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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. 2009 Oct; 109(4):1232-45.A&A

Abstract

BACKGROUND

Gains in operating room (OR) scheduling may be obtained by using accurate statistical models to predict surgical and procedure times. The 3 main contributions of this article are the following: (i) the validation of Strum's results on the statistical distribution of case durations, including surgeon effects, using OR databases of 2 European hospitals, (ii) the use of expert prior expectations to predict durations of rarely observed cases, and (iii) the application of the proposed methods to predict case durations, with an analysis of the resulting increase in OR efficiency.

METHODS

We retrospectively reviewed all recorded surgical cases of 2 large European teaching hospitals from 2005 to 2008, involving 85,312 cases and 92,099 h in total. Surgical times tended to be skewed and bounded by some minimally required time. We compared the fit of the normal distribution with that of 2- and 3-parameter lognormal distributions for case durations of a range of Current Procedural Terminology (CPT)-anesthesia combinations, including possible surgeon effects. For cases with very few observations, we investigated whether supplementing the data information with surgeons' prior guesses helps to obtain better duration estimates. Finally, we used best fitting duration distributions to simulate the potential efficiency gains in OR scheduling.

RESULTS

The 3-parameter lognormal distribution provides the best results for the case durations of CPT-anesthesia (surgeon) combinations, with an acceptable fit for almost 90% of the CPTs when segmented by the factor surgeon. The fit is best for surgical times and somewhat less for total procedure times. Surgeons' prior guesses are helpful for OR management to improve duration estimates of CPTs with very few (<10) observations. Compared with the standard way of case scheduling using the mean of the 3-parameter lognormal distribution for case scheduling reduces the mean overreserved OR time per case up to 11.9 (11.8-12.0) min (55.6%) and the mean underreserved OR time per case up to 16.7 (16.5-16.8) min (53.1%). When scheduling cases using the 4-parameter lognormal model the mean overutilized OR time is up to 20.0 (19.7-20.3) min per OR per day lower than for the standard method and 11.6 (11.3-12.0) min per OR per day lower as compared with the biased corrected mean.

CONCLUSIONS

OR case scheduling can be improved by using the 3-parameter lognormal model with surgeon effects and by using surgeons' prior guesses for rarely observed CPTs. Using the 3-parameter lognormal model for case-duration prediction and scheduling significantly reduces both the prediction error and OR inefficiency.

Authors+Show Affiliations

Institute of Health Policy and Management, Erasmus University Rotterdam, The Netherlands. stepaniak@bmg.eur.nlNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Multicenter Study
Validation Study

Language

eng

PubMed ID

19762753

Citation

Stepaniak, Pieter S., et al. "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." Anesthesia and Analgesia, vol. 109, no. 4, 2009, pp. 1232-45.
Stepaniak PS, Heij C, Mannaerts GH, et al. 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. 2009;109(4):1232-45.
Stepaniak, P. S., Heij, C., Mannaerts, G. H., 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. Anesthesia and Analgesia, 109(4), 1232-45. https://doi.org/10.1213/ANE.0b013e3181b5de07
Stepaniak PS, et al. 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. 2009;109(4):1232-45. PubMed PMID: 19762753.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - 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. AU - Stepaniak,Pieter S, AU - Heij,Christiaan, AU - Mannaerts,Guido H H, AU - de Quelerij,Marcel, AU - de Vries,Guus, PY - 2009/9/19/entrez PY - 2009/9/19/pubmed PY - 2009/10/2/medline SP - 1232 EP - 45 JF - Anesthesia and analgesia JO - Anesth Analg VL - 109 IS - 4 N2 - BACKGROUND: Gains in operating room (OR) scheduling may be obtained by using accurate statistical models to predict surgical and procedure times. The 3 main contributions of this article are the following: (i) the validation of Strum's results on the statistical distribution of case durations, including surgeon effects, using OR databases of 2 European hospitals, (ii) the use of expert prior expectations to predict durations of rarely observed cases, and (iii) the application of the proposed methods to predict case durations, with an analysis of the resulting increase in OR efficiency. METHODS: We retrospectively reviewed all recorded surgical cases of 2 large European teaching hospitals from 2005 to 2008, involving 85,312 cases and 92,099 h in total. Surgical times tended to be skewed and bounded by some minimally required time. We compared the fit of the normal distribution with that of 2- and 3-parameter lognormal distributions for case durations of a range of Current Procedural Terminology (CPT)-anesthesia combinations, including possible surgeon effects. For cases with very few observations, we investigated whether supplementing the data information with surgeons' prior guesses helps to obtain better duration estimates. Finally, we used best fitting duration distributions to simulate the potential efficiency gains in OR scheduling. RESULTS: The 3-parameter lognormal distribution provides the best results for the case durations of CPT-anesthesia (surgeon) combinations, with an acceptable fit for almost 90% of the CPTs when segmented by the factor surgeon. The fit is best for surgical times and somewhat less for total procedure times. Surgeons' prior guesses are helpful for OR management to improve duration estimates of CPTs with very few (<10) observations. Compared with the standard way of case scheduling using the mean of the 3-parameter lognormal distribution for case scheduling reduces the mean overreserved OR time per case up to 11.9 (11.8-12.0) min (55.6%) and the mean underreserved OR time per case up to 16.7 (16.5-16.8) min (53.1%). When scheduling cases using the 4-parameter lognormal model the mean overutilized OR time is up to 20.0 (19.7-20.3) min per OR per day lower than for the standard method and 11.6 (11.3-12.0) min per OR per day lower as compared with the biased corrected mean. CONCLUSIONS: OR case scheduling can be improved by using the 3-parameter lognormal model with surgeon effects and by using surgeons' prior guesses for rarely observed CPTs. Using the 3-parameter lognormal model for case-duration prediction and scheduling significantly reduces both the prediction error and OR inefficiency. SN - 1526-7598 UR - https://www.unboundmedicine.com/medline/citation/19762753/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_ L2 - https://doi.org/10.1213/ANE.0b013e3181b5de07 DB - PRIME DP - Unbound Medicine ER -