Literature DB >> 16632832

Predicting anesthesia times for diagnostic and interventional radiological procedures.

Franklin Dexter1, Jack C Yue, Angella J Dow.   

Abstract

We studied anesthesia times for diagnostic and interventional radiology using anesthesia billing data and paper radiology logbooks. For computerized tomography and magnetic resonance imaging procedures, we tried to predict future anesthesia times by using historical anesthesia times classified by Current Procedural Terminology (CPT) codes. By this method, anesthesia times were estimated even less accurately than operating room cases. Computerized tomography and magnetic resonance imaging had many different CPT codes, most rare, and CPT codes reflected organs imaged, not scanning times. However, when, anesthesia times were estimated by expert judgment, face validity and accuracy were good. Lower and upper prediction bounds were also estimated from the expert estimates. For interventional radiology, predicting anesthesia times was challenging because few CPT codes accounted for most cases. Because interventional radiologists scheduled their elective cases into allocated time, the necessary goal was not to estimate the time to complete each case but rather the time to complete each day's entire series of elective cases including turnover times. We determined the time of day (e.g., 4 pm) up to when interventional radiology could schedule so that on 80% of days the anesthesia team finishes no later than a specified time (e.g., 6 pm). Both diagnostic and interventional radiology results were similarly less accurate when Version 9 of the International Classifications of Diseases' procedure codes was used instead of CPT.

Mesh:

Year:  2006        PMID: 16632832     DOI: 10.1213/01.ane.0000202397.90361.1b

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  3 in total

1.  Analysis to Establish Differences in Efficiency Metrics Between Operating Room and Non-Operating Room Anesthesia Cases.

Authors:  Albert Wu; Joseph A Sanford; Mitchell H Tsai; Stephen E O'Donnell; Billy K Tran; Richard D Urman
Journal:  J Med Syst       Date:  2017-07-07       Impact factor: 4.460

2.  Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

Authors:  Eric R Edelman; Sander M J van Kuijk; Ankie E W Hamaekers; Marcel J M de Korte; Godefridus G van Merode; Wolfgang F F A Buhre
Journal:  Front Med (Lausanne)       Date:  2017-06-19

3.  Strategies for daily operating room management of ambulatory surgery centers following resolution of the acute phase of the COVID-19 pandemic.

Authors:  Franklin Dexter; Mohamed Elhakim; Randy W Loftus; Melinda S Seering; Richard H Epstein
Journal:  J Clin Anesth       Date:  2020-04-29       Impact factor: 9.452

  3 in total

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