An Array of Factors Influence Robotics Adoption in Lower Urinary Tract Reconstruction.

Abstract

IntroductionUrology has been a leader in the adoption of robotic technologies, with robotic prostatectomies far surpassing an open approach in the United States. However, this widespread adoption has not extended to lower urinary tract reconstruction (LUTR) such as neobladder creation and bladder augmentation. This study aims to identify factors that influence robotics adoption in these procedures from the perspectives of a wide range of stakeholders.MethodsSemi-structured, qualitative interviews were conducted as part of the National Science Foundation Innovation Corps (NSF I-Corps) entrepreneurship program. Analysis of transcribed notes was completed by six reviewers using a modified framework method. Each theme and subtheme was categorized as a driver or barrier to robotics adoption, and the strength of each factor was calculated via skew (the sum of the rating values divided by the total number of instances it was mentioned).ResultsOf 101 interviews, 84 discussed robotics in lower urinary tract reconstruction comprising 28 urologists, 16 device representatives, 22 administrators, 7 patients, 5 researchers, and 6 referring physicians. 21 subthemes were identified across 5 major themes. The three primary drivers of adoption of robotics were outcomes, competition across hospital systems, and complications, while the top three barriers were patient factors/comorbidities, perceived learning curve, and operative time.DiscussionWhile understanding traditional outcome measures remains critical, market dynamics, training requirements, and procedural challenges are additional core elements that affect robotics adoption in LUTR. Addressing these barriers through early training, advancements in device development (eg, reducing anastomotic complexity), and enhanced institutional support models (eg, OR time, dedicated robotic staff) to optimize operative availability can accelerate impactful innovation and integration of robotics into LUTR.