Mitchell G Goldenberg1, Jason Y Lee1, Jethro C C Kwong2, Teodor P Grantcharov3, Anthony Costello4. 1. Division of Urology, University of Toronto, Toronto, ON, Canada. 2. Faculty of Medicine, University of Toronto, Toronto, ON, Canada. 3. Division of General Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada. 4. Department of Surgery, Royal Melbourne Hospital, University of Melbourne, Melbourne, Vic, Australia.
Abstract
OBJECTIVES: To systematically review and synthesise the validity evidence supporting intraoperative and simulation-based assessments of technical skill in urological robot-assisted surgery (RAS), and make evidence-based recommendations for the implementation of these assessments in urological training. MATERIALS AND METHODS: A literature search of the Medline, PsycINFO and Embase databases was performed. Articles using technical skill and simulation-based assessments in RAS were abstracted. Only studies involving urology trainees or faculty were included in the final analysis. RESULTS: Multiple tools for the assessment of technical robotic skill have been published, with mixed sources of validity evidence to support their use. These evaluations have been used in both the ex vivo and in vivo settings. Performance evaluations range from global rating scales to psychometrics, and assessments are carried out through automation, expert analysts, and crowdsourcing. CONCLUSION: There have been rapid expansions in approaches to RAS technical skills assessment, both in simulated and clinical settings. Alternative approaches to assessment in RAS, such as crowdsourcing and psychometrics, remain under investigation. Evidence to support the use of these metrics in high-stakes decisions is likely insufficient at present.
OBJECTIVES: To systematically review and synthesise the validity evidence supporting intraoperative and simulation-based assessments of technical skill in urological robot-assisted surgery (RAS), and make evidence-based recommendations for the implementation of these assessments in urological training. MATERIALS AND METHODS: A literature search of the Medline, PsycINFO and Embase databases was performed. Articles using technical skill and simulation-based assessments in RAS were abstracted. Only studies involving urology trainees or faculty were included in the final analysis. RESULTS: Multiple tools for the assessment of technical robotic skill have been published, with mixed sources of validity evidence to support their use. These evaluations have been used in both the ex vivo and in vivo settings. Performance evaluations range from global rating scales to psychometrics, and assessments are carried out through automation, expert analysts, and crowdsourcing. CONCLUSION: There have been rapid expansions in approaches to RAS technical skills assessment, both in simulated and clinical settings. Alternative approaches to assessment in RAS, such as crowdsourcing and psychometrics, remain under investigation. Evidence to support the use of these metrics in high-stakes decisions is likely insufficient at present.
Authors: Iulia Andras; Elio Mazzone; Fijs W B van Leeuwen; Geert De Naeyer; Matthias N van Oosterom; Sergi Beato; Tessa Buckle; Shane O'Sullivan; Pim J van Leeuwen; Alexander Beulens; Nicolae Crisan; Frederiek D'Hondt; Peter Schatteman; Henk van Der Poel; Paolo Dell'Oglio; Alexandre Mottrie Journal: World J Urol Date: 2019-11-27 Impact factor: 4.226
Authors: A J W Beulens; Y A F Hashish; W M Brinkman; P Umari; S Puliatti; E L Koldewijn; A J M Hendrikx; J P van Basten; J J G van Merriënboer; H G Van der Poel; C H Bangma; C Wagner Journal: J Robot Surg Date: 2020-07-10
Authors: Alexander J W Beulens; Willem M Brinkman; Evert L Koldewijn; Ad J M Hendrikx; Jean Paul A van Basten; Jeroen J G van Merriënboer; Henk G Van der Poel; Chris H Bangma; Cordula Wagner Journal: Eur Urol Open Sci Date: 2020-07-03