Perceived reliability of medical device alarms—a major determinant of medical errors driven by frozen medical thinking

This concept paper introduces the phenomenon of self-assigning a 'perceived reliability' value to medical device readings as a potential source of cognitive bias in medical decision-making. Medical errors can result from clinical decisions based on partial clinical data despite medical device readings providing data to the contrary. At times, this results from clinician distrust of medical device output. Consequentially, clinicians engage in a form of 'frozen thinking', a fixation on a particular thought process despite data to the contrary. Many medical devices, such as intensive care unit (ICU) monitors and alarms, lack validated statistics of device output reliability and validity. In its absence, clinicians assign a self-perceived reliability value to device output data and base clinical decisions therefrom. When the perceived reliability value is low, clinicians distrust the device and ignore device readings, especially when other clinical data are contrary. We explore the cognitive and theoretical underpinnings of this 'perceived reliability' phenomenon. The mental assignment of a perceived reliability value stems from principles of 'script theory' of medical decision-making. In this conceptual framework, clinicians make decisions by comparing current situations to mental 'scripts' of prior clinical decisions and their outcomes. As such, the clinician utilizes scripts of prior experiences to create the perceived reliability value. Self-assigned perceived reliability is subject to multiple dangers of reliability and cognitive biases. Some of these biases are presented. Among these is the danger of dismissing device readings as 'noise'. This is particularly true of ICU alarms that can emit frequent false alarms and contribute to clinician sensory overload. The cognitive dangers of this 'noise dismissal' are elaborated via its similarity to the phenomenon of 'spatial disorientation' among aviation pilots. We conclude with suggestions for reducing the potential bias of 'perceived reliability'. First presented are regulatory/legislative and industry-based interventions for increasing the study of, and end-user access to, validated device output reliability statistics. Subsequently, we propose strategies for overcoming and preventing this phenomenon. We close with suggestions for future research and development of this 'perceived reliability' phenomenon.