Evaluation of standardized doctor's orders as an educational tool for undergraduate medical students: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Standardized doctor's orders are replacing traditional order writing in teaching hospitals. The impact of this shift in practice on medical education is unknown. It is possible that preprinted orders interfere with knowledge acquisition and retention by not requiring active decision-making. The objective of the study was to evaluate the impact of standardized admission orders on disease-specific knowledge among undergraduate medical trainees. METHODS: This prospective cohort study enrolled Year 3 (n = 121) and Year 4 (n = 54) medical students at two academic hospitals in Toronto (Ontario, Canada) during their general internal medicine rotation. We used standardized orders for patient admissions for alcohol withdrawal (AW) and for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) as the intervention and manual order writing as the control. Educational outcomes were assessed through end-of-rotation questionnaires assessing disease-specific knowledge of AW and AECOPD. RESULTS AND DISCUSSIONS: Of 175 students, 105 had exposure to patients with alcohol withdrawal during their rotation, and 68 students wrote admission orders. Among these 68 students, 48 used standardized orders (intervention, n = 48) and 20 used manual order writing (control, n = 20). Only 3 students used standardized orders for AECOPD, precluding analysis. There was no significant difference found in mean total score of questionnaires between those who used AW standardized orders and those who did not (11.8 vs. 11.0, p = 0.4). Students who had direct clinical experience had significantly higher mean total scores (11.6 vs. 9.0, p < 0.0001 for AW; 13.8 vs. 12.6, p = 0.02 for AECOPD) compared to students who did not. When corrected for overall knowledge, this difference only persisted for AW. CONCLUSIONS: No significant differences were found in total scores between students who used standardized admission orders and traditional manual order writing. Clinical exposure was associated with increase in disease-specific knowledge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.389 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.008 | 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".