Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting

Background Transoral robotic surgery has been successfully used by head and neck surgeons for a variety of procedures but is limited by rigid instrumentation and line-of-sight visualization. Non-linear systems specifically designed for the aerodigestive tract are needed. Ease of use of these new sys...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Surgical endoscopy 2022-02, Vol.36 (2), p.1563-1572
Hauptverfasser: Zhu, Toby S., Godse, Neal, Clayburgh, Daniel R., Duvvuri, Umamaheswar
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1572
container_issue 2
container_start_page 1563
container_title Surgical endoscopy
container_volume 36
creator Zhu, Toby S.
Godse, Neal
Clayburgh, Daniel R.
Duvvuri, Umamaheswar
description Background Transoral robotic surgery has been successfully used by head and neck surgeons for a variety of procedures but is limited by rigid instrumentation and line-of-sight visualization. Non-linear systems specifically designed for the aerodigestive tract are needed. Ease of use of these new systems in both training and clinical environments is critical in its widespread adoption. Methods Residents, fellows, and junior faculty performed four tasks on an anatomical airway mannequin using the Medrobotics FLEX™ Robotic System: expose and incise the tonsil, grasp the epiglottis, palpate the vocal processes, and grasp the interarytenoid space. These tasks were performed once a day for four days; after a 4-month time gap, subjects were asked to perform these same tasks for three more days. Time to task completion and total distance driven were tracked. In addition, a retrospective analysis was performed analyzing one attending physician’s experience with clinical usage of the robot. Results 13 subjects completed the initial round of the mannequin simulation and 8 subjects completed the additional testing 4 months later. Subjects rapidly improved their speed and efficiency at task completion. Junior residents were slower in most tasks initially compared to senior trainees but quickly reached similar levels of efficiency. Following the break there was minimal degradation in skills and continued improvement in efficiency was observed with additional trials. There was significant heterogeneity in the analyzed clinical cases, but when analyzing cases of similar complexity and pathology, clear decreases in overall operative times were demonstrable. Conclusion Novice users quickly gained proficiency with the FLEX™ Robotic System in a training environment, and these skills are retained after several months. This learning could translate to the clinical setting if a proper training regimen is developed. The Medrobotics FLEX™ Robotic System shows promise as a surgical tool in head and neck surgery in this study.
doi_str_mv 10.1007/s00464-021-08445-7
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8733873</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2619338403</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-98d68434d984d44944ed89bd82db609d7618702d214de74027dfbbd895f4682a3</originalsourceid><addsrcrecordid>eNp9UcuKFDEUDaI4besPuJCAGzeleVUl2QjD4AsG3Og6pCq3ujOkkzZJ9ejfm54e28fCRQiX87jnchB6TslrSoh8UwgRg-gIox1RQvSdfIBWVHDWMUbVQ7QimpOOSS0u0JNSbkjja9o_Rhecy54yylcoXJYCpfi4wXULOIDN8ThMSz4AtqWkydsKDt_6usUWx3SAgOcA3_0YAOc0pop9vBPvM3RT8NFPNmAbHT4PBWptrk_Ro9mGAs_u_zX6-v7dl6uP3fXnD5-uLq-7SUhRO63coAQXTivhhNBCgFN6dIq5cSDayYEqSZhjVDiQgjDp5rHBup_FoJjla_T25Ltfxh24CWLNNph99jubf5hkvfkbiX5rNulglOT8-Nbo1b1BTt8WKNXsfJkgBBshLcWwnrR8quVo1Jf_UG_SkmM7z7CB6uYnyNGQnVhTTqVkmM9hKDHHMs2pTNPKNHdlGtlEL_484yz51V4j8BOhNChuIP_e_R_bn9F_q0k</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2619338403</pqid></control><display><type>article</type><title>Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Zhu, Toby S. ; Godse, Neal ; Clayburgh, Daniel R. ; Duvvuri, Umamaheswar</creator><creatorcontrib>Zhu, Toby S. ; Godse, Neal ; Clayburgh, Daniel R. ; Duvvuri, Umamaheswar</creatorcontrib><description>Background Transoral robotic surgery has been successfully used by head and neck surgeons for a variety of procedures but is limited by rigid instrumentation and line-of-sight visualization. Non-linear systems specifically designed for the aerodigestive tract are needed. Ease of use of these new systems in both training and clinical environments is critical in its widespread adoption. Methods Residents, fellows, and junior faculty performed four tasks on an anatomical airway mannequin using the Medrobotics FLEX™ Robotic System: expose and incise the tonsil, grasp the epiglottis, palpate the vocal processes, and grasp the interarytenoid space. These tasks were performed once a day for four days; after a 4-month time gap, subjects were asked to perform these same tasks for three more days. Time to task completion and total distance driven were tracked. In addition, a retrospective analysis was performed analyzing one attending physician’s experience with clinical usage of the robot. Results 13 subjects completed the initial round of the mannequin simulation and 8 subjects completed the additional testing 4 months later. Subjects rapidly improved their speed and efficiency at task completion. Junior residents were slower in most tasks initially compared to senior trainees but quickly reached similar levels of efficiency. Following the break there was minimal degradation in skills and continued improvement in efficiency was observed with additional trials. There was significant heterogeneity in the analyzed clinical cases, but when analyzing cases of similar complexity and pathology, clear decreases in overall operative times were demonstrable. Conclusion Novice users quickly gained proficiency with the FLEX™ Robotic System in a training environment, and these skills are retained after several months. This learning could translate to the clinical setting if a proper training regimen is developed. The Medrobotics FLEX™ Robotic System shows promise as a surgical tool in head and neck surgery in this study.</description><identifier>ISSN: 0930-2794</identifier><identifier>EISSN: 1432-2218</identifier><identifier>DOI: 10.1007/s00464-021-08445-7</identifier><identifier>PMID: 33751213</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Abdominal Surgery ; Clinical Competence ; Efficiency ; Endoscopy ; Epiglottis ; Gastroenterology ; Gynecology ; Hepatology ; Humans ; Learning Curve ; Medicine ; Medicine &amp; Public Health ; Otolaryngology ; Proctology ; Retrospective Studies ; Robotic surgery ; Robotic Surgical Procedures - methods ; Robotics ; Simulation ; Surgeons ; Surgery ; Training</subject><ispartof>Surgical endoscopy, 2022-02, Vol.36 (2), p.1563-1572</ispartof><rights>The Author(s) 2021</rights><rights>2021. The Author(s).</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-98d68434d984d44944ed89bd82db609d7618702d214de74027dfbbd895f4682a3</citedby><cites>FETCH-LOGICAL-c474t-98d68434d984d44944ed89bd82db609d7618702d214de74027dfbbd895f4682a3</cites><orcidid>0000-0001-9264-9701</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00464-021-08445-7$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00464-021-08445-7$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33751213$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhu, Toby S.</creatorcontrib><creatorcontrib>Godse, Neal</creatorcontrib><creatorcontrib>Clayburgh, Daniel R.</creatorcontrib><creatorcontrib>Duvvuri, Umamaheswar</creatorcontrib><title>Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting</title><title>Surgical endoscopy</title><addtitle>Surg Endosc</addtitle><addtitle>Surg Endosc</addtitle><description>Background Transoral robotic surgery has been successfully used by head and neck surgeons for a variety of procedures but is limited by rigid instrumentation and line-of-sight visualization. Non-linear systems specifically designed for the aerodigestive tract are needed. Ease of use of these new systems in both training and clinical environments is critical in its widespread adoption. Methods Residents, fellows, and junior faculty performed four tasks on an anatomical airway mannequin using the Medrobotics FLEX™ Robotic System: expose and incise the tonsil, grasp the epiglottis, palpate the vocal processes, and grasp the interarytenoid space. These tasks were performed once a day for four days; after a 4-month time gap, subjects were asked to perform these same tasks for three more days. Time to task completion and total distance driven were tracked. In addition, a retrospective analysis was performed analyzing one attending physician’s experience with clinical usage of the robot. Results 13 subjects completed the initial round of the mannequin simulation and 8 subjects completed the additional testing 4 months later. Subjects rapidly improved their speed and efficiency at task completion. Junior residents were slower in most tasks initially compared to senior trainees but quickly reached similar levels of efficiency. Following the break there was minimal degradation in skills and continued improvement in efficiency was observed with additional trials. There was significant heterogeneity in the analyzed clinical cases, but when analyzing cases of similar complexity and pathology, clear decreases in overall operative times were demonstrable. Conclusion Novice users quickly gained proficiency with the FLEX™ Robotic System in a training environment, and these skills are retained after several months. This learning could translate to the clinical setting if a proper training regimen is developed. The Medrobotics FLEX™ Robotic System shows promise as a surgical tool in head and neck surgery in this study.</description><subject>Abdominal Surgery</subject><subject>Clinical Competence</subject><subject>Efficiency</subject><subject>Endoscopy</subject><subject>Epiglottis</subject><subject>Gastroenterology</subject><subject>Gynecology</subject><subject>Hepatology</subject><subject>Humans</subject><subject>Learning Curve</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Otolaryngology</subject><subject>Proctology</subject><subject>Retrospective Studies</subject><subject>Robotic surgery</subject><subject>Robotic Surgical Procedures - methods</subject><subject>Robotics</subject><subject>Simulation</subject><subject>Surgeons</subject><subject>Surgery</subject><subject>Training</subject><issn>0930-2794</issn><issn>1432-2218</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9UcuKFDEUDaI4besPuJCAGzeleVUl2QjD4AsG3Og6pCq3ujOkkzZJ9ejfm54e28fCRQiX87jnchB6TslrSoh8UwgRg-gIox1RQvSdfIBWVHDWMUbVQ7QimpOOSS0u0JNSbkjja9o_Rhecy54yylcoXJYCpfi4wXULOIDN8ThMSz4AtqWkydsKDt_6usUWx3SAgOcA3_0YAOc0pop9vBPvM3RT8NFPNmAbHT4PBWptrk_Ro9mGAs_u_zX6-v7dl6uP3fXnD5-uLq-7SUhRO63coAQXTivhhNBCgFN6dIq5cSDayYEqSZhjVDiQgjDp5rHBup_FoJjla_T25Ltfxh24CWLNNph99jubf5hkvfkbiX5rNulglOT8-Nbo1b1BTt8WKNXsfJkgBBshLcWwnrR8quVo1Jf_UG_SkmM7z7CB6uYnyNGQnVhTTqVkmM9hKDHHMs2pTNPKNHdlGtlEL_484yz51V4j8BOhNChuIP_e_R_bn9F_q0k</recordid><startdate>20220201</startdate><enddate>20220201</enddate><creator>Zhu, Toby S.</creator><creator>Godse, Neal</creator><creator>Clayburgh, Daniel R.</creator><creator>Duvvuri, Umamaheswar</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9264-9701</orcidid></search><sort><creationdate>20220201</creationdate><title>Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting</title><author>Zhu, Toby S. ; Godse, Neal ; Clayburgh, Daniel R. ; Duvvuri, Umamaheswar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-98d68434d984d44944ed89bd82db609d7618702d214de74027dfbbd895f4682a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Abdominal Surgery</topic><topic>Clinical Competence</topic><topic>Efficiency</topic><topic>Endoscopy</topic><topic>Epiglottis</topic><topic>Gastroenterology</topic><topic>Gynecology</topic><topic>Hepatology</topic><topic>Humans</topic><topic>Learning Curve</topic><topic>Medicine</topic><topic>Medicine &amp; Public Health</topic><topic>Otolaryngology</topic><topic>Proctology</topic><topic>Retrospective Studies</topic><topic>Robotic surgery</topic><topic>Robotic Surgical Procedures - methods</topic><topic>Robotics</topic><topic>Simulation</topic><topic>Surgeons</topic><topic>Surgery</topic><topic>Training</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhu, Toby S.</creatorcontrib><creatorcontrib>Godse, Neal</creatorcontrib><creatorcontrib>Clayburgh, Daniel R.</creatorcontrib><creatorcontrib>Duvvuri, Umamaheswar</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Surgical endoscopy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhu, Toby S.</au><au>Godse, Neal</au><au>Clayburgh, Daniel R.</au><au>Duvvuri, Umamaheswar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting</atitle><jtitle>Surgical endoscopy</jtitle><stitle>Surg Endosc</stitle><addtitle>Surg Endosc</addtitle><date>2022-02-01</date><risdate>2022</risdate><volume>36</volume><issue>2</issue><spage>1563</spage><epage>1572</epage><pages>1563-1572</pages><issn>0930-2794</issn><eissn>1432-2218</eissn><abstract>Background Transoral robotic surgery has been successfully used by head and neck surgeons for a variety of procedures but is limited by rigid instrumentation and line-of-sight visualization. Non-linear systems specifically designed for the aerodigestive tract are needed. Ease of use of these new systems in both training and clinical environments is critical in its widespread adoption. Methods Residents, fellows, and junior faculty performed four tasks on an anatomical airway mannequin using the Medrobotics FLEX™ Robotic System: expose and incise the tonsil, grasp the epiglottis, palpate the vocal processes, and grasp the interarytenoid space. These tasks were performed once a day for four days; after a 4-month time gap, subjects were asked to perform these same tasks for three more days. Time to task completion and total distance driven were tracked. In addition, a retrospective analysis was performed analyzing one attending physician’s experience with clinical usage of the robot. Results 13 subjects completed the initial round of the mannequin simulation and 8 subjects completed the additional testing 4 months later. Subjects rapidly improved their speed and efficiency at task completion. Junior residents were slower in most tasks initially compared to senior trainees but quickly reached similar levels of efficiency. Following the break there was minimal degradation in skills and continued improvement in efficiency was observed with additional trials. There was significant heterogeneity in the analyzed clinical cases, but when analyzing cases of similar complexity and pathology, clear decreases in overall operative times were demonstrable. Conclusion Novice users quickly gained proficiency with the FLEX™ Robotic System in a training environment, and these skills are retained after several months. This learning could translate to the clinical setting if a proper training regimen is developed. The Medrobotics FLEX™ Robotic System shows promise as a surgical tool in head and neck surgery in this study.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>33751213</pmid><doi>10.1007/s00464-021-08445-7</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9264-9701</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0930-2794
ispartof Surgical endoscopy, 2022-02, Vol.36 (2), p.1563-1572
issn 0930-2794
1432-2218
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8733873
source MEDLINE; SpringerNature Journals
subjects Abdominal Surgery
Clinical Competence
Efficiency
Endoscopy
Epiglottis
Gastroenterology
Gynecology
Hepatology
Humans
Learning Curve
Medicine
Medicine & Public Health
Otolaryngology
Proctology
Retrospective Studies
Robotic surgery
Robotic Surgical Procedures - methods
Robotics
Simulation
Surgeons
Surgery
Training
title Assessing the learning curve associated with a novel flexible robot in the pre-clinical and clinical setting
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T08%3A30%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessing%20the%20learning%20curve%20associated%20with%20a%20novel%20flexible%20robot%20in%20the%20pre-clinical%20and%20clinical%20setting&rft.jtitle=Surgical%20endoscopy&rft.au=Zhu,%20Toby%20S.&rft.date=2022-02-01&rft.volume=36&rft.issue=2&rft.spage=1563&rft.epage=1572&rft.pages=1563-1572&rft.issn=0930-2794&rft.eissn=1432-2218&rft_id=info:doi/10.1007/s00464-021-08445-7&rft_dat=%3Cproquest_pubme%3E2619338403%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2619338403&rft_id=info:pmid/33751213&rfr_iscdi=true