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Record W2167636960 · doi:10.5489/cuaj.12020

Day of surgery cancellation rates in urology: Identification of modifiable factors

2012· article· en· W2167636960 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Urological Association Journal · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsIdentification (biology)UrologyMedicineGeneral surgeryBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Day-of-surgery cancellations have a negative effect on operating room (OR) resources, as well as on patient satisfaction and perception of quality of care. Given increasing wait times in a universal healthcare system and the nature of urological surgery in our aging population, it should be a priority to identify modifiable risks of OR cancellations to assure timely and efficient delivery of care. We explore the rate and reasons for elective surgery cancellations in a Canadian urological practice. METHODS: We evaluated the rate and reason of urological surgery cancellation at a single academic institution, prospectively collected in our centre's Operating Room Scheduling Office System (ORSOS) database. Documented reasons for cancellations were divided into 3 components: (1) structural factors (e.g., no hospital bed); (2) patient factors (e.g., patient unwell); and (3) process factors (e.g., scheduling error). Rates and reasons for cancellations were compared to those of General Surgery and Gynecology. The documented reasons for cancellation in the ORSOS database were confirmed or extended by chart review and interviews with a subset of cancelled patients. RESULTS: Between 2005 and 2009, 1544 out of 19 141 (8.07 %) elective surgical cases were cancelled within the three surgical specialties (general surgery, gynecology and urology); urology had the highest average rate of 9.53%. Non-oncological cases represented a higher percentage of cancelled cases (15%, p < 0.001) and overall rates varied significantly over time in urology compared to the other surgical specialties. Potentially modifiable, process-related causes were by far the most common reason for cancellation (58.5%) and "standby" cases were a common cause of overall cancellation rates. Patient interviews confirmed the emotional and financial impact of cancellation; there was no overwhelming concern that clinical outcomes were negatively affected. CONCLUSIONS: This contemporary exploration of cancelled urological cases is consistent with previous reports, although variable over time and dependent on definitions used. Potentially modifiable, process-related factors appear to be most frequently associated with cancellation, although more thorough and detailed documentation is required to further mitigate inefficient OR use. We suggest that all OR cancellations should be considered to be adverse incidents to be monitored by institutions in a systematic fashion.

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.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.006
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.364
Teacher spread0.278 · 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