Drug‐Related Hospitalizations in a Tertiary Care Internal Medicine Service of a Canadian Hospital: A Prospective Study
Why this work is in the frame
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Bibliographic record
Abstract
STUDY OBJECTIVES: To determine the frequency, severity, preventability, and classification of adverse drug events resulting in hospitalization, and to identify any patient, prescriber, drug, and system factors associated with these events. DESIGN: Prospective, observational study. SETTING: Internal medicine service of a large tertiary care hospital in Canada. PATIENTS: A total of 565 consecutive adult patients admitted to the hospital during a 12-week period. MEASUREMENTS AND MAIN RESULTS: A patient's hospitalization was defined as drug related if it was directly related to one of eight predefined classifications; severity and preventability of the hospitalization were also assessed. Multivariate logistic regression analysis was used to evaluate patient, prescriber, drug, and system factors associated with drug-related hospitalizations. The frequency of drug-related hospitalization was 24.1% (95% confidence interval [CI] 20.6-27.8%), of which 72.1% (95% CI 63.7-79.4%) were deemed preventable. Severity was classified as mild, moderate, severe, and fatal in 8.1% (95% CI 4.1-14.0%), 83.8% (95% CI 76.5-89.6%), 7.4% (95% CI 3.6-13.1%), and 0.7% (95% CI 0.0-4.0%), respectively, of the hospitalizations. The most common classifications of drug-related hospitalization were adverse drug reactions (35.3% [95% CI 27.3-43.9%]), improper drug selection (17.6% [95% CI 11.6-25.1%]), and noncompliance (16.2% [95% CI 10.4-23.5%]). No independent risk factors for drug-related hospitalization were identified with regression modeling. CONCLUSION: Approximately 25% of patients in our study were hospitalized for drug-related causes; over 70% of these causes were deemed preventable. Drug-related hospitalization is a significant problem that merits further research and intervention.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it