Toward Feasible, Valid, and Reliable Video-Based Assessments of Technical Surgical Skills in the Operating Room
Bibliographic record
Abstract
OBJECTIVE: To determine the feasibility, validity, inter-rater, and intertest reliability of 4 previously published video-based rating scales, for technical skills assessment on a benchmark laparoscopic procedure. SUMMARY BACKGROUND DATA: Assessment of technical skills is crucial to the demonstration and maintenance of competent healthcare practitioners. Traditional assessment methods are prone to subjectivity through a lack of proven validity and reliability. METHODS: Nineteen surgeons (6 novice and 13 experienced) performed a median of 2 laparoscopic cholecystectomies each (range 1-5) on 53 patients within 2 Academic Surgical Departments. All patients had a diagnosis of biliary colic. Surgical technical skills were rated posthoc in a blinded manner by 2 experienced observers on 4 video-based rating scales. The different scales used had been developed to assess generic or procedure-specific technical skills in a global manner, or on a procedure-specific checklist. RESULTS: Six of 53 procedures were excluded on the basis of intraoperative difficulty. Of the remaining 47 procedures, 14 were performed by 6 novice surgeons and 33 by the 13 experienced surgeons. There were statistically significant differences between performance of the 2 groups on the generic global rating scale (median 24 vs. 27, P = 0.031), though not on procedural or checklist-based scales. All scales demonstrated inter-rater reliability (alpha = 0.58-0.76), though only the global rating scales exhibited intertest reliability (alpha = 0.72). CONCLUSIONS: Video-based technical skills evaluation in the operating room is feasible, valid and reliable. Global rating scales hold promise for summative assessment, though further work is necessary to elucidate the value of procedural rating scales.
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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 | 0.038 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".