Picking the Right Tool for the Job: A Reliability Study of 4 Assessment Tools for Central Venous Catheter Insertion
Bibliographic record
Abstract
BACKGROUND: Determining procedural competence requires psychometrically sound assessment tools. A variety of instruments are available to determine procedural performance for central venous catheter (CVC) insertion, but it is not clear which ones should be used in the context of competency-based medical education. OBJECTIVE: We compared several commonly used instruments to determine which should be preferentially used to assess competence in CVC insertion. METHODS: Junior residents completing their first intensive care unit rotation between July 31, 2006, and March 9, 2007, were video-recorded performing CVC insertion on task trainer mannequins. Between June 1, 2016, and September 30, 2016, 3 experienced raters judged procedural competence on the historical video recordings of resident performance using 4 separate tools, including an itemized checklist, Objective Structured Assessment of Technical Skills (OSATS), a critical error assessment tool, and the Ottawa Surgical Competency Operating Room Evaluation (O-SCORE). Generalizability theory (G-theory) was used to compare the performance characteristics among the tools. A decision study predicted the optimal testing environment using the tools. RESULTS: At the time of the original recording, 127 residents rotated through intensive care units at the University of Calgary, Alberta, Canada. Seventy-seven of them (61%) met inclusion criteria, and 55 of those residents (71%) agreed to participate. Results from the generalizability study (G-study) demonstrated that scores from O-SCORE and OSATS were the most dependable. Dependability could be maintained for O-SCORE and OSATS with 2 raters. CONCLUSIONS: Our results suggest that global rating scales, such as the OSATS or the O-SCORE tools, should be preferentially utilized for assessment of competence in CVC insertion.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".