Evidence map›Paper›PMID 40901502›Full record

ArticleFrontiers in medicine2025

Evidence-based practices for prevention and management of medical device alarm fatigue in anesthesia professionals.

Shaoru Chen, Jie Wang, Hui Zhi, Hongmei Zhang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shaoru ChenDepartment of Anesthesia and Perioperative Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
Jie WangDepartment of Anesthesia and Perioperative Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
Hui ZhiDepartment of Anesthesia and Perioperative Medicine, Henan Provincial People's Hospital, Zhengzhou, China.
Hongmei ZhangHenan Provincial Key Medicine Laboratory of Nursing, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess efficacy and implement the best available evidence for managing and preventing alarm fatigue in a healthcare context. Methods: Four phases of evidence acquisition, status review, evidence application, and effect evaluation were used to apply evidence-based practice to medical care in the PACU between January and June 2024. Prior to and following the application of evidence, the occurrence of unfavorable outcomes pertaining to the management of surgical patient monitors and anesthesia alarm reports, the degree of evidence-based organizational culture, the implementation rate of review indicators, and the associated knowledge level of alarm fatigue prevention and management were all compared. Results: Following the implementation of evidence-based practice, the indicators related to Anesthesiologists and nurses were reviewed, and the implementation rate was improved compared with the baseline. The frequency of negative outcomes associated with surgical patient monitoring and anesthesia alarm management was considerably decreased. Anesthesiology physicians' and nurses' knowledge of alarm fatigue management (t = -7.027, Conclusion: Continuous quality improvement is still required in subsequent clinical settings, but evidence-based practice in the Department of Anesthesiology and Perioperative Medicine can effectively standardize the alarm practice behaviors of healthcare professionals, enhance evidence-based competence, and lower the incidence of patient-related adverse events in alarm management.

Indexed as

alarm fatigueanesthesiologyevidence-based practicemanagementprevention

Identifiers

PMID40901502
PMCPMC12399625

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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.