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Maestre JM, Rojo E, Del Moral I. Future directions for simulation in healthcare: A critical review. J Healthc Qual Res 2024; 39:120-125. [PMID: 38176996 DOI: 10.1016/j.jhqr.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/01/2023] [Accepted: 12/08/2023] [Indexed: 01/06/2024]
Abstract
There was a widespread discontinuation of simulation programs during and after the COVID-19 pandemic. The objective is to explore how to facilitate greater integration of simulation in healthcare organizations. A literature review was conducted in PubMed, MEDES, IBECS and DOCUMED databases. Twenty-three articles published after the pandemic were selected, categorized in seven themes and critically reviewed. In order to consistently and fully integrate simulation into the organizational culture it is recommended to prioritize the development of new strategies that enhance the efficiency and safety of healthcare delivery. And also strategies that enhance the satisfaction and well-being of all stakeholders.
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Affiliation(s)
- Jose M Maestre
- Hospital Virtual Valdecilla, Avda. de Valdecilla s/n, 39008 Santander, Spain.
| | - Elena Rojo
- Hospital Virtual Valdecilla, Avda. de Valdecilla s/n, 39008 Santander, Spain
| | - Ignacio Del Moral
- Hospital Virtual Valdecilla, Avda. de Valdecilla s/n, 39008 Santander, Spain
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2
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Ryder CY, Mott NM, Gross CL, Anidi C, Shigut L, Bidwell SS, Kim E, Zhao Y, Ngam BN, Snell MJ, Yu BJ, Forczmanski P, Rooney DM, Jeffcoach DR, Kim GJ. Using Artificial Intelligence to Gauge Competency on a Novel Laparoscopic Training System. J Surg Educ 2024; 81:267-274. [PMID: 38160118 DOI: 10.1016/j.jsurg.2023.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/08/2023] [Accepted: 10/13/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Laparoscopic surgical skill assessment and machine learning are often inaccessible to low-and-middle-income countries (LMIC). Our team developed a low-cost laparoscopic training system to teach and assess psychomotor skills required in laparoscopic salpingostomy in LMICs. We performed video review using AI to assess global surgical techniques. The objective of this study was to assess the validity of artificial intelligence (AI) generated scoring measures of laparoscopic simulation videos by comparing the accuracy of AI results to human-generated scores. DESIGN Seventy-four surgical simulation videos were collected and graded by human participants using a modified OSATS (Objective Structured Assessment of Technical Skills). The videos were then analyzed via AI using 3 different time and distance-based calculations of the laparoscopic instruments including path length, dimensionless jerk, and standard deviation of tool position. Predicted scores were generated using 5-fold cross validation and K-Nearest-Neighbors to train classifiers. SETTING Surgical novices and experts from a variety of hospitals in Ethiopia, Cameroon, Kenya, and the United States contributed 74 laparoscopic salpingostomy simulation videos. RESULTS Complete accuracy of AI compared to human assessment ranged from 65-77%. There were no statistical differences in rank mean scores for 3 domains, Flow of Operation, Respect for Tissue, and Economy of Motion, while there were significant differences in ratings for Instrument Handling, Overall Performance, and the total summed score of all 5 domains (Summed). Estimated effect sizes were all less than 0.11, indicating very small practical effect. Estimated intraclass correlation coefficient (ICC) of Summed was 0.72 indicating moderate correlation between AI and Human scores. CONCLUSIONS Video review using AI technology of global characteristics was similar to that of human review in our laparoscopic training system. Machine learning may help fill an educational gap in LMICs where direct apprenticeship may not be feasible.
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Affiliation(s)
| | - Nicole M Mott
- University of Michigan Medical School, Ann Arbor, Michigan
| | | | - Chioma Anidi
- University of Michigan Medical School, Ann Arbor, Michigan
| | - Leul Shigut
- Department of Surgery, Soddo Christian General Hospital, Soddo, Ethiopia
| | | | - Erin Kim
- University of Michigan Medical School, Ann Arbor, Michigan
| | - Yimeng Zhao
- University of Michigan Medical School, Ann Arbor, Michigan
| | | | - Mark J Snell
- Department of Surgery, Mbingo Baptist Hospital, Mbingo, Cameroon
| | - B Joon Yu
- Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Pawel Forczmanski
- Department of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, Szczecin, Poland
| | - Deborah M Rooney
- Department of Learning Sciences, University of Michigan, Ann Arbor, Michigan
| | - David R Jeffcoach
- Department of Surgery, Community Regional Medical Center, Fresno, California
| | - Grace J Kim
- Department of Surgery, University of Michigan, Ann Arbor, Michigan.
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Jaraczewski TJ, SenthilKumar G, Ramamurthi A, Nimmer K, Yang X, Kothari AN. Teaming with artificial intelligence to support global cancer surgical care. J Surg Oncol 2023; 128:943-946. [PMID: 37818910 DOI: 10.1002/jso.27442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 09/02/2023] [Indexed: 10/13/2023]
Affiliation(s)
- Taylor J Jaraczewski
- Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Gopika SenthilKumar
- Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Department of Physiology and Anesthesiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Adhitya Ramamurthi
- Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Kaitlyn Nimmer
- Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Xin Yang
- Clinical and Translational Science Institute of Southeast Wisconsin, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Anai N Kothari
- Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Clinical and Translational Science Institute of Southeast Wisconsin, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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de Marinis R, Marigi EM, Atwan Y, Yang L, Oeding JF, Gupta P, Pareek A, Sanchez-Sotelo J, Sperling JW. Current clinical applications of artificial intelligence in shoulder surgery: what the busy shoulder surgeon needs to know and what's coming next. JSES Rev Rep Tech 2023; 3:447-453. [PMID: 37928999 PMCID: PMC10625013 DOI: 10.1016/j.xrrt.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
Background Artificial intelligence (AI) is a continuously expanding field with the potential to transform a variety of industries-including health care-by providing automation, efficiency, precision, accuracy, and decision-making support for simple and complex tasks. Basic knowledge of the key features as well as limitations of AI is paramount to understand current developments in this field and to successfully apply them to shoulder surgery. The purpose of the present review is to provide an overview of AI within orthopedics and shoulder surgery exploring current and forthcoming AI applications. Methods PubMed and Scopus databases were searched to provide a narrative review of the most relevant literature on AI applications in shoulder surgery. Results Despite the enormous clinical and research potential of AI, orthopedic surgery has been a relatively late adopter of AI technologies. Image evaluation, surgical planning, aiding decision-making, and facilitating patient evaluations over time are some of the current areas of development with enormous opportunities to improve surgical practice, research, and education. Furthermore, the advancement of AI-driven strategies has the potential to create a more efficient medical system that may reduce the overall cost of delivering and implementing quality health care for patients with shoulder pathology. Conclusion AI is an expanding field with the potential for broad clinical and research applications in orthopedic surgery. Many challenges still need to be addressed to fully leverage the potential of AI to clinical practice and research such as privacy issues, data ownership, and external validation of the proposed models.
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Affiliation(s)
- Rodrigo de Marinis
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
- Department of Orthopedic Surgery, Pontificia Universidad Católica de Chile, Santiago, Chile
- Shoulder and Elbow Unit, Hospital Dr. Sótero del Rio, Santiago, Chile
| | - Erick M. Marigi
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Yousif Atwan
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Linjun Yang
- Orthopedic Surgery Artificial Intelligence Lab (OSAIL), Mayo Clinic, Rochester, MN, USA
| | - Jacob F. Oeding
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Puneet Gupta
- Department of Orthopaedic Surgery, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Ayoosh Pareek
- Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY, USA
| | | | - John W. Sperling
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA
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Varas J, Coronel BV, Villagrán I, Escalona G, Hernandez R, Schuit G, Durán V, Lagos-Villaseca A, Jarry C, Neyem A, Achurra P. Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM). Rev Col Bras Cir 2023; 50:e20233605. [PMID: 37646729 PMCID: PMC10508667 DOI: 10.1590/0100-6991e-20233605-en] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/14/2023] [Indexed: 09/01/2023] Open
Abstract
The landscape of surgical training is rapidly evolving with the advent of artificial intelligence (AI) and its integration into education and simulation. This manuscript aims to explore the potential applications and benefits of AI-assisted surgical training, particularly the use of large language models (LLMs), in enhancing communication, personalizing feedback, and promoting skill development. We discuss the advancements in simulation-based training, AI-driven assessment tools, video-based assessment systems, virtual reality (VR) and augmented reality (AR) platforms, and the potential role of LLMs in the transcription, translation, and summarization of feedback. Despite the promising opportunities presented by AI integration, several challenges must be addressed, including accuracy and reliability, ethical and privacy concerns, bias in AI models, integration with existing training systems, and training and adoption of AI-assisted tools. By proactively addressing these challenges and harnessing the potential of AI, the future of surgical training may be reshaped to provide a more comprehensive, safe, and effective learning experience for trainees, ultimately leading to better patient outcomes. .
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Affiliation(s)
- Julian Varas
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
| | - Brandon Valencia Coronel
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
| | - Ignacio Villagrán
- - Pontificia Universidad Católica de Chile, Carrera de Kinesiología, Departamento de Ciencias de la Salud, Facultad de Medicina - Santiago - Región Metropolitana - Chile
| | - Gabriel Escalona
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
| | - Rocio Hernandez
- - Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile
| | - Gregory Schuit
- - Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile
| | - Valentina Durán
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
| | - Antonia Lagos-Villaseca
- - Pontificia Universidad Católica de Chile, Department of Otolaryngology - Santiago - Región Metropolitana - Chile
| | - Cristian Jarry
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
| | - Andres Neyem
- - Pontificia Universidad Católica de Chile, Computer Science Department, School of Engineering - Santiago - Región Metropolitana - Chile
| | - Pablo Achurra
- - Pontificia Universidad Católica de Chile, Experimental Surgery and Simulation Center, Department of Digestive Surgery - Santiago - Región Metropolitana - Chile
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Rasic G, Parikh PP, Wang ML, Keric N, Jung HS, Ferguson BD, Altieri MS, Nahmias J. The silver lining of the pandemic in surgical education: virtual surgical education and recommendations for best practices. Global Surg Educ 2023; 2:59. [PMID: 38013862 PMCID: PMC10205563 DOI: 10.1007/s44186-023-00137-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 05/04/2023] [Accepted: 05/14/2023] [Indexed: 11/29/2023]
Abstract
Virtual education is an evolving field within the realm of surgical training. Since the onset of the COVID-19 pandemic, the application of virtual technologies in surgical education has undergone significant exploration and advancement. While originally developed to supplement in-person curricula for the development of clinical decision-making, virtual surgical education has expanded into the realms of clinical decision-making, surgical, and non-surgical skills acquisition. This manuscript aims to discuss the various applications of virtual surgical education as well as the advantages and disadvantages associated with each education modality, while offering recommendations on best practices and future directions.
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Affiliation(s)
- Gordana Rasic
- Department of Surgery, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA USA
| | - Priti P. Parikh
- Department of Surgery, Boonshoft School of Medicine, Wright State University, Dayton, OH USA
| | - Ming-Li Wang
- Department of Surgery, University of New Mexico, Albuquerque, NM USA
| | - Natasha Keric
- Division of Trauma, Acute Care Surgery, and Surgical Critical Care, Department of Surgery, Banner-University Medical Center Phoenix, University of Arizona College of Medicine, Phoenix, AZ USA
| | - Hee Soo Jung
- Division of Acute Care and Regional General Surgery, Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI USA
| | - Benjamin D. Ferguson
- Division of Hepatopancreatobiliary Surgery, Department of Surgery, University of New Mexico, Albuquerque, NM USA
| | - Maria S. Altieri
- Division of Gastrointestinal Surgery, Department of Surgery, Pennsylvania Hospital, Penn Medicine, Philadelphia, PA USA
| | - Jeffry Nahmias
- Division of Trauma, Burns, and Surgical Critical Care, Department of Surgery, University of California Irvine, Orange, CA USA
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