Application of Information Link Control in Surgical Specimen Near-Miss Events in a South China Hospital: Nonrandomized Controlled Study
Bibliographic record
Abstract
Background: Information control is a promising approach for managing surgical specimens. However, there is limited research evidence on surgical near misses. This is particularly true in the closed loop of information control for each link. Objective: A new model of surgical specimen process management is further constructed, and a safe operating room nursing practice environment is created by intercepting specimen near-miss events through information safety barriers. Methods: In a large hospital in China, 84,289 surgical specimens collected in the conventional information specimen management mode from January to December 2021 were selected as the control group, and 99,998 surgical specimens collected in the information safety barrier control surgical specimen management mode from January to December 2022 were selected as the improvement group. The incidence of near misses, the qualified rate of pathological specimen fixation, and the average time required for specimen fixation were compared under the 2 management modes. The causes of 2 groups of near misses were analyzed and the near misses of information safety barrier control surgical specimens were studied. Results: Under the information-based safety barrier control surgical specimen management model, the incidence of adverse events in surgical specimens was reduced, the reporting of near-miss events in surgical specimens was improved by 100%, the quality control quality management of surgical specimens was effectively improved, the pass rate of surgical pathology specimen fixation was improved, and the meantime for surgical specimen fixation was shortened, with differences considered statistically significant at P<.05. Conclusions: Our research has developed a new mode of managing the surgical specimen process. This mode can prevent errors in approaching specimens by implementing information security barriers, thereby enhancing the quality of specimen management, ensuring the safety of medical procedures, and improving the quality of hospital services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".