Raymund Avenido
Papers
6
Total Citations
193
H-Index
4
About
Raymund Avenido is a clinical researcher and nursing professional specializing in robotic surgery optimization, operating room efficiency, and human factors engineering in perioperative care. His work sits at a compelling intersection of surgical technology and systems-based practice, addressing the real-world challenges that emerge when advanced robotic platforms enter complex clinical environments. Avenido's most influential contribution, "Safety, efficiency and learning curves in robotic surgery: a human factors analysis" (2015, 123 citations), established him as a leading voice in understanding how human performance shapes robotic surgical outcomes. Building on this foundation, he pioneered innovative approaches to reducing operating room turnover time — a critical hospital efficiency metric — including the creative application of a motor racing pit stop model to streamline robotic OR workflows, a study that has garnered 42 citations and captured widespread professional attention. Across his publication record, Avenido has consistently championed data-driven, systematic interventions to bridge the gap between perception and reality in OR performance. His more recent explorations into resident training effects on robotic operative times demonstrate a broadening research lens encompassing surgical education. With nearly 200 cumulative citations, his work meaningfully informs how healthcare institutions can safely and efficiently integrate robotic surgery into everyday practice.
Research Focus
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Top Papers
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