Falisha Kanji
Papers
11
Total Citations
186
H-Index
7
About
Falisha Kanji is an emerging researcher specializing in human factors, systems engineering, and patient safety within the context of robotic-assisted surgery (RAS). Her work addresses the complex interplay between surgical technology, team performance, and operating room design, making her a distinctive voice in surgical safety research. Kanji's most cited work, "Human Factors Integration in Robotic Surgery" (2022, 50 citations), establishes her as a leading contributor to understanding how evidence-based systems thinking can improve the integration of advanced technologies in clinical environments. Her investigations into workflow disruptions, docking barriers, and the influence of room size on surgical flow reveal a meticulous attention to the real-world demands faced by surgical teams. With over 185 cumulative citations across her portfolio, her research has meaningfully shaped how institutions approach RAS implementation and team training. Notably, Kanji pioneered a creative gamified training initiative — the "Robotic-Assisted Surgery Olympics" — demonstrating her commitment to innovative, engaging solutions for skill development in high-stakes environments. Her body of work offers students and practitioners a rigorous yet practical framework for rethinking surgical safety in the era of robotic medicine.
Research Focus
Key Achievements
Top Papers
- 1Human Factors Integration in Robotic Surgery50 citations · 2022
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- 3Barriers to safety and efficiency in robotic surgery docking27 citations · 2021
- 4Room Size Influences Flow in Robotic-Assisted Surgery24 citations · 2021
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- 10Robotic Assisted Surgery: The Gap Between Challenges And Solutions2 citations · 2020