Attitudes of Patients and Care Providers Toward a Surgical Site Marking Policy
Bibliographic record
Abstract
BACKGROUND: In the fall of 2005, the University Health Network in Toronto, Canada, initiated a policy requiring the surgeon-or his or her delegate-to sign the incision site for all operations. Little is known about what health care providers and patients think about official surgical site marking policy. METHOD: Twenty-one patients and health care providers were interviewed, and the authors conducted field observations of surgeons while they marked their patients. The data were analyzed using grounded theory methods. FINDINGS: Surgical site marking was perceived to be a safety precaution for operations involving multiple sides and structures but not for cases where there is no uncertainty about the intended operative site. Participants believed that marking could also facilitate error if the wrong side was marked. Site marking was perceived to have the effect of ensuring that the surgeon meets with the patient prior to the operation on the day of surgery. Concerns were raised with respect to who should mark patients and marking surgical sites for genital surgery or other private body sites. CONCLUSIONS: For operations that involve multiple possible surgical sites, site marking should be carried out by individuals who are knowledgeable about the patient and the proposed procedure. For operations in which there is no uncertainty about the intended site, interventions other than site marking could be implemented to ensure patient-surgeon interactions on the day of surgery. Surgical site marking procedures should respect patient dignity and privacy.
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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 | 0.018 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".