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Simulation-based evaluation of operating room management policies
BACKGROUND: Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to r...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992985/ https://www.ncbi.nlm.nih.gov/pubmed/33761931 http://dx.doi.org/10.1186/s12913-021-06234-5 |
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author | Schoenfelder, Jan Kohl, Sebastian Glaser, Manuel McRae, Sebastian Brunner, Jens O. Koperna, Thomas |
author_facet | Schoenfelder, Jan Kohl, Sebastian Glaser, Manuel McRae, Sebastian Brunner, Jens O. Koperna, Thomas |
author_sort | Schoenfelder, Jan |
collection | PubMed |
description | BACKGROUND: Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg. METHODS: Based on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries. RESULTS: We identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators. CONCLUSIONS: Our simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06234-5. |
format | Online Article Text |
id | pubmed-7992985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79929852021-03-26 Simulation-based evaluation of operating room management policies Schoenfelder, Jan Kohl, Sebastian Glaser, Manuel McRae, Sebastian Brunner, Jens O. Koperna, Thomas BMC Health Serv Res Research Article BACKGROUND: Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg. METHODS: Based on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries. RESULTS: We identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators. CONCLUSIONS: Our simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06234-5. BioMed Central 2021-03-24 /pmc/articles/PMC7992985/ /pubmed/33761931 http://dx.doi.org/10.1186/s12913-021-06234-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Schoenfelder, Jan Kohl, Sebastian Glaser, Manuel McRae, Sebastian Brunner, Jens O. Koperna, Thomas Simulation-based evaluation of operating room management policies |
title | Simulation-based evaluation of operating room management policies |
title_full | Simulation-based evaluation of operating room management policies |
title_fullStr | Simulation-based evaluation of operating room management policies |
title_full_unstemmed | Simulation-based evaluation of operating room management policies |
title_short | Simulation-based evaluation of operating room management policies |
title_sort | simulation-based evaluation of operating room management policies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992985/ https://www.ncbi.nlm.nih.gov/pubmed/33761931 http://dx.doi.org/10.1186/s12913-021-06234-5 |
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