Karen Chang

Tufts University, Good Samaritan Medical Center

Papers

15

Total Citations

312

H-Index

12

About

Karen Chang is a prominent surgical researcher whose work has significantly advanced the field of robotic hernia repair, with a particular focus on minimally invasive abdominal wall reconstruction. Her research portfolio spans critical dimensions of robotic ventral hernia repair (RVHR), including comparative surgical techniques, learning curve analysis, and outcomes across diverse patient populations. Chang's most impactful contributions include rigorous evaluations of prosthetic reinforcement strategies in RVHR and pioneering investigation into emergent robotic repair of incarcerated hernias — an area previously lacking evidence. Her repeated application of cumulative sum (CUSUM) methodology across multiple repair techniques, including robotic Rives-Stoppa, rTAPP, and intraperitoneal onlay mesh approaches, has provided surgeons with structured frameworks for understanding skill acquisition and procedural mastery. Her work on hybrid robotic transversus abdominis release (TAR) and propensity score matching analyses comparing transabdominal versus extraperitoneal approaches further demonstrates her commitment to evidence-based technique refinement. With over 265 cumulative citations across her top ten papers — all published within a remarkably narrow two-year window — Chang has established herself as a leading voice in robotic surgery outcomes research. Her findings offer meaningful guidance for surgeons adopting robotic platforms and for institutions developing structured hernia repair training programs.

Research Focus

Key Achievements

12
H-Index
15
Papers
312
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Robotic Ventral Hernia Repair
39 citations · 2021
📈 Most Prolific Year: 2020 (12 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Tufts University, Good Samaritan Medical Center

Top Papers

  1. 1
    Robotic Ventral Hernia Repair
    39 citations · 2021
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago