The incidence of adverse events among home care patients
Bibliographic record
Abstract
OBJECTIVE: Incidence of adverse events (AEs) among home care patients and preventability ratings were estimated. Risk factors, AE types and factors associated with AEs were identified. DESIGN: This study used a stratified, randomized sample of home care patients discharged in the fiscal year 2004/05. Trained nurse reviewers completed retrospective chart abstractions; charts for cases that were positive for screening criteria suggesting the presence of AEs were reviewed by trained physicians to determine the presence of and preventability of AEs. SETTING: Three publicly funded home care programs in Ontario, Canada. MAIN OUTCOME MEASURES: Prevalence and types of AEs; ratings of preventability. RESULTS: At least one screening criterion was positively identified in 286 (66.5%) of 430 cases. Physician reviewers identified 61 AEs in 55 (19.2%) of the 286 (12.8% of the 430) cases. The AE rate was 13.2 per 100 home care cases [95% confidence interval (CI): 10.4-16.6%, standard error 1.6%]. 32.7% (20 of 61 AEs) of the AEs were rated as having >50% probability of preventability; 6 deaths (10.9% of patients with an AE; 1.4% of all patients) occurred in AE-positive patients. The most common AEs were falls and adverse drug events. CONCLUSIONS: Providing health care through home care programs creates unintended harm to patients. The incidence rate of AEs of 13.2% suggests a significant number of home care patients experience AEs, one-third of which were considered preventable. Improvements in patient and informal caregiver education, skill development and clinical planning may be useful interventions to reduce AEs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".