Use of a National Continuing Medical Education Meeting to Provide Simulation-Based Training in Temporary Hemodialysis Catheter Insertion Skills: A Pre-Test Post-Test Study
Bibliographic record
Abstract
BACKGROUND: Simulation-based-mastery-learning (SBML) is an effective method to train nephrology fellows to competently insert temporary, non-tunneled hemodialysis catheters (NTHCs). Previous studies of SBML for NTHC-insertion have been conducted at a local level. OBJECTIVES: Determine if SBML for NTHC-insertion can be effective when provided at a national continuing medical education (CME) meeting. Describe the correlation of demographic factors, prior experience with NTHC-insertion and procedural self-confidence with simulated performance of the procedure. DESIGN: Pre-test - post-test study. SETTING: 2014 Canadian Society of Nephrology annual meeting. PARTICIPANTS: Nephrology fellows, internal medicine residents and medical students. MEASUREMENTS: Participants were surveyed regarding demographics, prior NTHC-insertion experience, procedural self-confidence and attitudes regarding the training they received. NTHC-insertion skills were assessed using a 28-item checklist. METHODS: Participants underwent a pre-test of their NTHC-insertion skills at the internal jugular site using a realistic patient simulator and ultrasound machine. Participants then had a training session that included a didactic presentation and 2 hours of deliberate practice using the simulator. On the following day, trainees completed a post-test of their NTHC-insertion skills. All participants were required to meet or exceed a minimum passing score (MPS) previously set at 79%. Trainees who did not reach the MPS were required to perform more deliberate practice until the MPS was achieved. RESULTS: Twenty-two individuals participated in SBML training. None met or exceeded the MPS at baseline with a median checklist score of 20 (IQR, 7.25 to 21). Seventeen of 22 participants (77%) completed post-testing and improved their scores to a median of 27 (IQR, 26 to 28; p < 0.001). All met or exceeded the MPS on their first attempt. There were no significant correlations between demographics, prior experience or procedural self-confidence with pre-test performance. LIMITATIONS: Small sample-size and self-selection of participants. Costs could limit the long-term feasibility of providing this type of training at a CME conference. CONCLUSIONS: Despite most participants reporting having previously inserted NTHCs in clinical practice, none met the MPS at baseline; this suggests their prior training may have been inadequate.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".