An exact, order-statistic approach to predicting Phase I recovery closing time in an ambulatory surgery center to provide advance notification to anesthesiologists
Authors' conclusion
A rolling, distribution-free prediction method based on exact order statistics provides stable and interpretable estimates of when the Phase I recovery is likely to close and the last anesthesiologist can leave for the day.
Study context
- Population
- Daily times at which the final patient left Phase I recovery at an ambulatory surgery center over a multi-year period
- Exposure
- Rolling window sizes for exact percentile-based prediction limits
- Outcome
- Accuracy (observed exceedance rate) and stability (coefficient of variation) of exact percentile prediction limits of Phase I recovery closing time
Methodological detailssingle ambulatory surgery center, rolling historical windows, distribution-free (exact order statistic) prediction limits, Example application to a single-specialty orthopedic hospital
- Single ambulatory surgery center
- Rolling historical windows
- Distribution-free (exact order statistic) prediction limits
- Example application to a single-specialty orthopedic hospital
Main finding
As reported in the abstract
80th-percentile prediction limit across window sizes
- Accuracy similar across window sizes (5 to 100 days); observed exceedance rates close to nominal 20% level
- Coefficient of variation decreased with increasing window size, little additional reduction beyond 60 workdays
- 60-workday window gave stable 80th-percentile prediction limits while preserving expected exceedance rate
Observational data: associations, not effects.
Further findings
Synthetic log-normal dataset
- Comparable accuracy and variability behavior across window sizes
Original publication
An exact, order-statistic approach to predicting Phase I recovery closing time in an ambulatory surgery center to provide advance notification to anesthesiologists. J Clin Anesth. Published 7 August 2026. doi:10.
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