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Journal articles on the topic 'Surgical Skill'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Khan, M. S., S. D. Bann, A. Darzi, and P. E. M. Butler. "Assessing Surgical Skill." Plastic and Reconstructive Surgery 112, no. 7 (December 2003): 1886–89. http://dx.doi.org/10.1097/01.prs.0000091244.89368.3b.

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2

Golnik, Karl C., Hilary Beaver, Vinod Gauba, Andrew G. Lee, Eduardo Mayorga, Gabriela Palis, and George M. Saleh. "Cataract Surgical Skill Assessment." Ophthalmology 118, no. 2 (February 2011): 427–427. http://dx.doi.org/10.1016/j.ophtha.2010.09.023.

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3

Mishriki, S. F. "NICE forgot surgical skill." BMJ 337, no. 19 1 (November 19, 2008): a2579. http://dx.doi.org/10.1136/bmj.a2579.

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4

Byrne, Michelle. "Skill Acquisition." AORN Journal 43, no. 6 (June 1986): 1312–17. http://dx.doi.org/10.1016/s0001-2092(07)65161-8.

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5

Liang, Hui, and Min Yong Shi. "Surgical Skill Evaluation Model for Virtual Surgical Training." Applied Mechanics and Materials 40-41 (November 2010): 812–19. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.812.

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As a safe, cost-effective, and easily accessible tool for gaining experience in surgery, the simulation-based surgical skill training has attracted more and more attention in modern hospitals and institutes. One of the most important advantages of virtual surgical training is affording useful instructional feedback to users. However, how to provide systemic and competitive surgical technique evaluation to trainees is still untouched. In this paper, for UK’s Royal Bournemouth Hospital virtual surgery system, we creatively constructed a surgical technique evaluation model which consists of static structure and dynamic process, as well as an index system which covers aspects of surgery performance.

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6

Perez, Ray S., Anna Skinner, Peter Weyhrauch, James Niehaus, Corinna Lathan, Steven D. Schwaitzberg, and Caroline G. L. Cao. "Prevention of Surgical Skill Decay." Military Medicine 178, no. 10S (October 2013): 76–86. http://dx.doi.org/10.7205/milmed-d-13-00216.

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7

Siska, Van Bruwaene, Lissens Ann, De Win Gunter, Neyrinck Bart, Lens Willy, Schijven Marlies, and Miserez Marc. "Surgical Skill: Trick or Trait?" Journal of Surgical Education 72, no. 6 (November 2015): 1247–53. http://dx.doi.org/10.1016/j.jsurg.2015.05.004.

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8

Lendvay, Thomas S., Lee White, and Timothy Kowalewski. "Crowdsourcing to Assess Surgical Skill." JAMA Surgery 150, no. 11 (November 1, 2015): 1086. http://dx.doi.org/10.1001/jamasurg.2015.2405.

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9

Ori, Michele, Luca D'Ascanio, and Giampietro Ricci. "Daytime Sleepiness and Surgical Skill." JAMA Facial Plastic Surgery 21, no. 4 (July 2019): 343–44. http://dx.doi.org/10.1001/jamafacial.2018.2040.

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10

Phillips, Robert. "Cognitive scores measure surgical skill." Nature Reviews Urology 11, no. 3 (February 11, 2014): 130. http://dx.doi.org/10.1038/nrurol.2014.26.

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11

Puri, Sidharth, and Shameema Sikder. "Cataract surgical skill assessment tools." Journal of Cataract & Refractive Surgery 40, no. 4 (April 2014): 657–65. http://dx.doi.org/10.1016/j.jcrs.2014.01.027.

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12

Vaporciyan, Ara A. "Teaching and Learning Surgical Skill." Annals of Thoracic Surgery 101, no. 1 (January 2016): 12–14. http://dx.doi.org/10.1016/j.athoracsur.2015.11.037.

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13

Sato, Toshihiko. "Continuous improvement of surgical skill." Journal of Thoracic Disease 11, S9 (May 2019): S1186—S1187. http://dx.doi.org/10.21037/jtd.2019.03.88.

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14

Lee, Dongheon, Hyeong Won Yu, Hyungju Kwon, Hyoun-Joong Kong, Kyu Eun Lee, and Hee Chan Kim. "Evaluation of Surgical Skills during Robotic Surgery by Deep Learning-Based Multiple Surgical Instrument Tracking in Training and Actual Operations." Journal of Clinical Medicine 9, no. 6 (June 23, 2020): 1964. http://dx.doi.org/10.3390/jcm9061964.

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As the number of robotic surgery procedures has increased, so has the importance of evaluating surgical skills in these techniques. It is difficult, however, to automatically and quantitatively evaluate surgical skills during robotic surgery, as these skills are primarily associated with the movement of surgical instruments. This study proposes a deep learning-based surgical instrument tracking algorithm to evaluate surgeons’ skills in performing procedures by robotic surgery. This method overcame two main drawbacks: occlusion and maintenance of the identity of the surgical instruments. In addition, surgical skill prediction models were developed using motion metrics calculated from the motion of the instruments. The tracking method was applied to 54 video segments and evaluated by root mean squared error (RMSE), area under the curve (AUC), and Pearson correlation analysis. The RMSE was 3.52 mm, the AUC of 1 mm, 2 mm, and 5 mm were 0.7, 0.78, and 0.86, respectively, and Pearson’s correlation coefficients were 0.9 on the x-axis and 0.87 on the y-axis. The surgical skill prediction models showed an accuracy of 83% with Objective Structured Assessment of Technical Skill (OSATS) and Global Evaluative Assessment of Robotic Surgery (GEARS). The proposed method was able to track instruments during robotic surgery, suggesting that the current method of surgical skill assessment by surgeons can be replaced by the proposed automatic and quantitative evaluation method.

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15

Kasula, Jayasree, and Kodandapani Yerroju. "Skill of donning surgical gloves amongst residents: a neglected skill." International Surgery Journal 6, no. 9 (August 28, 2019): 3142. http://dx.doi.org/10.18203/2349-2902.isj20193593.

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Background: Sepsis is a preventable cause of morbidity and mortality. Sepsis causes approximately 1 million new-born deaths annually. The global prevalence of maternal sepsis is 4.4% causing more than 5.7 million cases and one tenth of maternal deaths annually. Skin preparation, shaving and wound closure were some factors involved in surgical site infections. But the technique of wearing gloves in a sterile way has not received enough attention. Hence this cross sectional observational study was undertaken to assess the awareness and proficiency in this technique among the residents.Methods: 104 post graduate students from the departments of General Surgery, Obstetrics and Gynaecology, Paediatrics and Anaesthesiology from two medical colleges were administered a questionnaire and also were observed one at a time with a checklist in an OSCE station. Study was conducted in several sessions over a period of 2 months.Results: None of them were formally taught this technique. 36 (34.56%) were informally taught by seniors. 7 (6.72%) tore the glove while wearing. 39 (37.44%) put two fingers in one finger space. 42 (40.32%) touched bare skin with gloved hands while wearing. 54 (51.84%) touched bare skin with used surface of the glove while removing.Conclusions: Awareness about technique and skill of donning sterile gloves among residents of various specialities are not satisfactory. It is recommended to teach this skill as soon as the students enter medical school in a strict and formal way and monitor their proficiency throughout their training period.

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16

Mills, James T., Helen Y. Hougen, Daniel Bitner, Tracey L. Krupski, and Noah S. Schenkman. "Does Robotic Surgical Simulator Performance Correlate With Surgical Skill?" Journal of Surgical Education 74, no. 6 (November 2017): 1052–56. http://dx.doi.org/10.1016/j.jsurg.2017.05.011.

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17

Smith, S., J. Torkington, N. Taffinder, and A. Darzi. "The objective assessment of surgical skill." Minimally Invasive Therapy & Allied Technologies 9, no. 5 (January 2000): 315–19. http://dx.doi.org/10.3109/13645700009061452.

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18

Kanehira, Eiji. "Who assesses your surgical skill? How?" Minimally Invasive Therapy & Allied Technologies 19, no. 1 (January 23, 2010): 1. http://dx.doi.org/10.3109/13645700903516544.

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19

Azari, David, Caprice Greenberg, Carla Pugh, Douglas Wiegmann, and Robert Radwin. "In Search of Characterizing Surgical Skill." Journal of Surgical Education 76, no. 5 (September 2019): 1348–63. http://dx.doi.org/10.1016/j.jsurg.2019.02.010.

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20

Tseng, YaWei, Ira Papel, and S. Swaroop Vedula. "Daytime Sleepiness and Surgical Skill—Reply." JAMA Facial Plastic Surgery 21, no. 4 (July 2019): 344. http://dx.doi.org/10.1001/jamafacial.2018.2043.

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21

Wong, Jaime A., and Edward D. Matsumoto. "Primer: cognitive motor learning for teaching surgical skill—how are surgical skills taught and assessed?" Nature Clinical Practice Urology 5, no. 1 (January 2008): 47–54. http://dx.doi.org/10.1038/ncpuro0991.

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22

Black, Peter C. "Time to Start Measuring Surgical Skill? Commentary on: Surgical Skill and Complication Rates After Bariatric Surgery." Urology 83, no. 6 (June 2014): 1223–24. http://dx.doi.org/10.1016/j.urology.2014.01.045.

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23

De Witte, Benjamin, Franck Di Rienzo, Xavier Martin, Ye Haixia, Christian Collet, and Nady Hoyek. "Implementing Cognitive Training Into a Surgical Skill Course: A Pilot Study on Laparoscopic Suturing and Knot Tying." Surgical Innovation 25, no. 6 (September 15, 2018): 625–35. http://dx.doi.org/10.1177/1553350618800148.

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Mini-invasive surgery—for example, laparoscopy—has challenged surgeons’ skills by extending their usual haptic space and displaying indirect visual feedback through a screen. This may require new mental abilities, including spatial orientation and mental representation. This study aimed to test the effect of cognitive training based on motor imagery (MI) and action observation (AO) on surgical skills. A total of 28 postgraduate residents in surgery took part in our study and were randomly distributed into 1 of the 3 following groups: (1) the basic surgical skill, which is a short 2-day laparoscopic course + MI + AO group; (2) the basic surgical skill group; and (3) the control group. The MI + AO group underwent additional cognitive training, whereas the basic surgical skill group performed neutral activity during the same time. The laparoscopic suturing and knot tying performance as well as spatial ability and mental workload were assessed before and after the training period. We did not observe an effect of cognitive training on the laparoscopic performance. However, the basic surgical skill group significantly improved spatial orientation performance and rated lower mental workload, whereas the 2 others exhibited lower performance in a mental rotation test. Thus, actual and cognitive training pooled together during a short training period elicited too high a strain, thus limiting potential improvements. Because MI and AO already showed positive outcomes on surgical skills, this issue may, thus, be mitigated according to our specific learning conditions. Distributed learning may possibly better divide and share the strain associated with new surgical skills learning.

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24

Bonrath, Esther M., Nicolas J. Dedy, Lauren E. Gordon, and Teodor P. Grantcharov. "Comprehensive Surgical Coaching Enhances Surgical Skill in the Operating Room." Annals of Surgery 262, no. 2 (August 2015): 205–12. http://dx.doi.org/10.1097/sla.0000000000001214.

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25

Kumar, Suren, Narges Ahmidi, Greg Hager, Pankaj Singhal, Jason Corso, and Venkat Krovi. "Surgical Performance Assessment." Mechanical Engineering 137, no. 09 (September 1, 2015): S7—S10. http://dx.doi.org/10.1115/1.2015-sep-7.

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This article focuses on human skill understanding in the context of surgical assessment and training which has enormous and immediate application potential to enhance healthcare delivery. Surgical procedural performance involves interplay of a highly dynamic system of inter-coupled perceptual, sensory, and cognitive components. Computer-Integrated Surgery systems are a quintessential part of modern surgical workflow owing to developments in miniaturization, sensors and computation. Robotic Minimally Invasive Surgery, and the engendered computer-integration, offers unique opportunities for quantitative computer-based surgical-performance evaluation. The skill evaluation metrics as discussed need a variety of sensory data that limits the application to very specific robotic devices. The ability to couple quantitative, validated and stable metrics for surgical performance would lead to improvements in assessment and subsequently, training methods. Cognitive assessment can now be extended to also include sensorimotor assessment, with capacity to monitor and track skill across time.

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26

Topalli, Damla, and Nergiz Ercil Cagiltay. "Classification of Intermediate and Novice Surgeons’ Skill Assessment Through Performance Metrics." Surgical Innovation 26, no. 5 (June 6, 2019): 621–29. http://dx.doi.org/10.1177/1553350619853112.

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Background. Endoscopic surgeries have become an alternative for open procedures whenever possible. For such types of operations, surgeons are required to gain several skills, whose development needs hands-on practice. Accordingly, gaining these skills today is a challenge for surgical education programs. Despite the development of several technology-enhanced training environments, there are still problems to better integrate these technologies into educational programs. For an appropriate integration, it is critical to assess the skill levels and adapt the training content according to the trainees’ requirements. In the literature, there exist several methods for assessing these skill levels. However, there are still problems in practice for objective and repetitive assessment. Methods. The present study aims to estimate the skill levels of participants in surgical training programs in an objective manner by collecting experimental data from residents in an endoscopic surgical simulation environment and gathering performance metrics. Results. It is shown that, by comparing the results of a number of classification algorithms for the best accuracy estimation and feature set, the “novice” and “intermediate” skill levels can be estimated with an accuracy of 86%. Conclusions. The outcomes help surgical educators and instructional system designers to better assess the skill levels of the trainees and guide them accordingly. In addition, objective assessments as highlighted in this study can be beneficial when designing technology-enhanced adaptive learning environments.

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27

Cauraugh, James H., Marcel Martin, and Karen Komer Martin. "Modeling surgical expertise for motor skill acquisition." American Journal of Surgery 177, no. 4 (April 1999): 331–36. http://dx.doi.org/10.1016/s0002-9610(99)00057-4.

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28

McElnay, Philip. "Surgical skill: is it nature versus nurture?" Clinical Teacher 11, no. 6 (September 11, 2014): 442–43. http://dx.doi.org/10.1111/tct.12134.

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29

Koehler, Ryan J., Simon Amsdell, Elizabeth A. Arendt, Leslie J. Bisson, Jonathan P. Bramen, Aaron Butler, Andrew J. Cosgarea, et al. "The Arthroscopic Surgical Skill Evaluation Tool (ASSET)." American Journal of Sports Medicine 41, no. 6 (April 2, 2013): 1229–37. http://dx.doi.org/10.1177/0363546513483535.

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30

Stephens, Elizabeth H., and Joseph A. Dearani. "Commentary: Surgical skill assessment: Time to examine?" Journal of Thoracic and Cardiovascular Surgery 160, no. 1 (July 2020): 242–43. http://dx.doi.org/10.1016/j.jtcvs.2020.01.004.

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31

Huffman, Elizabeth, Nicholas Anton, John Martin, Lava Timsina, Walter Dearing, Benjamin Breece, Ian Mann, and Dimitrios Stefanidis. "Optimizing Assessment of Surgical Knot Tying Skill." Journal of Surgical Education 77, no. 6 (November 2020): 1577–82. http://dx.doi.org/10.1016/j.jsurg.2020.05.004.

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32

Singapogu, Ravikiran B., Lindsay O. Long, Dane E. Smith, Timothy C. Burg, Christopher C. Pagano, Varun V. Prabhu, and Karen J. L. Burg. "Simulator-Based Assessment of Haptic Surgical Skill." Surgical Innovation 22, no. 2 (July 22, 2014): 183–88. http://dx.doi.org/10.1177/1553350614537119.

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33

Kennedy, Ann-Marie, Sean Carroll, Oscar Traynor, and Anthony G. Gallagher. "Assessing Surgical Skill Using Bench Station Models." Plastic and Reconstructive Surgery 121, no. 5 (May 2008): 1869–70. http://dx.doi.org/10.1097/prs.0b013e31816b19bc.

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34

Khan, Mansoor S., Simon D. Bann, Ara W. Darzi, and Peter E. M. Butler. "Assessing Surgical Skill Using Bench Station Models." Plastic and Reconstructive Surgery 120, no. 3 (September 2007): 793–800. http://dx.doi.org/10.1097/01.prs.0000271072.48594.fe.

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35

Byrnes, Kevin Gerard, and David Edward Kearney. "Assessment of Surgical Skill and Performance Variability." JAMA Surgery 155, no. 12 (December 1, 2020): 1175. http://dx.doi.org/10.1001/jamasurg.2020.3781.

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36

Saleh, George M. "Objective Structured Assessment of Cataract Surgical Skill." Archives of Ophthalmology 125, no. 3 (March 1, 2007): 363. http://dx.doi.org/10.1001/archopht.125.3.363.

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37

Shah, J., D. Buckley, J. Frisby, and A. Darzi. "Reaction time does not predict surgical skill." British Journal of Surgery 90, no. 10 (2003): 1285–86. http://dx.doi.org/10.1002/bjs.4180.

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38

Panait, Lucian, Azhar Rafiq, Ahmed Mohamed, Charles Doarn, and Ronald C. Merrell. "Surgical Skill Facilitation in Videoscopic Open Surgery." Journal of Laparoendoscopic & Advanced Surgical Techniques 13, no. 6 (December 2003): 387–95. http://dx.doi.org/10.1089/109264203322656469.

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39

Zia, Aneeq, and Irfan Essa. "Automated surgical skill assessment in RMIS training." International Journal of Computer Assisted Radiology and Surgery 13, no. 5 (March 16, 2018): 731–39. http://dx.doi.org/10.1007/s11548-018-1735-5.

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40

Chen, J., M. Yeasin, and R. Sharma. "Visual modelling and evaluation of surgical skill." Pattern Analysis & Applications 6, no. 1 (April 22, 2003): 1–11. http://dx.doi.org/10.1007/s10044-002-0165-7.

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41

Stansfield, Tim, and N. Tai. "Surgical skill decay in the contingency era." BMJ Military Health 167, no. 5 (September 27, 2021): 300–301. http://dx.doi.org/10.1136/bmjmilitary-2021-001921.

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42

Davies, Nigel, Francine Alexander, and Mike Larvin. "Simulation in surgical training: the College's role." Bulletin of the Royal College of Surgeons of England 93, no. 9 (October 1, 2011): 318–19. http://dx.doi.org/10.1308/147363511x13135061294969.

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Traditionally, surgeons learned all of the complex knowledge, skills and judgement necessary to practise safe surgery over many years, during real procedures involving real patients. Trainees no longer spend many years under the close supervision of an expert surgeon, nor is it acceptable for trainees to acquire a skill on a patient without prior practice.

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43

Koch, Frances A. "Nursing Management: An Experiential/Skill Building Workbook." AORN Journal 49, no. 3 (March 1989): 902–4. http://dx.doi.org/10.1016/s0001-2092(07)66718-0.

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44

Shanks, Gail D. "OR Nurse Day: Skill and Compassion Combine." AORN Journal 48, no. 4 (October 1988): 740–41. http://dx.doi.org/10.1016/s0001-2092(07)69129-7.

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45

Arora, C., A. Menzies, ES Han, M. Lee, JHJ Kim, and AP Advincula. "Surgical Skills Across the Spectrum: Comparing Surgical Skill Based on Surgical Experience Using a Standardized, High-Fidelity Total Laparoscopic Hysterectomy Model." Journal of Minimally Invasive Gynecology 26, no. 7 (November 2019): S76—S77. http://dx.doi.org/10.1016/j.jmig.2019.09.697.

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46

Lin, Lawrence O., and Larry H. Hollier. "Review of “Comprehensive Surgical Coaching Enhances Surgical Skill in the Operating Room." Journal of Craniofacial Surgery 26, no. 8 (November 2015): 2430. http://dx.doi.org/10.1097/scs.0000000000002258.

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47

De Groote, R., S. Puliatti, M. Amato, E. Mazzone, G. Rosiello, R. Farinha, A. Paludo, et al. "Is surgical skill related to surgical discipline? Results of the PROVESA trial." European Urology Open Science 21 (November 2020): S33—S34. http://dx.doi.org/10.1016/s2666-1683(20)35872-9.

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48

Alzahrani, Tarek, Richard Haddad, Abdullah Alkhayal, Josee Delisle, Laura Drudi, Walter Gotlieb, Shannon Fraser, et al. "Validation of the da Vinci Surgical Skill Simulator across three surgical disciplines." Canadian Urological Association Journal 7, no. 7-8 (July 2, 2013): 520. http://dx.doi.org/10.5489/cuaj.419.

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Objective: In this paper, we evaluate face, content and construct validity of the da Vinci Surgical Skills Simulator (dVSSS) across 3 surgical disciplines.Methods: In total, 48 participants from urology, gynecology and general surgery participated in the study as novices (0 robotic cases performed), intermediates (1-74) or experts (≥75). Each participant completed 9 tasks (Peg board level 2, match board level 2, needle targeting, ring and rail level 2, dots and needles level 1, suture sponge level 2, energy dissection level 1, ring walk level 3 and tubes). The Mimic Technologies software scored each task from 0 (worst) to 100 (best) using several predetermined metrics. Face and content validity were evaluated by a questionnaire administered after task completion. Wilcoxon test was used to perform pairwise comparisons.Results: The expert group comprised of 6 attending surgeons. The intermediate group included 4 attending surgeons, 3 fellows and 5 residents. The novices included 1 attending surgeon, 1 fellow, 13 residents, 13 medical students and 2 research assistants. The median number of robotic cases performed by experts and intermediates were 250 and 9, respectively. The median overall realistic score (face validity) was 8/10. Experts rated the usefulness of the simulator as a training tool for residents (content validity) as 8.5/10. For construct validity, experts outperformed novices in all 9 tasks (p < 0.05). Intermediates outperformed novices in 7 of 9 tasks (p < 0.05); there were no significant differences in the energy dissection and ring walk tasks. Finally, experts scored significantly better than intermediates in only 3 of 9 tasks (matchboard, dots and needles and energy dissection) (p < 0.05).Conclusions: This study confirms the face, content and construct validities of the dVSSS across urology, gynecology and general surgery. Larger sample size and more complex tasks are needed to further differentiate intermediates from experts.

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49

Whitfield, Nicholas. "Surgical Skills Beyond Scientific Management." Medical History 59, no. 3 (June 19, 2015): 421–42. http://dx.doi.org/10.1017/mdh.2015.28.

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During the Great War, the French surgeon Alexis Carrel, in collaboration with the English chemist Henry Dakin, devised an antiseptic treatment for infected wounds. This paper focuses on Carrel’s attempt to standardise knowledge of infected wounds and their treatment, and looks closely at the vision of surgical skill he espoused and its difference from those associated with the doctrines of scientific management. Examining contemporary claims that the Carrel–Dakin method increased rather than diminished demands on surgical work, this paper further shows how debates about antiseptic wound treatment opened up a critical space for considering the nature of skill as a vital dynamic in surgical innovation and practice.

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50

Rathod, Surekha, Dhanashree Ghoderao, Vrinda Kolte, and Nilima Budhraja. "Simulation-based surgical skill training in internship program." SRM Journal of Research in Dental Sciences 10, no. 3 (2019): 135. http://dx.doi.org/10.4103/srmjrds.srmjrds_45_19.

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