Day surgery in a teaching hospital: identifying barriers to productivity
Bibliographic record
Abstract
Introduction: Ambulatory surgery is a standard of care for many surgical procedures due to cost-effectiveness and benefits to patients including the reduced risk of contracting hospital infection by reducing the hospital stay. However, late cancellations can be costly. We examined the utilisation of the surgical day ward in our institution over a four-year period. Methods: A retrospective study of surgical day ward records from September 2007 to September 2011 in one institution. Parameters investigated included the number of planned admissions. Reasons for cancellations were also collected. Results: A total of 17,461 procedures were intended as a day ward admission during the study interval. There were 3,539 procedures that were cancelled (20.3%). The prevalent proportion of cancellations (n = 1,367) (38.6%) were due to patients not showing up for their procedures (7.8% of planned admissions); 1,188 (33.6%) patients were cancelled by the admissions office due to bed shortages, accounting for 6.8 % of planned admissions and 650 (18.4%) of cases were due to last minute cancellations by patients, accounting for 3.7% of all planned admission. The remaining 334 (9.4%) of cases were cancelled on medical grounds including patients who were considered unfit for the intended procedure, or anti-coagulations not appropriately ceased prior to surgery, accounting for 1.9% of all planned admissions. Conclusion: The cancellation rate in this study was high, mainly due to failure of patients to attend or signal their intentions, inadequate bed capacity and bed closure strategies. The ring fencing and protection of day beds and a more active patient management interaction would have had the greatest impact on increased efficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".