dekker & Hollnagel, 2004) that currently surround the clinical alarm problem, as well as the added costs, time, and complications associated with introducing science-based solutions into practice (Collins, 2011;Eccles et.…”

“…These factors have led to the large-scale design and use of opinion-based and scientifically unsound clinical alarm interventions (Edworthy et. al, 2018;Rayo & Moffat-Bruce, 2015), which has resulted in ineffective and failed attempts at resolving the alarm problem in healthcare (Block, 2008;Cvach, 2012;Edworthy, 2014;Edworthy et. al, 2018;Edworthy & Hellier, 2006;Sanderson et.…”

“…The field of human factors offers many scientifically sound insights that could provide more permanent and effective solutions to the burdens of the clinical alarm problem (Edworthy, 2018;Rayo, 2015;Patterson, 1989;Welch et. al, 2016).…”