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Record W3178640078 · doi:10.7759/cureus.16218

Utilizing the Operating Room Black Box to Characterize Intraoperative Delays, Distractions, and Threats in the Gynecology Operating Room: A Pilot Study

2021· article· en· W3178640078 on OpenAlexaffabout
Alysha Nensi, Vanessa N. Palter, Cheyanne Reed, Pansy Schulthess, Teodor Grantcharov, Eliane M. Shore

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineInterquartile rangePatient safetyTeamworkTechnicianHealth careMedical emergencySurgery

Abstract

fetched live from OpenAlex

Introduction Operating Room Black Box (ORBB) technology can be used to capture information during surgery for analysis and potential identification of root causes that jeopardize safety and efficiency. In this study, our objective was to identify and characterize procedural steps, intraoperative distractions, errors, and threats, as well as the non-technical skills of the team during a common minimally invasive gynecologic procedure. Methodology This was a cross-sectional pilot study of 25 patients undergoing total laparoscopic hysterectomy between May 2019 and February 2020 at a Canadian tertiary care academic hospital. Video, audio, and patient physiologic data from all procedures were obtained through a multichannel synchronized recording device (ORBB). Trained analysts reviewed and coded the recordings. Results The median total case time was 165 minutes (interquartile range [IQR]: 160-178 minutes) with the shortest step being cystoscopy and the longest being vaginal cuff closure. Time pressure and device absence or malfunction occurred in 48% of the cases, and a median of 262 (IQR: 228-304) auditory distractions were noted per case. There was a median of 3 (IQR: 2-4) safety threats identified per case and at least one error was identified in 11/25 cases (44%). Only two adverse events were noted among all 25 cases. Observed non-technical skills were mainly positive, and observations were the highest for situational awareness and leadership among the surgical team and communication and teamwork among the nursing/scrub technician and anesthesia teams. Conclusions This study is a novel application of the ORBB in the gynecology operating room to capture information regarding procedure times, intraoperative distractions, errors, and non-technical skills of the team. Frequent intraoperative cognitive and auditory distractions were noted. Although adverse events were rare, safety threats were identified. Ongoing and future research from our group will aim to identify key areas for organizational, technological, and team improvement to minimize inefficiencies and optimize patient safety in the operating room.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.329
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2021
Admission routes2
Has abstractyes

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