Digitalisation in healthcare: the future of surgical training
| dc.contributor.advisor | O'Reilly, Barry A. | |
| dc.contributor.author | Galvin, Daniel | en |
| dc.date.accessioned | 2024-10-09T09:26:08Z | |
| dc.date.available | 2024-10-09T09:26:08Z | |
| dc.date.issued | 2023 | en |
| dc.date.submitted | 2023 | |
| dc.description.abstract | Introduction The impact of digital technology and artificial intelligence (AI) has a daily impact on our lives. Healthcare as an industry is at the forefront of technological innovation. The application of novel technology to aid performance and enhance training in surgery is key. Challenges in surgical training owing to an increase in trainee numbers, a reduction in working hours, increase in complexity and variety of surgeries performed have become major issues in surgical education. The COVID-19 pandemic further compounded these concerns between 2020 and 2022 where there was significant disruption and reduction in elective surgical activity. Methods Five studies examining the challenges in surgical training in gynaecology and their potential solutions were designed. These comprised of a national cross-sectional trainee and trainer survey on the current challenges of surgical training in gynaecology and in training during the COVID-19 pandemic. Potential solutions examined were a trial of the application of artificial intelligence to the grading of surgical performance and two randomised controlled trails of the application of transcranial direct current stimulation (tDCS) to enhance surgical performance in laparoscopic and robotic surgery. Results Our results showed significant challenges in surgical training over the last decade with a significant reduction in trainee confidence and experience in operative gynaecology. The COVID-19 pandemic had a significant impact on operative volumes of both trainees and trainers. Trainees failed to increase their self-reported confidence in performing common gynaecology procedures over the pandemic period. AI grading of operative performance was shown to be a potential means of enhancing trainee feedback and reducing workload for trainers. tDCS was shown to decrease rates of excessive velocity events during novice laparoscopic training setting it out as a potential solution to maximise training opportunities. tDCS was not shown to enhance robotic surgical performance. Conclusion While the current training environment is challenging in operative gynaecology, potential solutions to augment and accelerate training exist. Further study is required to assess the best means of implementing these solutions to ensure continued access to high quality surgical training. | en |
| dc.description.status | Not peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Galvin, D. M. 2023. Digitalisation in healthcare: the future of surgical training. MD Thesis, University College Cork. | |
| dc.identifier.endpage | 208 | |
| dc.identifier.uri | https://hdl.handle.net/10468/16511 | |
| dc.language.iso | en | en |
| dc.publisher | University College Cork | en |
| dc.rights | © 2023, Daniel Galvin. | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Gynaecology | |
| dc.subject | Surgery | |
| dc.subject | Training | |
| dc.subject | Simulation | |
| dc.subject | Neurostimulation | |
| dc.title | Digitalisation in healthcare: the future of surgical training | en |
| dc.type | Doctoral thesis | |
| dc.type.qualificationlevel | Doctoral | en |
| dc.type.qualificationname | MD - Doctor of Medicine | en |
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