Using the language of surgery to enhance ophthalmology surgical education.
Education standardization
Language of surgery
Ophthalmology
Robotic surgery
Surgical education
Surgical instruments
Journal
Surgery open science
ISSN: 2589-8450
Titre abrégé: Surg Open Sci
Pays: United States
ID NLM: 101768812
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
received:
02
07
2023
accepted:
09
07
2023
medline:
2
8
2023
pubmed:
2
8
2023
entrez:
2
8
2023
Statut:
epublish
Résumé
Currently, surgical education utilizes a combination of the apprentice model, wet-lab training, and simulation, but due to reliance on subjective data, the quality of teaching and assessment can be variable. The "language of surgery," an established concept in engineering literature whose incorporation into surgical education has been limited, is defined as the description of each surgical maneuver using quantifiable metrics. This concept is different from the traditional notion of surgical language, generally thought of as the qualitative definitions and terminology used by surgeons. A literature search was conducted through April 2023 using MEDLINE/PubMed using search terms to investigate wet-lab, virtual simulators, and robotics in ophthalmology, along with the language of surgery and surgical education. Articles published before 2005 were mostly excluded, although a few were included on a case-by-case basis. Surgical maneuvers can be quantified by leveraging technological advances in virtual simulators, video recordings, and surgical robots to create a language of surgery. By measuring and describing maneuver metrics, the learning surgeon can adjust surgical movements in an appropriately graded fashion that is based on objective and standardized data. The main contribution is outlining a structured education framework that details how surgical education could be improved by incorporating the language of surgery, using ophthalmology surgical education as an example. By describing each surgical maneuver in quantifiable, objective, and standardized terminology, a language of surgery can be created that can be used to learn, teach, and assess surgical technical skill with an approach that minimizes bias. The "language of surgery," defined as the quantification of each surgical movement's characteristics, is an established concept in the engineering literature. Using ophthalmology surgical education as an example, we describe a structured education framework based on the language of surgery to improve surgical education. Surgical education, robotic surgery, ophthalmology, education standardization, computerized assessment, simulations in teaching. Practice-Based Learning and Improvement.
Sections du résumé
Background
UNASSIGNED
Currently, surgical education utilizes a combination of the apprentice model, wet-lab training, and simulation, but due to reliance on subjective data, the quality of teaching and assessment can be variable. The "language of surgery," an established concept in engineering literature whose incorporation into surgical education has been limited, is defined as the description of each surgical maneuver using quantifiable metrics. This concept is different from the traditional notion of surgical language, generally thought of as the qualitative definitions and terminology used by surgeons.
Methods
UNASSIGNED
A literature search was conducted through April 2023 using MEDLINE/PubMed using search terms to investigate wet-lab, virtual simulators, and robotics in ophthalmology, along with the language of surgery and surgical education. Articles published before 2005 were mostly excluded, although a few were included on a case-by-case basis.
Results
UNASSIGNED
Surgical maneuvers can be quantified by leveraging technological advances in virtual simulators, video recordings, and surgical robots to create a language of surgery. By measuring and describing maneuver metrics, the learning surgeon can adjust surgical movements in an appropriately graded fashion that is based on objective and standardized data. The main contribution is outlining a structured education framework that details how surgical education could be improved by incorporating the language of surgery, using ophthalmology surgical education as an example.
Conclusion
UNASSIGNED
By describing each surgical maneuver in quantifiable, objective, and standardized terminology, a language of surgery can be created that can be used to learn, teach, and assess surgical technical skill with an approach that minimizes bias.
Key message
UNASSIGNED
The "language of surgery," defined as the quantification of each surgical movement's characteristics, is an established concept in the engineering literature. Using ophthalmology surgical education as an example, we describe a structured education framework based on the language of surgery to improve surgical education.
Classifications
UNASSIGNED
Surgical education, robotic surgery, ophthalmology, education standardization, computerized assessment, simulations in teaching.
Competencies
UNASSIGNED
Practice-Based Learning and Improvement.
Identifiants
pubmed: 37528917
doi: 10.1016/j.sopen.2023.07.002
pii: S2589-8450(23)00037-4
pmc: PMC10387608
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
52-59Informations de copyright
© 2023 The Authors.
Déclaration de conflit d'intérêts
James T. Handa receives grant funding and royalties from Bayer Pharmaceuticals. He also receives grant funding and is a member of the Scientific Advisory Board for Clover Therapeutics, is a member of the Scientific Advisory Board for Seeing Medicines, and serves as a consultant for Nano Retina. Nathan Pan-Doh, Shameema Sikder, and Fasika A. Woreta report no proprietary or commercial interest in any product mentioned or concept discussed in this article.
Références
Retina. 2013 Jan;33(1):200-6
pubmed: 22810149
Reg Anesth Pain Med. 2011 May-Jun;36(3):213-9
pubmed: 21519307
Acta Ophthalmol. 2013 Aug;91(5):469-74
pubmed: 22676143
J Am Coll Surg. 2001 Nov;193(5):479-85
pubmed: 11708503
J Surg Educ. 2021 Jul-Aug;78(4):1077-1088
pubmed: 33640326
Annu Rev Biomed Eng. 2017 Jun 21;19:301-325
pubmed: 28375649
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):435-42
pubmed: 20426017
Retina. 2020 Nov;40(11):2091-2098
pubmed: 31842191
BMC Anesthesiol. 2017 Sep 29;17(1):131
pubmed: 28962548
Invest Ophthalmol Vis Sci. 2013 Feb 15;54(2):1316-24
pubmed: 23329663
IEEE Trans Robot. 2012 Feb 1;28(1):195-212
pubmed: 23028266
IEEE Trans Robot. 2020 Aug;36(4):1207-1218
pubmed: 36168513
Br J Ophthalmol. 2021 Oct;105(10):1325-1328
pubmed: 32816750
J Cataract Refract Surg. 2014 Apr;40(4):657-65
pubmed: 24581974
Obstet Gynecol Clin North Am. 2006 Jun;33(2):233-6, vii
pubmed: 16647599
Eye (Lond). 2014 Jan;28(1):78-84
pubmed: 24071776
Ophthalmology. 2011 Feb;118(2):427.e1-5
pubmed: 21292117
Ophthalmology. 2005 Jul;112(7):1236-41
pubmed: 15922450
Eye (Lond). 2011 Jul;25(7):947-53
pubmed: 21527954
Graefes Arch Clin Exp Ophthalmol. 2013 Sep;251(9):2295-6
pubmed: 23532452
Surg Endosc. 2000 Sep;14(9):791-8
pubmed: 11000356
Int J Comput Assist Radiol Surg. 2020 Jul;15(7):1187-1194
pubmed: 32385598
Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron. 2010 Sep 1;2010(26-29):814-819
pubmed: 21461178
Arch Ophthalmol. 2006 Sep;124(9):1263-6
pubmed: 16966621
Indian J Ophthalmol. 2017 Sep;65(9):898-899
pubmed: 28905845
Acta Ophthalmol. 2021 Feb;99(1):90-96
pubmed: 32701225
Int J Med Robot. 2013 Jun;9(2):180-9
pubmed: 22588785
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):426-34
pubmed: 20426016
Transl Vis Sci Technol. 2020 Sep 01;9(10):2
pubmed: 32953242
Ophthalmology. 2006 Jul;113(7):1237-44
pubmed: 16725202
Int J Comput Assist Radiol Surg. 2019 Jun;14(6):1097-1105
pubmed: 30977091
Int J Comput Assist Radiol Surg. 2020 Jan;15(1):15-25
pubmed: 31605352
Int J Comput Assist Radiol Surg. 2015 Jun;10(6):981-91
pubmed: 25895080
Eye (Lond). 2019 Feb;33(2):313-319
pubmed: 30206417
JAMA Netw Open. 2019 Apr 5;2(4):e191860
pubmed: 30951163
Surv Ophthalmol. 2017 May - Jun;62(3):371-377
pubmed: 28104385
Acta Ophthalmol. 2017 May;95(3):270-275
pubmed: 28084059
Can J Anaesth. 2009 Jun;56(6):419-26
pubmed: 19340491
Eye (Lond). 2013 Aug;27(8):972-8
pubmed: 23722720
J Cataract Refract Surg. 1990 Jan;16(1):31-7
pubmed: 2299571
J Cataract Refract Surg. 2013 Oct;39(10):1616-7
pubmed: 24075164
Indian J Ophthalmol. 2018 Jun;66(6):793-797
pubmed: 29785985
Am J Surg. 2002 Jul;184(1):70-3
pubmed: 12135725
JAMA Ophthalmol. 2013 May;131(5):659-61
pubmed: 23519488
Biomed Opt Express. 2015 Jan 09;6(2):457-72
pubmed: 25780736
J Cataract Refract Surg. 2017 Apr;43(4):552-557
pubmed: 28532942
Br J Ophthalmol. 2020 Mar;104(3):324-329
pubmed: 31142463
Nat Biomed Eng. 2018 Jun 18;2:649-656
pubmed: 30263872
Med Image Comput Comput Assist Interv. 2005;8(Pt 1):802-10
pubmed: 16685920
Eye (Lond). 2020 Oct;34(10):1737-1759
pubmed: 32203241
J Cataract Refract Surg. 2021 Feb 1;47(2):256-264
pubmed: 32675650
Surg Clin North Am. 2021 Aug;101(4):587-595
pubmed: 34242602
BJS Open. 2018 Apr 27;2(3):151-157
pubmed: 29951639
J Thorac Cardiovasc Surg. 2012 Mar;143(3):528-34
pubmed: 22172215
Surv Ophthalmol. 2019 Jul - Aug;64(4):570-578
pubmed: 30703406
PLoS One. 2016 Sep 27;11(9):e0162037
pubmed: 27676261
NPJ Digit Med. 2022 Mar 3;5(1):24
pubmed: 35241760
Int J Med Robot. 2018 Feb;14(1):
pubmed: 28762253
Eye (Lond). 2020 Sep;34(9):1554-1562
pubmed: 32152518
IEEE Trans Biomed Eng. 2020 Jul;67(7):2073-2083
pubmed: 31751219
Clin Ophthalmol. 2013;7:1973-7
pubmed: 24124350
Ann Biomed Eng. 2018 Oct;46(10):1676-1685
pubmed: 29797141
IEEE Trans Biomed Eng. 2017 Sep;64(9):2025-2041
pubmed: 28060703
Graefes Arch Clin Exp Ophthalmol. 2011 Aug;249(8):1263-5
pubmed: 20931214
J Cataract Refract Surg. 2008 Jun;34(6):980-5
pubmed: 18499005
Retina. 2017 Jul;37(7):1220-1228
pubmed: 27893625
IEEE Trans Biomed Eng. 2001 May;48(5):579-91
pubmed: 11341532
PLoS One. 2016 Mar 07;11(3):e0149174
pubmed: 26950551