Abstract
The planning of operations in the Academic Medical Center is primarily based on the assessments of the length of the operation by the surgeons. We investigate whether duration models employing the information available at the moment the planning is made, offer a better alternative. Our empirical results indicate that statistical methods often do better than surgeons. This does not imply that the surgeons’ predictions do not contain valuable information. This information is a key explanatory variable in our statistical models. What our conclusion does entail is that a correction of the predictions of surgeons is possible because they are often under- or overestimating the actual length of operations.
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References
Bago d’Uva T, Jones AM (2009) Health care utilization in Europe: new evidence from the ECHP. J Health Econ 28: 265–279
Benchmarking OR (2008) Benchmarking: een kwestie van leren, digital publication. URL: http://www.benchmarking-ok.nl
Cameron AC, Trivedi PK (2005) Microeconometrics. Cambridge University Press, Cambridge
Dexter F, Zhou J (1998) Method to assist in the scheduling of add-on surgical cases. Anesthesiology 89: 1228–1232
Dexter F, Macario A, Ledolter J (2007) Identification and systematic underestimation (bias) of case durations during case scheduling would not markedly reduce over-utilized operating room time. J Clin Anesthesiol 19: 198–203
Dexter F, Dexter EU, Masursky D, Nussmeier NA (2008) Systematic review of general thoraric surgery articles to identify predictors of operating room case duration. Anaesth Analg 106: 1232–1241
Eijkemans MJC, Van Houdenhoven M, Nguyen T, Boersma E, Steyerberg EW, Kazemier G (2010) Predicting the unpredictable: a new prediction model for operating room times using individual characteristics and the surgeon’s estimate. Anesthesiology 12: 41–49
Joustra P, Meester R, Van Ophem H (2010) Can statisticians beat surgeons at the planning of operations. Discussion paper 2010/06. UvA-Econometrics, Amsterdam/School of Economics, University of Amsterdam
Lancaster T (1990) The econometric analysis of transition data. Cambridge University Press, Cambridge
Macario A, Vites TS, Dunn B, McDonald T (1995) Where are the costs in perioperative care?: analysis of hospital costs and charges for inpatient surgical care. Anaesthesiology 83: 1138–1144
Pandit JJ, Carey A (2006) Estimating the duration of common elective operations: implications for operating list management. Anesthesia 1: 768–776
Rossiter CE, Reynolds JA (1963) Automatic monitoring of the time waited in out-patient departments. Med Care 1: 218–225
Stepaniak PS, Heij C, Mannaerts GH, de Quelerij M, De Vries G (2009) Modeling procedure and surgical times for current procedural terminology-anesthesia-surgeon combinations and evaluation in terms of case-duration prediction and operating room efficiency: a multicenter study. Anesth Analg 109: 1232–1245
Stepaniak PS, Heijand C, De Vries G (2010) Modeling and prediction of surgical procedure times. Stat Neerl 64: 1–18
Strum DP, May JH, Vargas LG (2000a) Modeling the uncertainty of surgical procedure times. Anesthesiology 94: 1160–1167
Strum DP, Sampson AR, May JH, Vargas LG (2000b) Surgeon and type of anaesthesia predict variability in surgical procedure times. Anesthesiology 92: 1454–1466
Strum DP, May JH, Sampson AR, Vargas LG, Sprangler WE (2003) Estimating times of surgeries with two component procedures. Anesthesiology 98: 232–240
Van Houdenhoven M, Van Oostrum JM, Hans EW, Wullink G, Kazemier G (2007) Improving operating room efficiency by applying bin-packing and portfolio techniques to surgical case scheduling. Anesth Analg 105: 707–714
Wullink GM, Van Houdenhoven M, Hans EW, Van Oostrum JM, Van Der Lans M, Kazemier G (2007) Closing emergency operating rooms improves efficiency. J Med Syst 31: 543–546
Acknowledgments
The comments of two anonymous referees are gratefully acknowledged. All ML-routines used are either performed by using standard routines from Stata or are carried out using R (free software, for information see http://www.r-project.org/).
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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Joustra, P., Meester, R. & van Ophem, H. Can statisticians beat surgeons at the planning of operations?. Empir Econ 44, 1697–1718 (2013). https://doi.org/10.1007/s00181-012-0594-0
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DOI: https://doi.org/10.1007/s00181-012-0594-0