Alarm-inducing variability in cardiac postoperative data and the effects of prealarm delay

Aki Mäkivirta, Erkki Koski

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)

Abstract

Objective. Our objective was to study the distribution of invasively measured hemodynamic data to enhance the reliability of patient monitor alarm systems.Methods. Monitoring data were collected, preprocessed off-line, and analyzed in 10 postcardiac surgery patients. The data were studied statistically to estimate the probability distributions, the probability of alarm at various probability levels in these distributions, the effect of theprealarm delay to the alarm probability, and the effect of preprocessing the monitoring data using one- or multidimensionalmedian filtering. Results. Fifteen percent of all registered values fell outside of commonly applied alarm limits. Doubling the prealarm delay from 5 to 10 sec reduced the mean alarm rate by 26%. A further decrease of 8% in the alarm rate was observed when a multidimensional vector median filter was used to remove the variable value interdependencies.Conclusions. Brief excursions beyond clinically optimal alarm limits were frequent and can occur without leading to significant degradation of the patient’s state. Preprocessing can decrease the alarm rate effectively. Multidimensional preprocessing may produce more reliable alarms than one-dimensional processing.

Original languageEnglish
Pages (from-to)153-162
Number of pages10
JournalJournal of Clinical Monitoring
Volume10
Issue number3
DOIs
Publication statusPublished - 1994
MoE publication typeA1 Journal article-refereed

Fingerprint

Hemodynamics

Cite this

@article{00650ffa794149dd98d1feaf1b68b1c6,
title = "Alarm-inducing variability in cardiac postoperative data and the effects of prealarm delay",
abstract = "Objective. Our objective was to study the distribution of invasively measured hemodynamic data to enhance the reliability of patient monitor alarm systems.Methods. Monitoring data were collected, preprocessed off-line, and analyzed in 10 postcardiac surgery patients. The data were studied statistically to estimate the probability distributions, the probability of alarm at various probability levels in these distributions, the effect of theprealarm delay to the alarm probability, and the effect of preprocessing the monitoring data using one- or multidimensionalmedian filtering. Results. Fifteen percent of all registered values fell outside of commonly applied alarm limits. Doubling the prealarm delay from 5 to 10 sec reduced the mean alarm rate by 26{\%}. A further decrease of 8{\%} in the alarm rate was observed when a multidimensional vector median filter was used to remove the variable value interdependencies.Conclusions. Brief excursions beyond clinically optimal alarm limits were frequent and can occur without leading to significant degradation of the patient’s state. Preprocessing can decrease the alarm rate effectively. Multidimensional preprocessing may produce more reliable alarms than one-dimensional processing.",
author = "Aki M{\"a}kivirta and Erkki Koski",
year = "1994",
doi = "10.1007/BF02908855",
language = "English",
volume = "10",
pages = "153--162",
journal = "Journal of Clinical Monitoring and Computing",
issn = "1387-1307",
publisher = "Springer",
number = "3",

}

Alarm-inducing variability in cardiac postoperative data and the effects of prealarm delay. / Mäkivirta, Aki; Koski, Erkki.

In: Journal of Clinical Monitoring, Vol. 10, No. 3, 1994, p. 153-162.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Alarm-inducing variability in cardiac postoperative data and the effects of prealarm delay

AU - Mäkivirta, Aki

AU - Koski, Erkki

PY - 1994

Y1 - 1994

N2 - Objective. Our objective was to study the distribution of invasively measured hemodynamic data to enhance the reliability of patient monitor alarm systems.Methods. Monitoring data were collected, preprocessed off-line, and analyzed in 10 postcardiac surgery patients. The data were studied statistically to estimate the probability distributions, the probability of alarm at various probability levels in these distributions, the effect of theprealarm delay to the alarm probability, and the effect of preprocessing the monitoring data using one- or multidimensionalmedian filtering. Results. Fifteen percent of all registered values fell outside of commonly applied alarm limits. Doubling the prealarm delay from 5 to 10 sec reduced the mean alarm rate by 26%. A further decrease of 8% in the alarm rate was observed when a multidimensional vector median filter was used to remove the variable value interdependencies.Conclusions. Brief excursions beyond clinically optimal alarm limits were frequent and can occur without leading to significant degradation of the patient’s state. Preprocessing can decrease the alarm rate effectively. Multidimensional preprocessing may produce more reliable alarms than one-dimensional processing.

AB - Objective. Our objective was to study the distribution of invasively measured hemodynamic data to enhance the reliability of patient monitor alarm systems.Methods. Monitoring data were collected, preprocessed off-line, and analyzed in 10 postcardiac surgery patients. The data were studied statistically to estimate the probability distributions, the probability of alarm at various probability levels in these distributions, the effect of theprealarm delay to the alarm probability, and the effect of preprocessing the monitoring data using one- or multidimensionalmedian filtering. Results. Fifteen percent of all registered values fell outside of commonly applied alarm limits. Doubling the prealarm delay from 5 to 10 sec reduced the mean alarm rate by 26%. A further decrease of 8% in the alarm rate was observed when a multidimensional vector median filter was used to remove the variable value interdependencies.Conclusions. Brief excursions beyond clinically optimal alarm limits were frequent and can occur without leading to significant degradation of the patient’s state. Preprocessing can decrease the alarm rate effectively. Multidimensional preprocessing may produce more reliable alarms than one-dimensional processing.

U2 - 10.1007/BF02908855

DO - 10.1007/BF02908855

M3 - Article

VL - 10

SP - 153

EP - 162

JO - Journal of Clinical Monitoring and Computing

JF - Journal of Clinical Monitoring and Computing

SN - 1387-1307

IS - 3

ER -