Alan Pearman

University of Leeds

Papers

7

Total Citations

313

H-Index

7

About

Alan Pearman is a prominent researcher whose work sits at the intersection of surgical innovation, healthcare implementation science, and organizational behavior. His scholarship has made substantial contributions to understanding how robot-assisted surgery (RAS) is integrated into clinical practice, with particular focus on its effects on teamwork, communication, and decision-making within operating theatre environments. Pearman's most influential body of work employs realist evaluation methodology to unpack the complex contextual factors that shape whether and how surgical robots become embedded in routine practice. His 2016 review (68 citations) and 2017 process evaluation (47 citations) stand as foundational texts examining how physical separation between surgeon and team during robotic procedures reshapes professional relationships and collaborative dynamics. His 2019 interview study (58 citations) further illuminated the stakeholder-level theories governing successful implementation, offering actionable insights for healthcare organizations navigating technology adoption. Beyond documenting challenges, Pearman's work investigates emerging divisions of labour within surgical teams and the mechanisms through which experience shapes those changes. Collectively accumulating over 310 citations, his research provides an indispensable evidence base for clinicians, hospital administrators, and policymakers seeking to maximize the safe and effective adoption of robotic surgical technologies.

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 · 13 days ago