Cargando…
Machine Learning Prediction Models to Reduce Length of Stay at Ambulatory Surgery Centers Through Case Resequencing
The post-anesthesia care unit (PACU) length of stay is an important perioperative efficiency metric. The aim of this study was to develop machine learning models to predict ambulatory surgery patients at risk for prolonged PACU length of stay - using only pre-operatively identified factors - and the...
Autores principales: | Tully, Jeffrey L., Zhong, William, Simpson, Sierra, Curran, Brian P., Macias, Alvaro A., Waterman, Ruth S., Gabriel, Rodney A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10333394/ https://www.ncbi.nlm.nih.gov/pubmed/37428267 http://dx.doi.org/10.1007/s10916-023-01966-9 |
Ejemplares similares
-
Machine Learning-Based Models Predicting Outpatient Surgery End Time and Recovery Room Discharge at an Ambulatory Surgery Center
por: Gabriel, Rodney A., et al.
Publicado: (2022) -
A Retrospective Analysis Investigating Whether Case Volume Experience of the Anesthesiologist Correlates with Intraoperative Efficiency for Joint Arthroplasty
por: Macias, Alvaro A., et al.
Publicado: (2023) -
An Ensemble Learning Approach to Improving Prediction of Case Duration for Spine Surgery: Algorithm Development and Validation
por: Gabriel, Rodney Allanigue, et al.
Publicado: (2023) -
Reducing emergency admissions and length of stay by introducing emergency surgical ambulatory service
por: Kazem, M.A., et al.
Publicado: (2019) -
Critical length in long-read resequencing
por: De Coster, Wouter, et al.
Publicado: (2020)