Evidence map›Paper›PMID 38352290›Full record

ReviewInternational journal of nursing sciences2024

The effect of intelligent management interventions in intensive care units to reduce false alarms: An integrative review.

Bingyu Li, Liqing Yue, Huiyu Nie, Ziwei Cao, Xiaoya Chai, Bin Peng, Tiange Zhang, Weihong Huang

Open access · goldAbstract readReview
In one paragraph

Review in International journal of nursing sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Alert burden when monitoring patients' vital signs continuously at home.Journal of clinical monitoring and computing · 2026
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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

8 authors at 1 institution in 1 country.

Bingyu LiTeaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Liqing YueTeaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Huiyu NieTeaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Ziwei CaoTeaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Xiaoya ChaiXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Bin PengXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Tiange ZhangXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Weihong Huang"Mobile Health" Ministry of Education - China Mobile Joint Laboratory, Xiangya Hospital of Central South University, Changsha, Hunan, China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: In intensive care units (ICU), frequent false alarms from medical equipment can cause alarm fatigue among nurses, which might lead to delayed or missed responses and increased risk of adverse patient events. This review was conducted to evaluate the effectiveness of intelligent management interventions to reduce false alarms in ICU. Method: Following the framework of Whitmore and Knafl, the reviewers systematically searched six databases: PubMed, EMBASE, CINAHL, OVID, Cochrane Library, and Scopus, and studies included intelligent management of clinical alarms published in the English or Chinese language from the inception of each database to December 2022 were retrieved. The researchers used the PICOS framework to formulate the search strategy, developed keywords, screened literature, and assessed the studies' quality using the Joanna Briggs Institute-Meta-Analysis of Statistics, Assessment, and Review Instrument (JBI-MAStARI). The review was preregistered on PROSPERO (CRD42023411552). Results: Seven studies met the inclusion criteria. The results showed that different interventions for intelligent management of alarms were beneficial in reducing the number of false alarms, the duration of alarms, the response time to important alarms for nurses, and the alarm fatigue levels among nurses. Positive results were found in practice after the application of the novel alarm management approaches. Conclusion: Intelligent management intervention may be an effective way to reduce false alarms. The application of systems or tools for the intelligent management of clinical alarms is urgent in hospitals. To ensure more effective patient monitoring and less distress for nurses, more alarm management approaches combined with artificial intelligence will be needed in the future to enable accurate identification of critical alarms, ensure nurses are responding accurately to alarms, and make a real difference to alarm-ridden healthcare environments.

Indexed as

Artificial intelligenceClinical alarmsIntensive care unitsNursesPhysiologic monitoringSafety management

Identifiers

PMID38352290
PMCPMC10859571
OpenAlexW4389719841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.