Absence of July Phenomenon in Acute Ischemic Stroke Care Quality and Outcomes
Bibliographic record
Abstract
Background Lower care quality and an increase in adverse outcomes as a result of new medical trainees is a concept well rooted in popular belief, termed the “July phenomenon.” Whether this phenomenon occurs in acute ischemic stroke has not been well studied. Methods and Results We analyzed data from patients admitted with ischemic stroke in 1625 hospitals participating in the Get With The Guidelines–Stroke program for the 5‐year period between January 2009 and December 2013. We compared acute stroke treatment processes and in‐hospitals outcomes among the 4 quarters (first quarter: July–September, last quarter: April–June) of the academic year. Multivariable logistic regression models were used to evaluate the relationship between academic year transition and processes measures. A total of 967 891 patients were included in the study. There was a statistically significant, but modest (<4 minutes or 5 percentage points) difference in distribution of or quality and clinical metrics including door‐to‐computerized tomography time, door‐to‐needle time, the proportion of patients with symptomatic intracranial hemorrhage within 36 hours of admission, and the proportion of patients who received defect‐free care in stroke performance measures among academic year quarters ( P <0.0001). In multivariable analyses, there was no evidence that quarter 1 of the academic year was associated with lower quality of care or worse in‐hospital outcomes in teaching and nonteaching hospitals. Conclusions We found no evidence of the “July phenomenon” in patients with acute ischemic stroke among hospitals participating in the Get With The Guidelines–Stroke program.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".