Preadmission processes may improve length of stay for colorectal surgery
Bibliographic record
Abstract
BACKGROUND: The preadmission process (PAP) is known to reduce length of stay prior to surgery, but there are few data on its effects on postoperative stay. The aim of the present study was to test the hypothesis that a PAP may reduce postoperative length of stay as well as the preoperative length of stay. METHODS: An audit of admission and discharge times for patients having major colorectal surgery was undertaken to determine the impact of the preadmission process at Dandenong Hospital. One hundred and two elective patients were identified over a 12-month period. RESULTS: The 71 patients admitted through the preadmission process had a 10.7-day average length of stay compared to 18.4 days if the patients were admitted directly by the surgeon. The reduction in length of stay was contributed to by 4 days less preoperatively and 4 days less postoperatively. Thus the benefits from a preadmission service can be realized both at admission and discharge. The nature of this impact of preadmission requires further investigation. CONCLUSIONS: The PAP will reduce preoperative length of stay. Utilization of a PAP also appears to reduce postoperative length of stay and may reduce postoperative complications. Further investigation is required to determine the exact nature and extent of these PAP benefits.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".