Using Virtual Care to Facilitate Direct Hospital Admissions in Outpatients with Worsening COVID-19 Infection
Bibliographic record
Abstract
Recognizing emergency department overcrowding during the COVID-19 pandemic, a pathway to facilitate direct admissions for outpatients with worsening COVID-19 infection was created using the COVID-19 expansion to outpatients (COVIDEO) virtual care program. Outpatients appropriate for direct admission had oxygen saturations consistently <92% without severe respiratory distress. Pulse oximeters were proactively delivered to high-risk patients, and patients contacted the program in the event of worsening symptoms or desaturation persistently <92%. Over a 15-month period, 9,116 outpatients were managed by the program, 164 of whom were hospitalized, and 83 of those hospitalized (50.6%) were directly admitted through this pathway. Of those directly admitted, 10 (12.0%) patients required ICU admission, occurring a median of 4 days from hospital admission. The mortality rate among directly admitted patients was 3.6% (3/83). Implementation of a virtual care program to facilitate direct admissions in outpatients with COVID-19 created a safe, efficient, and patient-centered pathway of care.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".