Evidence map›Paper›PMID 41346076›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2025

Reducing False Alarm Rates and Workload in ICUs by Improving Arrhythmia Detection Algorithms of Patient Monitoring Systems.

Jiyoon Oh, You Rim Kim, Yong Ju Lee, Dae Keun Jeon, Ji Soo Choi, Jae-Sun Uhm, Chul-Min Ahn, Won Seuk Jang

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jiyoon OhDepartment of Medical Device Engineering and Management, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0009-0009-7872-2015
You Rim KimDepartment of Medical Device Engineering and Management, Yonsei University College of Medicine, Seoul, South Korea.
Yong Ju LeePatient monitoring Lab, Mediana Co., Ltd, Seoul, South Korea.
Dae Keun JeonPatient monitoring Lab, Mediana Co., Ltd, Seoul, South Korea.
Ji Soo ChoiDivision of Pulmonology, Allergy and Critical Care Medicine, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, South Korea.ORCID 0000-0003-2716-6775
Jae-Sun UhmDepartment of Cardiology, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0000-0002-1611-8172
Chul-Min AhnDivision of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, South Korea.ORCID 0000-0002-7071-4370
Won Seuk JangDepartment of Medical Device Engineering and Management, Yonsei University College of Medicine, Seoul, South Korea.ORCID 0000-0002-4925-3549

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Patient monitoring systems are widely used in intensive care units (ICUs) to monitor patient's conditions. A high false alarm rate can lead to alarm fatigue among nurses, increasing workload and stress. This study aimed to improve the accuracy of arrhythmia detection by enhancing the noise detection algorithm in patient monitoring systems and to determine whether false alarm rate and workload decreased through clinical trials. MATERIAL AND METHODS Trials were conducted on adult patients in the ICU at Yongin Severance Hospital who required continuous electrocardiogram (ECG) monitoring for at least 2 days. After the first trial, the noise detection algorithm of the M50 (investigational device) was improved, and a second trial was conducted to evaluate its performance. Both trials followed the same study design. During the study period, M50 and MX700 (comparator device) were applied simultaneously for 3 days. Arrhythmia alarms were reviewed by an independent evaluator who assessed false alarms by comparing them with the ECG signals. False alarm rates were compared between trials using the chi-square (χ²) test. RESULTS The clinical trial was conducted through 2 separate trials, with 17 and 11 participants, respectively. A comparative analysis of false alarm rates of the investigational device demonstrated a reduction from 71.75% to 27.61%. Statistical analysis using the chi-square test indicated a P value of 0.000 (<0.001), confirming a statistically significant difference. CONCLUSIONS The results of 2 trials demonstrated reductions in false alarm rate and NASA-TLX score. These findings suggest that enhancing the noise detection algorithm in the patient monitoring system improved arrhythmia detection accuracy and helped reduce nurses' workload.

Indexed as

Arrhythmias, CardiacClinical AlarmsAdultAgedAlgorithmsDetection AlgorithmsElectrocardiographyFemaleHumansIntensive Care UnitsMaleMiddle AgedMonitoring, PhysiologicWorkload

Identifiers

PMID41346076
PMCPMC12743425

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.