Literature DB >> 25479906

Enhancement opportunities in operating room utilization; with a statistical appendix.

Elizabeth van Veen-Berkx1, Sylvia G Elkhuizen2, Sanne van Logten3, Wolfgang F Buhre4, Cor J Kalkman5, Hein G Gooszen6, Geert Kazemier7.   

Abstract

BACKGROUND: The purpose of this study was to assess the direct and indirect relationships between first-case tardiness (or "late start"), turnover time, underused operating room (OR) time, and raw utilization, as well as to determine which indicator had the most negative impact on OR utilization to identify improvement potential. Furthermore, we studied the indirect relationships of the three indicators of "nonoperative" time on OR utilization, to recognize possible "trickle down" effects during the day.
MATERIALS AND METHODS: (Multiple) linear regression analysis and mediation effect analysis were applied to a data set from all eight University Medical Centers in the Netherlands. This data set consisted of 190,071 OR days (on which 623,871 surgical cases were performed).
RESULTS: Underused OR time at the end of the day had the strongest influence on raw utilization, followed by late start and turnover time. The relationships between the three "nonoperative" time indicators were negligible. The impact of the partial indirect effects of "nonoperative" time indicators on raw utilization were statistically significant, but relatively small. The "trickle down" effect that late start can cause resulting in an increased delay as the day progresses, was not supported by our results.
CONCLUSIONS: The study findings clearly suggest that OR utilization can be improved by focusing on the reduction of underused OR time at the end of the day. Improving the prediction of total procedure time, improving OR scheduling by, for example, altering the sequencing of operations, changing patient cancellation policies, and flexible staffing of ORs adjusted to patient needs, are means to reduce "nonoperative" time.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Benchmarking; Nonoperative time; Operating rooms; Performance indicators; Utilization

Mesh:

Year:  2014        PMID: 25479906     DOI: 10.1016/j.jss.2014.10.044

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  5 in total

1.  The Impact of Overestimations of Surgical Control Times Across Multiple Specialties on Medical Systems.

Authors:  Albert Wu; Ethan Y Brovman; Edward E Whang; Jesse M Ehrenfeld; Richard D Urman
Journal:  J Med Syst       Date:  2016-02-10       Impact factor: 4.460

2.  Operating Room Efficiency before and after Entrance in a Benchmarking Program for Surgical Process Data.

Authors:  Sara Pedron; Vera Winter; Eva-Maria Oppel; Enno Bialas
Journal:  J Med Syst       Date:  2017-08-23       Impact factor: 4.460

3.  Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration.

Authors:  Matthew A Bartek; Rajeev C Saxena; Stuart Solomon; Christine T Fong; Lakshmana D Behara; Ravitheja Venigandla; Kalyani Velagapudi; John D Lang; Bala G Nair
Journal:  J Am Coll Surg       Date:  2019-07-13       Impact factor: 6.113

4.  Machine Learning-Based Models Predicting Outpatient Surgery End Time and Recovery Room Discharge at an Ambulatory Surgery Center.

Authors:  Rodney A Gabriel; Bhavya Harjai; Sierra Simpson; Nicole Goldhaber; Brian P Curran; Ruth S Waterman
Journal:  Anesth Analg       Date:  2022-04-07       Impact factor: 6.627

5.  Surgical phase modelling in minimal invasive surgery.

Authors:  F C Meeuwsen; F van Luyn; M D Blikkendaal; F W Jansen; J J van den Dobbelsteen
Journal:  Surg Endosc       Date:  2018-09-05       Impact factor: 4.584

  5 in total

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