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Healthcare Alarm Ontology and Science-based Design Improves Alarm Response

CSEL director Dr. Mike Rayo and eternal friend (and alumna!) of the lab Dr. Emily Patterson completed work on their recent P30 grant awarded from the Agency for Healthcare Research and Quality (AHRQ) by publishing two papers, one with CSEL student C.J. Hansen, demonstrating the benefits of using the human factors and cogntive psychology literature to explicitly design a single alarm system that successfully conveys multiple human-triggered and machine-triggered events and their associated urgencies.

The overall study lays out the alarm ontology that was used to ensure that different alarm events could be discerned from each other and were not masked by environmental sounds or other alarms. It also describes the actual design decisions that were made to translate the ontology into actual alarm sounds and escalation strategies.
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The second study and paper demonstrates the effectiveness of the ontology in reducing the alarm response time for the most urgent alarms, specifially the Code Blue alarm which indicates that a patient is in cardiac arrest.
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These studies are unique in that the results did not come from laboratory experiments, but by measuring alarm duration and observing alarm response throughtout a tertiary-care medical center spanning multiple hospitals and care settings. This required expertise in data science to collect, interpret, and analyze the data (thanks to co-author Dr. Ted Allen for his work in selecting and performing the most appropriate data analysis techniques). It also required a deep partnership between the research and the day-to-day operations of the medical center with support from the administration, spearheaded by co-authors Todd Yamokoski and Dr. Susan Moffatt-Bruce. We truly hope that this work inspires upcoming work on alarm design across multiple industries, helping us all grapple with the increasingly onerous alarm problems that the proliferation of beeping, booping, alarming devices is contributing to.