Editorial
Case duration prediction and estimating time remaining in ongoing cases
British journal of anaesthesia : BJA, Vol.128(5), pp.751-755
04/02/2022
DOI: 10.1016/j.bja.2022.02.002
PMID: 35382924
Abstract
In this issue of the British Journal of Anaesthesia, Jiao and colleagues applied a neural network model for surgical case durations to predict the operating room times remaining for ongoing anaesthetics. We review estimation of case durations before each case starts, showing why their scientific focus is useful. We also describe managerial epidemiology studies of historical data by the scheduled procedure or distinct combinations of scheduled procedures included in each surgical case. Most cases have few or no historical data for the scheduled procedures. Generalizability of observational results such as theirs, and automatic computer assisted clinical and managerial decision-making, are both facilitated by using structured vocabularies when analysing surgical procedures.
Details
- Title: Subtitle
- Case duration prediction and estimating time remaining in ongoing cases
- Creators
- Franklin Dexter - Department of Anesthesia, University of Iowa, Iowa City, IA, USARichard H Epstein - University of MiamiAnil A Marian - University of Iowa
- Resource Type
- Editorial
- Publication Details
- British journal of anaesthesia : BJA, Vol.128(5), pp.751-755
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.bja.2022.02.002
- PMID
- 35382924
- ISSN
- 0007-0912
- eISSN
- 1471-6771
- Language
- English
- Date published
- 04/02/2022
- Academic Unit
- Health Management and Policy; Anesthesia
- Record Identifier
- 9984240759302771
Metrics
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