Quantitative Analysis of the Impact of Infectious Disease Physicians on Patients in the Emergency Department Fast-Track Parenteral Antibiotics Program
Bibliographic record
Abstract
Abstract Introduction: The outpatient parenteral antibiotic therapy (OPAT) program of Vancouver General Hospital (VGH) was supervised solely by emergency physicians (EPs) until 2017 when infectious disease (ID) physicians began assisting in management. We designed a retrospective study to determine whether ID involvement led to improved outcomes. Methods This study analyses the impact of this increased ID involvement by comparing the mean days patients spend on OPAT with ID involvement versus EPs alone through a retrospective chart review. Our secondary research objectives were to compare patient care decisions, e.g., antibiotic choice, tests ordered, and final diagnosis. Results When directly compared, there was no difference between the mean number of days on OPAT between physician types. Compared to historic patterns, patients seen in OPAT after increased ID consultation spent an average of 0.5 fewer days in the program. However, when grouped by the first day of ID assessment, the average total days in OPAT was closely aligned with the day of first ID assessment, implying that ID frequently discharged patients close to initial assessment. Patients seen by ID were less likely to return within one month of discharge compared to those not seen by ID. Secondary findings include ID physicians prescribing a greater range of antibiotics, providing more varied final diagnoses, prescribing antibiotics less frequently, and ordering more cultures, diagnostic imaging and specialist consults. Discussion The findings of this study support the hypothesis that ID involvement in OPAT programs leads to changes in care that may have beneficial outcomes for patients and the healthcare system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".