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Cropp, Alan J.; Woods, Larry; Raney, Debra; Bredle, Donald L.

doi:10.1378/chest.105.4.1217

Cited by 90 publications

(7 citation statements)

References 10 publications

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“…The implications of frequent alerts are of importance. First, there is a risk of alarm fatigue, ignoring even critical alerts 34 . Second, alerts with low specificity to clinical complications (pneumonia, bleeding, arrhythmias, etc.)…”

Section: Discussionmentioning

confidence: 99%

“…First, there is a risk of alarm fatigue, ignoring even critical alerts. 34 Second, alerts with low specificity to clinical complications (pneumonia, bleeding, arrhythmias, etc.) may induce unnecessary investigations with the risk of inflicting iatrogenic injury despite self-limiting and allocating staff to patients without need.…”

Section: Ta B L E 1 Baseline Characteristicsmentioning

confidence: 99%

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Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Haahr-Raunkjær

Mølgaard

Elvekjær

et al. 2022

Acta Anaesthesiol Scand

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Background: Patients undergoing major surgery are at risk of complications, so-called serious adverse events (SAE). Continuous monitoring may detect deteriorating patients by recording abnormal vital signs. We aimed to assess the association between abnormal vital signs inspired by Early Warning Score thresholds and subsequent SAEs in patients undergoing major abdominal surgery.Methods: Prospective observational cohort study continuously monitoring heart rate, respiratory rate, peripheral oxygen saturation, and blood pressure for up to 96 h in 500 postoperative patients admitted to the general ward. Exposure variables were vital sign abnormalities, primary outcome was any serious adverse event occurring within 30 postoperative days. The primary analysis investigated the association between exposure variables per 24 h and subsequent serious adverse events.Results: Serious adverse events occurred in 37% of patients, with 38% occurring during monitoring. Among patients with SAE during monitoring, the median duration of vital sign abnormalities was 272 min (IQR 110-447), compared to 259 min (IQR 153-394) in patients with SAE after monitoring and 261 min (IQR 132-468) in the patients without any SAE (p = .62 for all three group comparisons). Episodes of heart rate ≥110 bpm occurred in 16%, 7.1%, and 3.9% of patients in the time before SAE during monitoring, after monitoring, and without SAE, respectively (p < .002). Patients withThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Discussionmentioning

confidence: 99%

Section: Ta B L E 1 Baseline Characteristicsmentioning

confidence: 99%

Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Haahr-Raunkjær

Mølgaard

Elvekjær

et al. 2022

Acta Anaesthesiol Scand

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“…Sık ve yüksek sesli çoklu alarmlar hem hasta güvenliği hem de sağlık profesyonellerinin sağlığını tehdit etmektedir (27) . Sağlık profesyonellerinin alarm seslerini ayırt edebilme düzeylerini araştıran bir çalışmada, sağlık profesyonellerinin kritik alarmların yalnızca %50'sini doğru şekilde belirleyebildiği belirlenmiştir (28) . Başka bir çalışmada, hemşirelerin monitörlü alanlardan uzaklaştıkça alarmı duyma hassasiyetlerinin azaldığı ve paralel olarak müdahalelerde gecikmelerin olduğu vurgulanmaktadır (29) .…”

Section: Alarm Yorgunluğu Ve Hasta Güvenliği Sorunlarıunclassified

Alarm Management In Intensive Care Units

Ergezen¹,

Kol²,

Ramazanoğlu³

2020

JAREN

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Sağlık hizmetlerinde kullanılan alarm sistemleri, hastada meydana gelebilecek olası sorunlar ve tehlikeli durumlarda sesli ve ışıklı yöntemler ile uyarı veren mekanizmalardır. Alarm sistemleri yoğun bakım ünitelerinde, hastanın durumundaki ani değişimleri belirlemek ve uygun müdahaleleri gerçekleştirmek amacıyla kullanılmaktadır. Alarm sistemleri, hasta güvenliği amacı ile sıklıkla kullanılmasına rağmen, bilgi ve yönetim eksikliğine bağlı sorunları da beraberinde getirmektedir. Bu makalede, alarm sistemleri ile ilgili kavramlar/tanımlar, alarm sistemleri ve hasta güvenliği ilişkisi, alarm yönetimi ile ilgili uygulamalar tartışılmıştır.

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“…ICU alarms produce sound intensities above 80 dB that can lead to sleep deprivation Chambrin (2001); Meyer et al (1994); Parthasarathy and Tobin (2004), inferior sleep structure Johnson (2001); Slevin et al (2000), stress for both patients and staff Cropp et al (1994); Novaes et al (1997); Topf and Thompson (2001); Morrison et al (2003) and depressed immune systems Berg (2001). There are also indications that the incidence of re-hospitalization is lower if disruptive noise levels are decreased during a patient's stay Hagerman et al (2005).…”

Section: Introductionmentioning

confidence: 99%

“…There are also indications that the incidence of re-hospitalization is lower if disruptive noise levels are decreased during a patient's stay Hagerman et al (2005). Furthermore, such disruptions have been shown to have an important effect on recovery and length of stay Donchin and Seagull (2002); Cropp et al (1994). In particular, cortisol levels have been shown to be elevated (reflecting increased stress) Topf and Thompson (2001); Morrison et al (2003), and sleep disruption has been shown to lead to longer stays in the ICU Parthasarathy and Tobin (2004).…”

Section: Introductionmentioning

confidence: 99%

False alarm reduction in critical care

et al. 2016

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High false alarm rates in the ICU decrease quality of care by slowing staff response times while increasing patient delirium through noise pollution. The 2015 Physio-Net/Computing in Cardiology Challenge provides a set of 1,250 multi-parameter ICU data segments associated with critical arrhythmia alarms, and challenges the general research community to address the issue of false alarm suppression using all available signals. Each data segment was 5 minutes long (for real time analysis), ending at the time of the alarm. For retrospective analysis, we provided a further 30 seconds of data after the alarm was triggered. A total of 750 data segments were made available for training and 500 were held back for testing. Each alarm was reviewed by expert annotators, at least two of whom agreed that the alarm was either true or false. Challenge participants were invited to submit a complete, working algorithm to distinguish true from false alarms, and received a score based on their program's performance on the hidden test set. This score was based on the percentage of alarms correct, but with a penalty that weights the suppression of true alarms five times more heavily than acceptance of false alarms. We provided three example entries based on well-known, open source signal processing algorithms, to serve as a basis for comparison and as a starting point for participants to develop their own code. A total of 38 teams submitted a total of 215 entries in this year's Challenge. This editorial reviews the background issues for this Challenge, the design of the Challenge itself, the key achievements, and the follow-up research generated as a result of the Challenge, published in the concurrent special issue of Physiological Measurement. Additionally we make some recommendations for future changes in the field of patient monitoring as a result of the Challenge.

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Name That Tone

Cited by 90 publications

References 10 publications

Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Continuous monitoring of vital sign abnormalities; association to clinical complications in 500 postoperative patients

Alarm Management In Intensive Care Units

False alarm reduction in critical care

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