Aiqin Chen

Sun Yat-sen University

Papers

2

Total Citations

14

H-Index

2

About

Aiqin Chen is a researcher specializing in the sterilization, disinfection, and quality management of advanced surgical instrumentation, with a particular focus on da Vinci robotic surgical systems. Her work addresses a critically underexplored area in surgical practice: the safe and effective reprocessing of complex, high-precision robotic instruments used in minimally invasive procedures. Chen's most notable contributions include a multicenter comparative study evaluating three non-destructive methods for assessing the cleanliness of da Vinci robotic instruments, offering practical guidance for healthcare professionals navigating the challenges of robotic equipment maintenance. Complementing this, her cross-sectional survey examining the current landscape of cleaning, disinfection, and sterilization practices across Chinese healthcare institutions has shed important light on systemic gaps and standardization needs as robotic-assisted surgery rapidly expands in clinical settings. Both studies have each garnered 7 citations, reflecting growing interest from infection control specialists, surgical nurses, and hospital administrators seeking evidence-based protocols. Chen's research is particularly timely given the accelerating adoption of robotic surgery in China and globally, where instrument reprocessing errors can carry significant patient safety implications. Her work positions her as an emerging voice in surgical instrument management and healthcare quality assurance.

Research Focus

Key Achievements

2
H-Index
2
Papers
14
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Multicenter comparative study of three “non-destructive” methods of detecting the cleanliness of the da Vinci surgical robotic instrument
7 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Sun Yat-sen University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago