James Bena
Papers
1
Total Citations
21
H-Index
1
About
James Bena is a distinguished biostatistician whose work bridges the gap between complex surgical innovation and rigorous quantitative analysis. His primary research focuses on the learning curves associated with adopting new surgical technologies, particularly in the field of stereoelectroencephalography (SEEG) for epilepsy treatment. Bena’s major contribution lies in developing statistical frameworks that allow surgeons to objectively evaluate their own performance and proficiency when integrating novel techniques into clinical practice. His most cited work, “Incorporating New Technology Into a Surgical Technique: The Learning Curve of a Single Surgeon’s Stereo-Electroencephalography Experience” (2019, 21 citations), provides a seminal model for how to quantitatively assess procedural mastery, moving beyond anecdotal experience to data-driven benchmarks. This paper has become a key reference for surgical teams seeking to safely implement advanced technologies. Through his collaborations at the Cleveland Clinic, Bena has helped shape evidence-based guidelines for surgical training and quality improvement, ensuring that patient outcomes remain paramount during periods of technical transition. His work continues to empower surgeons with the statistical tools needed to navigate the evolving landscape of modern medicine.
Research Focus
Key Achievements
Top Papers
- 1