Evaluation of a Web‐based Educational Program to Teach the Identification and Management of Alcohol Withdrawal in the Emergency Department
Bibliographic record
Abstract
BACKGROUND: Ideal management of alcohol withdrawal syndrome (AWS) incorporates a symptom-driven approach, where patients are regularly assessed using a standardized scoring system (Clinical Institute Withdrawal Assessment for Alcohol-Revised [CIWA-Ar]) and treated according to severity. Accurate administration of the CIWA-Ar requires experience, yet there is no training program to teach this competency. The objective of this study was to develop and evaluate a curriculum to teach clinicians how to accurately assess and treat AWS. METHODS: This was a three-phase education program consisting of a series of e-learning modules containing core competency material, an in-person seminar to orient learners to high-fidelity simulation, and a summative evaluation in an objective structured clinical examination setting using a standardized patient. To determine the impact of the AWS curriculum, we recorded how often the CIWA-Ar was appropriately applied in the emergency department (ED) before and after training. A CIWA-Ar protocol breach was defined as inappropriate administration of benzodiazepines (CIWA-Ar < 10) and failure to administer benzodiazepines when required (CIWA-Ar ≥ 10). ED length of stay, amount of benzodiazepines administered in the ED, discharge prescriptions, and unit doses (take-away bottle of four tablets) of benzodiazepine given were recorded. RESULTS: Seventy-four ED nurses completed the curriculum over an 8-week period. In the 5 months prior to the educational program delivery, we identified 144 of 565 (25.5%) CIWA-Ar protocol breaches, compared to 64 of 547 (11.7%) in the 5 months after training (∆13.8%, 95% confidence interval [CI] = 9.3%-18.3%). Program completion resulted in a reduction in the median total dose of diazepam administered in the ED (40 mg vs. 30 mg, ∆10 mg, 95% CI = 0-20 mg) and no change was detected in ED length of stay and benzodiazepines prescribed. CONCLUSIONS: Completion of this curriculum resulted in better compliance with the CIWA-Ar protocol by those who administer the CIWA-Ar; however, changes in inappropriate benzodiazepine prescribing practice will require future interdisciplinary initiatives.
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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 | 0.000 |
| 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".