Evidence map›Paper›PMID 35213681›Full record

ArticleBiomedical instrumentation & technology2022

State of Science in Alarm System Safety: Implications for Researchers, Vendors, and Clinical Leaders.

Azizeh K Sowan, Nancy Staggers, Charles C Reed, Tommye Austin, Qian Chen, Shouhuai Xu, Emme Lopez

Abstract read
In one paragraph

Article in Biomedical instrumentation & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Review
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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

7 authors.

Azizeh K SowanAzizeh K. Sowan, PhD, RN, MSN, MSDA, MBA, FAAN is an associate professor in the School of Nursing at the University of Texas Health at San Antonio. Email: sowan@uthscsa.edu.
Nancy StaggersNancy Staggers, PhD, RN, FAAN is a professor in the School of Nursing and Department of Biomedical Informatics at the University of Utah in Salt Lake City. Email: nancystaggers@sisna.com.
Charles C ReedCharles C. Reed, PhD, RN, CNRN, is a vice president and associate chief nursing officer at the University Health System in San Antonio, TX. Email: charles.reed@uhs-sa.com.
Tommye AustinTommye Austin, PhD, MBA, RN, NEA-BC, is a senior vice president and chief nurse executive at the University Health System in San Antonio. Email: tommye.austin@uhs-sa.com.
Qian ChenQian Chen, PhD, is an assistant professor in the Department of Computer Science at the University of Texas at San Antonio. Email: guenevereqian.chen@utsa.edu.
Shouhuai XuShouhuai Xu, PhD, was affiliated with The University of Texas at San Antonio at the time this work was conducted; he currently is a professor in the Department of Computer Science at the University of Colorado Colorado Springs. Email: sxu@uccs.edu.
Emme LopezEmme Lopez is a librarian in the School of Nursing at the University of Texas Health at San Antonio. Email: lopeze13@uthscsa.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alarm fatigue is a complex phenomenon that needs to be assessed within the context of the clinical setting. Considering that complexity, the available information on how to address alarm fatigue and improve alarm system safety is relatively scarce. This article summarizes the state of science in alarm system safety based on the eight dimensions of a sociotechnical model for studying health information technology in complex adaptive healthcare systems. The summary and recommendations were guided by available systematic reviews on the topic, interventional studies published between January 2019 and February 2022, and recommendations and evidence-based practice interventions published by professional organizations. The current article suggests implications to help researchers respond to the gap in science related to alarm safety, help vendors design safe monitoring systems, and help clinical leaders apply evidence-based strategies to improve alarm safety in their settings. Physiologic monitors in intensive care units-the devices most commonly used in complex care environments and associated with the highest number of alarms and deaths-are the focus of the current work.

Indexed as

Clinical AlarmsMedical InformaticsElectrocardiographyIntensive Care UnitsMonitoring, Physiologic

Identifiers

PMID35213681
PMCPMC8979078

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.