title: False alarms during patient monitoring in clinical intensive care units are highly related to poor quality of the monitored electrocardiogram signals.
abstract: Electrocardiograms (ECGs) recorded from patients in intensive care were investigated to quantify any relationship between ECG signal quality and false monitoring alarms. False alarms are a considerable problem for nursing and medical staff as they distract from clinical care, and are also a problem for patients as they disturb rest, which is important for clinical recovery. ECG and alarm data were obtained for 750 patient alarms from the PhysioNet database. The final 8 s period before the alarm was triggered was investigated. All but one ECG channel in 38 ECG recordings with out-of-range data were associated with false positive alarms (p  <  0.0001). The frequency contributions for baseline (BL) instability, electromyogram (EMG) muscle noise, and high frequency (HF) noise were calculated. For all three frequency bands, the contributions associated with false positive alarms were very significantly greater than for true positive alarms (p  <  0.0001). The greatest difference was for BL with a mean level for false positive alarms 4.0 times greater than for true positive alarms, followed by EMG and HF at 1.6 times and 1.4 times respectively. These results confirm that attention needs to be taken to improve ECG signal quality to reduce the frequency of clinical false alarms, and hence improve conditions for clinical staff and patients.
authors.affiliation: School of Electrical & Electronic Engineering, Newcastle University, Newcastle upon Tyne, UK.
authors.forename: Charalampos
authors.initials: C
authors.lastname: Tsimenidis
authors.forename: Alan
authors.initials: A
authors.lastname: Murray
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000503:physiopathology; D056902:Clinical Alarms; D004562:Electrocardiography / Q000295:instrumentation*; D005189:False Positive Reactions; D006801:Humans; D007362:Intensive Care Units; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D011786:Quality Control; D012815:Signal Processing, Computer-Assisted