Joanne Greenhalgh

University of Leeds

Papers

7

Total Citations

313

H-Index

7

About

Joanne Greenhalgh is a leading health services researcher whose work sits at the intersection of surgical innovation, implementation science, and healthcare teamwork. She has made substantial contributions to understanding how robotic and robot-assisted surgery (RAS) becomes embedded within clinical practice, examining not just technical dimensions but the complex human and organizational factors that shape successful adoption. Greenhalgh is particularly recognized for her pioneering application of realist evaluation methodology to surgical contexts, using it to unpack the mechanisms by which RAS affects communication, collaboration, and decision-making within operating theatre teams. Her research has illuminated the unintended consequences of physical separation between surgeon and team, offering critical insights for healthcare providers navigating the rapid uptake of surgical robotics. With her most-cited works accumulating nearly 300 citations collectively, her influence on both implementation science and surgical practice research is clear. Beyond individual studies, Greenhalgh has helped establish a rigorous theoretical framework for evaluating complex healthcare technologies, most notably through her development and application of Context-Mechanism-Outcome configurations. Her empirical investigations of shifting divisions of labour in surgical teams provide valuable guidance for institutions seeking to integrate advanced surgical technologies safely and effectively.

Research Focus

Key Achievements

7
H-Index
7
Papers
313
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
Embedding robotic surgery into routine practice and impacts on communication and decision making: a review of the experience of surgical teams
68 citations · 2016
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: University of Leeds

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago