Evidence map›Paper›PMID 32685694›Full record

ArticleTrauma surgery & acute care open2020

Pushing boundaries of video review in trauma: using comprehensive data to improve the safety of trauma care.

Brodie Nolan, Christopher M Hicks, Andrew Petrosoniak, James Jung, Teodor Grantcharov

Abstract read
In one paragraph

Article in Trauma surgery & acute care open, 2020. 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. Article
  2. Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
    Article
  3. Reliability of the safety threats and adverse events in trauma (STAT) taxonomy using trauma video review.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
    Article
  4. Introducing the Safety Threats and Adverse events in Trauma (STAT) taxonomy: standardized classification system for evaluating safety during trauma resuscitation.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2022
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. 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

5 authors.

Brodie NolanDepartment of Emergency Medicine, St Michael's Hospital, Toronto, Ontario, Canada.ORCID 0000-0003-2872-0643
Christopher M HicksDepartment of Emergency Medicine, St Michael's Hospital, Toronto, Ontario, Canada.
Andrew PetrosoniakDepartment of Emergency Medicine, St Michael's Hospital, Toronto, Ontario, Canada.
James JungDepartment of Surgery, University of Toronto, Toronto, Ontario, Canada.
Teodor GrantcharovDepartment of Surgery, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adverse events and lapses in safety are identified after the fact and often discussed through postevent review. These rounds rely on personal recollection, information from patient charts and incident reports that are limited by retrospective data collection. This results in recall bias and inaccurate or insufficient detail related to timeline, incidence and nature adverse events. To better understand the interplay of the complex team and task-based challenges in the trauma bay, we have developed a synchronized data capture and analysis platform called the Trauma Black Box (Surgical Safety Technologies, Toronto). This system continuously acquires audiovisual, patient physiological and environmental data from a sophisticated array of wall-mounted cameras, microphones and sensors. Expert analysts and software-based algorithms then populate a data timeline of case events from start to finish, retaining a handful of anonymized video clippings to supplement the review. These data also provide a consistent and reliable method to track specific quality metrics, such as time to trauma team assembly or time to blood product arrival. Furthermore, data can also be linked to patients' electronic medical records to explore relationships between initial trauma resuscitation and downstream patient-oriented outcomes. A video capture and data analysis system for the trauma bay overcomes the inherent deficiencies in the current standard for evaluating patient care in the trauma bay and offers exciting potential to enhance patient safety through a comprehensive data collection system.

Indexed as

quality improvementresuscitationsystems analysis

Identifiers

PMID32685694
PMCPMC7359065

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.