Incidence, severity and preventability of medication-related visits to the emergency department: a prospective study
Bibliographic record
Abstract
BACKGROUND: Medication-related visits to the emergency department are an important but poorly understood phenomenon. We sought to evaluate the frequency, severity and preventability of drug-related visits to the emergency department. METHODS: We performed a prospective observational study of randomly selected adults presenting to the emergency department over a 12-week period. Emergency department visits were identified as drug-related on the basis of assessment by a pharmacist research assistant and an emergency physician; discrepancies were adjudicated by 2 independent reviewers. RESULTS: Among the 1017 patients included in the study, the emergency department visit was identified as drug-related for 122 patients (12.0%, 95% confidence interval [CI] 10.1%-14.2%); of these, 83 visits (68.0%, 95% CI 59.0%-76.2%) were deemed preventable. Severity was classified as mild in 15.6% of the 122 cases, moderate in 74.6% and severe in 9.8%. The most common reasons for drug-related visits were adverse drug reactions (39.3%), nonadherence (27.9%) and use of the wrong or suboptimal drug (11.5%). The probability of admission was significantly higher among patients who had a drug-related visit than among those whose visit was not drug-related (OR 2.18, 95% CI 1.46-3.27, p < 0.001), and among those admitted, the median length of stay was longer (8.0 [interquartile range 23.5] v. 5.5 [interquartile range 10.0] days, p = 0.06). INTERPRETATION: More than 1 in 9 emergency department visits are due to drug-related adverse events, a potentially preventable problem in our health care system.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".