Ambulatory Surgery Ensemble: Predicting Adult and Pediatric Same-Day Surgery Cases Across Specialties
An ensemble model can predict CL, LOS, and DD for elective cases across multiple services and locations at the time of case posting. While limited in its inclusion of patient factors, this model can systematically facilitate clinical operations such as strategic planning, surgical block time, and case scheduling.
Authors
- Peter J. Allen (ORCID: https://orcid.org/0000-0001-7912-9197)
- Daniel M. Buckland (ORCID: https://orcid.org/0000-0001-5274-3840)
- Thomas Clark Howell (ORCID: https://orcid.org/0000-0002-7916-1952)
- Allan D. Kirk (ORCID: https://orcid.org/0000-0003-2004-5962)
- Hamed Zaribafzadeh (ORCID: https://orcid.org/0000-0002-0363-395X)
- Bruce Rogers (ORCID: https://orcid.org/0000-0001-8458-4709)
- Maxwell D. Sumner (ORCID: https://orcid.org/0000-0002-3590-5112)
- Michael Kent (ORCID: https://orcid.org/0000-0002-9051-2645)
- Ursula Rogers (ORCID: https://orcid.org/0000-0002-2838-3918)
- John C. Rollman
Institutions
- Duke University (US)
- Duke Medical Center (US)
Publication Details
- Journal
- Annals of Surgery Open
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1097/as9.0000000000000534
- Citations
- 3
- Primary Topic
- Hospital Admissions and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.07