Medical Student Use of Electronic and Paper Health Records During Inpatient Clinical Clerkships: Results of a National Longitudinal Study
Bibliographic record
Abstract
PURPOSE: An important goal of medical education is to teach students to use an electronic health record (EHR) safely and effectively. The purpose of this study is to examine medical student accounts of EHR use during their core inpatient clinical clerkships using a national sample. Paper health records (PHRs) are similarly examined. METHOD: An online survey about health record use within the inpatient component of six core clerkships was administered to medical students after they completed Step 2 Clinical Knowledge of the United States Medical Licensing Examination. The sample included 17,202 U.S. medical students graduating between 2012 and 2016. Mean percentages of clerkships in which students engaged in various health record activities were computed, and analysis of variance was used to examine differences. RESULTS: The mean percentages of clerkships in which a student accessed or entered information into an EHR increased from 78% to 93% and 59% to 72%, respectively. For students who used an EHR, the mean percentage of clerkships in which they entered information remained constant at 76%. Students entered notes during the majority of their clerkships, with increases over time. However, students entered orders in less than a quarter of their clerkships, with decreases over time. The percentage of clerkships in which students used PHRs was lower and declining. CONCLUSIONS: Although students used an EHR in the majority of their inpatient core clerkships, they received limited educational experiences related to order and note writing, which could translate into a lack of preparedness for future training and practice.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".