Case duration prediction and estimating time remaining in ongoing cases

Franklin Dexter, Richard H. Epstein, Anil A. Marian

Research output: Contribution to journalEditorialpeer-review

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.

Original languageEnglish (US)
JournalBritish Journal of Anaesthesia
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Keywords

  • Bayesian methods
  • case duration
  • case scheduling
  • industrial engineering
  • machine learning
  • neural network
  • operating room management
  • operational research

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine

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