Mortality during hospitalisation for pneumonia in Alberta, Canada, is associated with physician volume
Bibliographic record
Abstract
The association of mortality with patient factors (severity of illness, comorbidity), physician factors (specialty training, prehospitalisation visit, in-hospital consultation, volume of patients seen per physician) and healthcare organisation factors (patient-travel distances, regional beds per capita, admitting hospital-bed occupancy, admitting hospital-bed turnover, hospital location, volume of pneumonia cases per hospital) after hospital admission with community-acquired pneumonia was investigated using administrative data from Alberta, Canada from April 1, 1994-March 31, 1999. During the 5-yr study period there were 43,642 pneumonia hospitalisations, with an 11% in-hospital and 26% 1-yr mortality. Patient severity of illness and comorbidity were the strongest predictors of increased mortality. Physicians with the highest in-hospital pneumonia patient volume (>27 patients x yr(-1)) cared for patients with greater severity/comorbidity, but with decreased odds of in-hospital mortality, compared with the lowest volume physicians (less than seven patients per year). The effects of internal medicine specialist or subspecialist care were mixed, with a reduction in deaths for the first 72 h and an increase in in-hospital deaths. Prehospitalisation visit by a physician was associated with decreased mortality. Healthcare organisation factors were the least strong predictor of mortality, demonstrating an effect only for 1-yr mortality in those discharged alive from hospital. Admissions to larger volume or metropolitan hospitals were associated with a decrease in mortality. Severity of illness and comorbidity had the strongest association with mortality. The first association of high-volume physician and pre-hospital care with decreased in-hospital mortality for community-acquired pneumonia is reported.
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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 | 0.000 |
| 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".