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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,

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Presentation on theme: "Predicting Daily Surgical Case Volume March 28, 2014 Association of Anesthesia Clinical Directors Nashville, TN Vikram Tiwari, Ph.D. William R Furman,"— Presentation transcript:

1 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

2 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) 2

3 Research Motivation MonthBudg.ActualDiff.% Diff. Aug-12292430511274.3% Sep-1224482489411.7% Oct-1228132912993.5% Nov-1226732694210.8% Dec-1225652605401.6% Jan-1328132833200.7% Feb-1324912558672.7% Mar-1326782601-77-2.9% Apr-1328372826-11-0.4% May-13275429151615.8% Jun-13268828021144.2% Jul-1328152884692.5% Aug-13287930191404.9% 3 Resources needed for DoS are planned usually weeks in advance Variability in daily surgical case volume sub- optimizes resources day

4 Daily surgical volume time-series 4

5 How to predict the daily volume? Elective case booking pattern – can that provide a signal? 5

6 Research Questions Working from the elective schedule as it develops over time, whether: 1.surgical case volume can be predicted, if so, 2.with what confidence 3.how many days in advance 4.and, if the predictions could be used to flex staff up or down 6

7 Linear trend of case bookings 7

8 Days-Out Model 8

9 Results / Model Output 9

10 Putting the output to use – Daily Case Report 10 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.

11 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 5 th, 2013 (Friday) – identified 4 weeks in advance that volume would be like a typical Friday, and no usual shortfall 11

12 Spring Break Week of March 17, 2014 12

13 How is the model’s output used? PurposeOrganization Supply & Processes 1.Case cart preparation center 2.Inpatient bed management Staffing 3.Anesthesiology Dept. 4.OR Managers 5.Surgical Pathology Labs 6.Case cart preparation center 13

14 Replication Children’s Hospital. Similar results. Let’s collaborate to replicate this! 14

15 Questions? 15

16 Backup An Empirical Approach to Predicting Case Volume from the Accumulating Elective Operating Room Schedule Facilitates Operationally Useful Staffing Improvements 16

17 Research Motivation 17

18 Model 2  Linear trend model – discarded Model 3  Percentage of final count – Model 4  Days-out model – 18 Methods: Linear models

19 Methods: predicting daily volume Model 1: time-series of daily surgical volume 19

20 Distribution of Case Bookings from 30 days prior to DoS 20

21 Model 3: Percentage of Final Count 21

22 22


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