Evidence map›Paper›PMID 37934335›Full record

ArticleJournal of medical systems2023

Alert-Grouping: Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle with Alarm Fatigue in Intensive Care.

Shai Rozenes, Adi Fux, Ilya Kagan, Moran Hellerman, Boaz Tadmor, Arriel Benis

Abstract read
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In one paragraph

Article in Journal of medical systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Shai RozenesFaculty of Industrial Engineering and Technology Management, Holon Institute of Technology, Holon, 5810201, Israel.
Adi FuxAfeka Tel Aviv Academic College of Engineering, Tel Aviv-Yafo, 6910717, Israel. adif@afeka.ac.il.
Ilya KaganDepartment of General Intensive Care, Institute of Nutrition Research, Rabin Medical Center, Belinson Hospital, Petach Tikva, 49100, Israel.
Moran HellermanDepartment of General Intensive Care, Institute of Nutrition Research, Rabin Medical Center, Belinson Hospital, Petach Tikva, 49100, Israel.
Boaz TadmorResearch Authority, Rabin Medical Center, Belinson Hospital, Petach Tikva, 49100, Israel.
Arriel BenisDepartment of Digital Medical Technologies, Holon Institute of Technology, Holon, 5810201, Israel. arrielb@hit.ac.il.
Holon Institute of Technology · ILRabin Medical Center · ILTel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Intensive Care Units (ICUs), patients are monitored using various devices that generate alerts when specific metrics, such as heart rate and oxygen saturation, exceed predetermined thresholds. However, these alerts can be inaccurate and lead to alert fatigue, resulting in errors and inaccurate diagnoses. We propose Alert grouping, a "Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle Alarm Fatigue in Intensive Care" model. The alert grouping looks at patients at the individual and cluster levels, and healthcare-related constraints to assist medical and nursing teams in setting personalized alert thresholds of vital parameters. By simulating the function of ICU patient bed devices, we demonstrate that the proposed alert grouping model effectively reduces the number of alarms overall, improving the alert system's validity and reducing alarm fatigue. Implementing this personalized alert model in ICUs boosts medical and nursing teams' confidence in the alert system, leading to better care for ICU patients by significantly reducing alarm fatigue, thereby improving the quality of care for ICU patients.

Indexed as

Clinical AlarmsBenchmarkingCritical CareHumansIntensive Care UnitsPatient Care TeamAlarm fatigueAlert fatigueIntensive care unitsPatient safetyPersonalized medicineQuality of health care

Identifiers

PMID37934335
OpenAlexW4388462368

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.