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Experience matters for robotic assistance: an analysis of case data
Many robotic procedures require active participation by assistants. Most prior work on assistants’ effect on outcomes has been limited in procedural focus and scope, with studies reporting differing results. Knowing how assistant experience affects operating room time could inform operating room cas...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492713/ https://www.ncbi.nlm.nih.gov/pubmed/37450105 http://dx.doi.org/10.1007/s11701-023-01677-w |
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author | Brian, Riley Oh, Daniel Ifuku, Kelli Ann Sarin, Ankit O’Sullivan, Patricia Chern, Hueylan |
author_facet | Brian, Riley Oh, Daniel Ifuku, Kelli Ann Sarin, Ankit O’Sullivan, Patricia Chern, Hueylan |
author_sort | Brian, Riley |
collection | PubMed |
description | Many robotic procedures require active participation by assistants. Most prior work on assistants’ effect on outcomes has been limited in procedural focus and scope, with studies reporting differing results. Knowing how assistant experience affects operating room time could inform operating room case scheduling and provide an impetus for additional assistant training. As such, this retrospective cohort study aimed to determine the association between assistant experience and operating room time for 2291 robotic-assisted operations performed from 2016 to 2022 at our institution. Linear regression showed a significant association between the presence of a junior resident and increased case length differential with an increase of 26.9 min (p = 0.01). There were no significant associations between the presence of a senior resident (p = 0.52), presence of a fellow (p = 0.20), or presence of a physician assistant (p = 0.43) and case length differential. The finding of increased operating room time in the presence of a junior resident during robotic cases supports consideration of the adoption of formal assistant training programs for residents to improve efficiency. |
format | Online Article Text |
id | pubmed-10492713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-104927132023-09-11 Experience matters for robotic assistance: an analysis of case data Brian, Riley Oh, Daniel Ifuku, Kelli Ann Sarin, Ankit O’Sullivan, Patricia Chern, Hueylan J Robot Surg Research Many robotic procedures require active participation by assistants. Most prior work on assistants’ effect on outcomes has been limited in procedural focus and scope, with studies reporting differing results. Knowing how assistant experience affects operating room time could inform operating room case scheduling and provide an impetus for additional assistant training. As such, this retrospective cohort study aimed to determine the association between assistant experience and operating room time for 2291 robotic-assisted operations performed from 2016 to 2022 at our institution. Linear regression showed a significant association between the presence of a junior resident and increased case length differential with an increase of 26.9 min (p = 0.01). There were no significant associations between the presence of a senior resident (p = 0.52), presence of a fellow (p = 0.20), or presence of a physician assistant (p = 0.43) and case length differential. The finding of increased operating room time in the presence of a junior resident during robotic cases supports consideration of the adoption of formal assistant training programs for residents to improve efficiency. Springer London 2023-07-14 2023 /pmc/articles/PMC10492713/ /pubmed/37450105 http://dx.doi.org/10.1007/s11701-023-01677-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Brian, Riley Oh, Daniel Ifuku, Kelli Ann Sarin, Ankit O’Sullivan, Patricia Chern, Hueylan Experience matters for robotic assistance: an analysis of case data |
title | Experience matters for robotic assistance: an analysis of case data |
title_full | Experience matters for robotic assistance: an analysis of case data |
title_fullStr | Experience matters for robotic assistance: an analysis of case data |
title_full_unstemmed | Experience matters for robotic assistance: an analysis of case data |
title_short | Experience matters for robotic assistance: an analysis of case data |
title_sort | experience matters for robotic assistance: an analysis of case data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492713/ https://www.ncbi.nlm.nih.gov/pubmed/37450105 http://dx.doi.org/10.1007/s11701-023-01677-w |
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