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. 2023 Jun;26(2):261-278.
doi: 10.1007/s10729-022-09622-3. Epub 2022 Dec 19.

Operating room design using agent-based simulation to reduce room obstructions

Affiliations

Operating room design using agent-based simulation to reduce room obstructions

Kevin Taaffe et al. Health Care Manag Sci. 2023 Jun.

Abstract

This study seeks to improve the safety of clinical care provided in operating rooms (OR) by examining how characteristics of both the physical environment and the procedure affect surgical team movement and contacts. We video recorded staff movements during a set of surgical procedures. Then we divided the OR into multiple zones and analyzed the frequency and duration of movement from origin to destination through zones. This data was abstracted into a generalized, agent-based, discrete event simulation model to study how OR size and OR equipment layout affected surgical staff movement and total number of surgical team contacts during a procedure. A full factorial experiment with seven input factors - OR size, OR shape, operating table orientation, circulating nurse (CN) workstation location, team size, number of doors, and procedure type - was conducted. Results were analyzed using multiple linear regression with surgical team contacts as the dependent variable. The OR size, the CN workstation location, and team size significantly affected surgical team contacts. Also, two- and three-way interactions between staff, procedure type, table orientation, and CN workstation location significantly affected contacts. We discuss implications of these findings for OR managers and for future research about designing future ORs.

Keywords: Agent-based simulation; Markov chains; Operating room design; Operations management; Operations research; Statistical analysis; Surgical safety.

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Conflict of interest statement

Conflicts of interest/Competing interests The authors have no relevant financial or non-financial interests to disclose.

The authors have no conflicts of interest to declare that are relevant to the content of this article.

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no financial or proprietary interests in any material discussed in this article.

Figures

Fig. 1
Fig. 1
Sample zone locations in a sample OR
Fig. 2
Fig. 2
Movement via exact path vs. destination zones only
Fig. 3
Fig. 3
Transition probabilities and dwell times (mean and standard deviation): Scrub tech, intra-operative phase, Adult G-LAP
Fig. 4
Fig. 4
The movement patterns of a nurse in both playback and probabilistic models
Fig. 5
Fig. 5
Two-way Interaction between Team Size and (a) Procedure Type or (b) Room Size
Fig. 6
Fig. 6
Two-way Interaction between Procedure Type and (a) OR Table Orientation or (b) CN Workstation Location
Fig. 7
Fig. 7
Three-way Interaction between (1) OR Table Orientation, (2) Procedure Type, and (3) either CN (a) Workstation Location or (b) Team Size or (c) Room Size

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