The Influence of Hospitalist Continuity on the Likelihood of Patient Discharge in General Medicine Patients
Bibliographic record
Abstract
Hospitalists responsible for specific inpatients may change during their hospitalization. To measure the association of hospitalist continuity with the adjusted daily discharge probability, 6,405 admissions (38,967 patientdays, 5,208 patients) to a general medicine service at a tertiary care teaching hospital in 2015 were investigated. Continuity was measured as the consecutive number of days-including weekends-a hospitalist treated a particular team of patients. After accounting for important covariables, discharge probability increased significantly with hospitalist continuity; the adjusted daily discharge probabilities for an average patient with a new physician vs. one on service for 4 continuous weeks were 18.1% and 25.7%, respectively (P < .001). Hospitalist continuity did not influence hospital mortality. Increasing hospitalist continuity could decrease hospital length of stay.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".