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Predicting Daily Surgical Case Volume. March 28, 2014 Association of Anesthesia Clinical Directors Nashville, TN Vikram Tiwari, Ph.D . William R Furman, MD Warren S Sandberg, MD, Ph.D. Department of Anesthesiology, Vanderbilt University Nashville, Tennessee.

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predicting daily surgical case volume

Predicting Daily Surgical Case Volume

March 28, 2014

Association of Anesthesia Clinical Directors

Nashville, TN

Vikram Tiwari, Ph.D.

William R Furman, MD

Warren S Sandberg, MD, Ph.D.

Department of Anesthesiology, Vanderbilt University

Nashville, Tennessee

slide2

Predicting Case Volume from the Accumulating Elective Operating Room Schedule Facilitates Staffing Improvements

Vikram Tiwari, Ph.D., William R. Furman, M.D., and Warren S. Sandberg, M.D., Ph.D.

(Accepted for publication: Anesthesiology)

research motivation
Research Motivation
  • Resources needed for DoS are planned usually weeks in advance
  • Variability in daily surgical case volume sub-optimizes resources day
how to predict the daily volume
How to predict the daily volume?
  • Elective case booking pattern – can that provide a signal?
research questions
Research Questions

Working from the elective schedule as it develops over time, whether:

  • surgical case volume can be predicted, if so,
  • with what confidence
  • how many days in advance
  • and, if the predictions could be used to flex staff up or down
putting the output to use daily case report
Putting the output to use – Daily Case Report

For the first 15 days of July (excluding weekends), the model’s predictions (at TMinus5) were within +/- 7 cases of the final volume 80% of the time, whereas the budgeted volume was within +/- 7 cases 40% of the time.

early wins
Early wins!
  • May – 2013
    • identified volume shortfall 12 days in advance, arising due to all surgeons of a service attending a conference, without prior knowledge of the OR managers
  • July 5th, 2013 (Friday)
    • identified 4 weeks in advance that volume would be like a typical Friday, and no usual shortfall
replication
Replication
  • Children’s Hospital. Similar results.
  • Let’s collaborate to replicate this!
backup
Backup
  • An Empirical Approach to Predicting Case Volume from the Accumulating Elective Operating Room Schedule Facilitates Operationally Useful Staffing Improvements
methods linear models
Methods: Linear models
  • Model 2  Linear trend model
    • discarded
  • Model 3  Percentage of final count
    • <brief description / figure 4?>
  • Model 4  Days-out model
    • <description, keep Figure 6 in backup>
methods predicting daily volume
Methods: predicting daily volume
  • Model 1: time-series of daily surgical volume