Financial cost of elective day of surgery cancellations
Bibliographic record
Abstract
Operative care is one of the major areas of healthcare services as over 310 million surgeries are conducted yearly. Surgery cancellations is a widely used indicator when evaluating the quality of preoperative care. Cancellations cause financial lost for organizations, however there is only limited research about the costs. The aim of this study was to evaluate the cost of elective day of surgery (DOS) cancellations in 13 operative specialties at a university hospital in Finland between September 1, 2015 and May 31, 2016 after a structured preoperative protocol was implemented to practice and a cancellation rate of 4.7% was recognized. Procedure prices conducted the data for the research and were collected from the hospital’s invoicing system. Financial loss and savings of cancellations were calculated from the total cost of procedures. As a result the total cost of DOS cancellations during the nine-month time period was 953,374.27 euros and mean loss of a single cancelled operation was 2,459.91 euros. The total of material savings for the hospital were 106,917.33 euros. As a conclusion, DOS cancellations cause unnecessary wastage, and financial aspects should be followed and evaluated systematically by setting goals and providing continuing developments.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".