Accuracy of nurse documentation of delirium symptoms in medical charts
Bibliographic record
Abstract
The purpose of this study undertaken in an acute care hospital was to evaluate sensitivity and specificity of the documentation of nurse-reported delirium symptoms in medical charts. This is a descriptive study based on the clinical assessments of a study nurse and nursing notes in the medical charts of 226 delirious older patients newly admitted to an acute care hospital. The results of this prospective validation study indicated that documentation of delirium symptoms is poor. Disorientation, agitation and altered level of consciousness were the three symptoms yielding a higher level of sensitivity, but even so said symptoms were reported in less than a third of the medical charts. Univariate analysis suggested that higher comorbidity level, more severe symptoms of delirium and the use of physical restraints were associated with more valid documentation of delirium symptoms in medical charts. Lastly, this study corroborates results of previous studies, indicating that documentation of delirium symptoms in medical charts can be improved. Future study should target improving nurse documentation of delirium symptoms in medical charts.
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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 | 0.009 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".