Computer Assisted Patient Monitoring: Associated Patient, Clinical and ECG Characteristics and Strategy to Minimize False Alarms

Abstract

This chapter is a review of studies that have examined false arrhythmia alarms during in-hospital electrocardiographic (ECG) monitoring in the intensive care unit. In addition, we describe an annotation effort being conducted at the UCSF School of Nursing, Center for Physiologic Research designed to improve algorithms for lethal arrhythmias (i.e., asystole, ventricular fibrillation, and ventricular tachycardia). Background: Alarm fatigue is a serious patient safety hazard among hospitalized patients. Data from the past five years, showed that alarm fatigue was responsible for over 650 deaths, which is likely lower than the actual number due to under-reporting. Arrhythmia alarms are a common source of false alarms and 90% are false. While clinical scientists have implemented a number of interventions to reduce these types of alarms (e.g., customized alarm settings; daily skin electrode changes; disposable vs. non-disposable lead wires; and education), only minor improvements have been made. This is likely as these interventions do not address the primary problem of false arrhythmia alarms, namely deficient and outdated arrhythmia algorithms. In this chapter we will describe a number of ECG features associated with false arrhythmia alarms. In addition, we briefly discuss an annotation effort our group has undertaken to improve lethal arrhythmia algorithms.

The Application of Computer Techniques to ECG Interpretation

“…The article by Pelter et al [8] highlights the problem and outlines an attempt to produce a database of ECGs from patients being monitored that will ultimately lead to an enhancement of algorithms for accurate detection of significant arrhythmias. Current algorithms have a very high percentage of false positive often to the extent that nursing staff simply turn off the alarms in order to avoid continuous interruption for checking what frequently turns out to be a false alarm.…”

"CER-S, an ECG Platform for the Management of Continuous ECG Recordings and Databases"

“…In a notable example, it has been used in a study to validate an atrial fibrillation algorithm in patients simultaneous wearing a commercial patch and a Samsung smartwatch, with a total of 81,944 hours of collected data [6]. The software is also used as viewer for Intensive Care unit bedside monitors alarms annotations with the aim of generating a gold standard of correct/false arrhythmia alarms [7][8].…”

Orthogonality-Constrained CNMF-Based Noise Reduction with Reduced Degradation of Biological Sound

“…In addition, the collection and analysis of measurement data can be applied as a diagnostic aid for physicians or for automated diagnosis. Several biological measurement devices have already been commercialized, such as bedside monitors and electronic stethoscopes used in hospitals [ 12 , 13 ]. The bedside monitor displays multiple vital signs, such as the electrocardiogram, respiratory information, and body temperature of the patient.…”