Evidence map›Paper›PMID 29854451›Full record

ArticleCritical care research and practice2018

Design and Deployment of a Pediatric Cardiac Arrest Surveillance System.

Jordan Michel Duval-Arnould, Heather Marie Newton, Leann McNamara, Branden Michael Engorn, Kareen Jones, Meghan Bernier, Pamela Dodge, Cheryl Salamone, Utpal Bhalala, Justin M Jeffers and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Critical care research and practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Improved Cardiopulmonary Resuscitation Performance With CODE ACESJournal of the American Heart Association · 2018
    Observational
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

13 authors.

Jordan Michel Duval-ArnouldDivision of Health Sciences Informatics, Department of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0001-6050-9894
Heather Marie NewtonDepartment of Occupational Health, The Johns Hopkins Hospital, Baltimore, MD, USA.
Leann McNamaraDepartment of Pharmacy, The Johns Hopkins Hospital, Baltimore, MD, USA.
Branden Michael EngornDepartment of Anesthesiology and Critical Care Medicine and Department of Pediatrics, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.
Kareen JonesDepartment of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.
Meghan BernierDepartment of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.
Pamela DodgeDepartment of Pediatrics, The Johns Hopkins Hospital, Baltimore, MD, USA.
Cheryl SalamoneNeonatology Respiratory Therapy, The Johns Hopkins Hospital, Baltimore, MD, USA.
Utpal BhalalaDepartment of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.
Justin M JeffersDepartment of Pediatrics, The Johns Hopkins Hospital, Baltimore, MD, USA.
Lilly EngineerDepartment of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.
Marie Diener-WestDepartment of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
Elizabeth Anne HuntDivision of Health Sciences Informatics, Department of Anesthesiology and Critical Care Medicine, School of Medicine, The Johns Hopkins University, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aimed to increase detection of pediatric cardiopulmonary resuscitation (CPR) events and collection of physiologic and performance data for use in quality improvement (QI) efforts. MATERIALS AND

methodsWe developed a workflow-driven surveillance system that leveraged organizational information technology systems to trigger CPR detection and analysis processes. We characterized detection by notification source, type, location, and year, and compared it to previous methods of detection.

resultsFrom 1/1/2013 through 12/31/2015, there were 2,986 unique notifications associated with 2,145 events, 317 requiring CPR. PICU and PEDS-ED accounted for 65% of CPR events, whereas floor care areas were responsible for only 3% of events. 100% of PEDS-OR and >70% of PICU CPR events would not have been included in QI efforts. Performance data from both defibrillator and bedside monitor increased annually. (2013: 1%; 2014: 18%; 2015: 27%). DISCUSSION: After deployment of this system, detection has increased ∼9-fold and performance data collection increased annually. Had the system not been deployed, 100% of PEDS-OR and 50-70% of PICU, NICU, and PEDS-ED events would have been missed.

conclusionBy leveraging hospital information technology and medical device data, identification of pediatric cardiac arrest with an associated increased capture in the proportion of objective performance data is possible.

Identifiers

PMID29854451
PMCPMC5966697

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Registered trials

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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.