Assessment of Electronic Health Record Usability with Undergraduate Nursing Students
Bibliographic record
Abstract
Health information technology (HIT), and specifically electronic health records (EHR), are recognized as fundamental tools for collecting, storing, retrieving, and monitoring patient care and information. However, few schools of nursing have incorporated theoretical or practical aspects of HIT competencies within the educational curriculum. The purpose of this study was to conduct a usability assessment to explore undergraduate nursing student electronic health record documentation knowledge and skill, using a patient case scenario to inform the development of an informatics-based undergraduate nursing curriculum. Three themes were identified: "Being a Novice User/Practitioner," "Confidentiality and Security," and "Repetition and Practice." Integration of the EHR into nursing curriculum will allow students an EHR apprenticeship with the potential to enhance understanding and skill of nursing processes, documentation, and critical thinking. Findings will also guide teaching and learning strategies that will respond to rising expectations for competency with health information technology.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".