Implementation of an Innovative Postoperative Monitoring Approach for Patients with Obstructive Sleep Apnea
Bibliographic record
Abstract
This article shares how William Osler Health System (Osler) achieved improved quality of care for clinically challenging patients using state-of-the-art technology combined with interprofessional and intermanagerial teamwork in an acute care setting. Obstructive sleep apnea, a respiratory disorder caused by upper airway obstruction, increases the risk of complications after anesthesia. Although an initial postoperative monitoring strategy designed for patients with obstructive sleep apnea at Osler ensured patient safety, it required reorganization to resolve operational challenges. Concerned stakeholders at all levels contributed to the development and implementation of a new program approach focused on remote pulse oximetry monitoring as a component of the standard of care. Osler has developed a case study to share its experience with other hospitals and health systems that are already engaged in or that are considering implementing such a 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".