Evidence map›Paper›PMID 31629782›Full record

ReviewSeminars in thoracic and cardiovascular surgery

Cognitive Engineering to Improve Patient Safety and Outcomes in Cardiothoracic Surgery.

Marco A Zenati, Lauren Kennedy-Metz, Roger D Dias

Abstract readReview
In one paragraph

Review in Seminars in thoracic and cardiovascular surgery. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Exploring Intraoperative Cognitive Biases in Cardiac Surgery Teams.Applied Human Factors and Ergonomics Conference · 2024
    Article
  5. Situational Awareness in the Context of Clinical Practice.Healthcare (Basel, Switzerland) · 2023
    Review
  6. Article
  7. Using Digital Biomarkers for Objective Assessment of Perfusionists' Workload and Acute Stress During Cardiac Surgery.Bioinformatics and Biomedical Engineering : 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12-14, 2023, Proceedings. Part I. IWBBIO (Conference) (10th : 2023 : Gran Canaria, Canary Islands) · 2023
    Article
  8. Article
  9. Assessing Team Situational Awareness in the Operating Room via Computer Vision.IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) · 2022
    Article
  10. Importance of high-performing teams in the cardiovascular intensive care unit.The Journal of thoracic and cardiovascular surgery · 2022
    Article
  11. Commentary: Culture trumps (transfusion) guidelines.The Journal of thoracic and cardiovascular surgery · 2022
    Article
  12. Review
  13. Using machine learning to predict perfusionists' critical decision-making during cardiac surgery.Computer methods in biomechanics and biomedical engineering. Imaging & visualization · 2022
    Article
  14. Article
  15. The Cognitive Relevance of a Formal Pre-incision Time-out in Surgery.ECCE ... : proceedings of the ... European Conference on Cognitive Ergonomics. European Conference on Cognitive Ergonomics · 2021
    Article
  16. Computer Vision in the Operating Room: Opportunities and Caveats.IEEE transactions on medical robotics and bionics · 2021
    Article
  17. Article
  18. Review
  19. Autonomic Activity and Surgical Flow Disruptions in Healthcare Providers during Cardiac Surgery.IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) · 2020
    Article
  20. Digital Cognitive Aids to Support Adaptation of Surgical Processes to COVID-19 Protective Policies.IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) · 2020
    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

3 authors.

Marco A ZenatiDivision of Cardiac Surgery, Veterans Affairs Boston Healthcare System, Boston, Massachusetts; Medical Robotics & Computer-Assisted Surgery MRCAS) Laboratory, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Department of Surgery, Brigham & Women's Hospital, Boston, Massachusetts. Electronic address: Marco_Zenati@hms.harvard.edu.
Lauren Kennedy-MetzDivision of Cardiac Surgery, Veterans Affairs Boston Healthcare System, Boston, Massachusetts; Medical Robotics & Computer-Assisted Surgery MRCAS) Laboratory, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts; Department of Surgery, Brigham & Women's Hospital, Boston, Massachusetts.
Roger D DiasHarvard Medical School, Boston, Massachusetts; Department of Emergency Medicine, STRATUS Center for Medical Simulation, Brigham & Women's Hospital, Boston, Massachusetts.

Funding

Developing Standardized Intraoperative Process Models to Enhance Surgical SafetyR01HL126896 · NHLBI · HARVARD MEDICAL SCHOOL · PI ZENATI, MARCO A. · 2016 to 2023
$3.7M
NHLBI NIH HHS R01 HL126896
6 · The paper itself

Abstract

Cognitive engineering is focused on how humans can cope and master the complexity of processes and technological environments. In cardiothoracic surgery, the goal is to support safe and effective human performance by preventing medical errors. Strategies derived from cognitive engineering research could be introduced in cardiothoracic surgery practice in the near future to enhance patient safety and outcomes.

Indexed as

Attitude of Health PersonnelClinical CompetenceCognitionCognitive ScienceErgonomicsHealth Knowledge, Attitudes, PracticeThoracic Surgical ProceduresCardiac Surgical ProceduresHumansMedical ErrorsMentalizationPatient Care TeamPatient SafetyPostoperative ComplicationsRisk AssessmentRisk FactorsCognitive engineeringHuman factorsMedical errorsMental workloadNeuroergonomicsPatient safetySurgical data science

Identifiers

PMID31629782
PMCPMC7060831

What OpenQuestion holds

Textmetadata
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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.