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Record W2793816908 · doi:10.1002/alr.22106

A challenge‐response endoscopic sinus surgery specific checklist as an add‐on to standard surgical checklist: an evaluation of potential safety and quality improvement issues

2018· article· en· W2793816908 on OpenAlexaff
Doron D. Sommer, Sadaf Arbab‐Tafti, Forough Farrokhyar, Marc A. Tewfik, Allan Vescan, Ian Witterick, Brian Rotenberg, Rakesh Chandra, Erik K Weitzel, Erin D. Wright, Jayant Ramakrishna

Bibliographic record

VenueInternational Forum of Allergy & Rhinology · 2018
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversity of AlbertaUniversity of TorontoMcGill UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsChecklistMedicinePatient safetyAuditObservational studyDelphi methodMedical emergencyHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of this study was to develop and evaluate the impact of an aviation-style challenge and response sinus surgery-specific checklist on potential safety and equipment issues during sinus surgery at a tertiary academic health center. The secondary goal was to assess the potential impact of use of the checklist on surgical times during, before, and after surgery. This initiative is designed to be utilized in conjunction with the "standard" World Health Organization (WHO) surgical checklist. Although endoscopic sinus surgery is generally considered a safe procedure, avoidable complications and potential safety concerns continue to occur. The WHO surgical checklist does not directly address certain surgery-specific issues, which may be of particular relevance for endoscopic sinus surgery. METHODS: This prospective observational pilot study monitored compliance with and compared the occurrence of safety and equipment issues before and after implementation of the checklist. Forty-seven consecutive endoscopic surgeries were audited; the first 8 without the checklist and the following 39 with the checklist. The checklist was compiled by evaluating the patient journey, utilizing the available literature, expert consensus, and finally reevaluation with audit type cases. The final checklist was developed with all relevant stakeholders involved in a Delphi method. RESULTS: Implementing this specific surgical checklist in 39 cases at our institution, allowed us to identify and rectify 35 separate instances of potentially unsafe, improper or inefficient preoperative setup. These incidents included issues with labeling of topical vasoconstrictor or injectable anesthetics (3, 7.7%) and availability, function and/or position of video monitors (2, 5.1%), endoscope (6, 15.4%), microdebrider (6, 15.4%), bipolar cautery (6, 15.4%), and suctions (12, 30.8%). CONCLUSION: The design and integration of this checklist for endoscopic sinus surgery, has helped improve efficiency and patient safety in the operating room setting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.120
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.066
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.120
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.370
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2018
Admission routes1
Has abstractyes

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