Barriers and enablers to the effective implementation of robotic assisted surgery

Implementation of Robotic Assisted Surgery (RAS) is complex as it requires adjustments to associated physical infrastructure, but also changes to processes and behaviours. With the global objective of optimising and improving RAS implementation, this study aimed to: 1) Explore the barriers and enablers to RAS service adoption, incorporating an assessment of behavioural influences; 2) Provide an optimised plan for effective RAS implementation, with the incorporation of theory-informed implementation strategies that have been adapted to address the barriers/enablers that affect RAS service adoption.

Semi-structured interviews were conducted with RAS personnel and stakeholders, including: surgeons, theatre staff, managers, industry representatives, and policy-makers/commissioners. The Theoretical Domains Framework (TDF) and the Consolidated Framework for Implementation Research (CFIR) was used to identify barriers and enablers that represent individual behaviours, capabilities, attitudes, beliefs, and external organisational factors that influence the implementation of RAS.

Findings suggest that implementation planning has three separate phases-pre-, early, and late implementation. For pre-implementation, barriers and enablers identified included the cost of RAS equipment and issues of economic viability, weak outcome evidence for RAS, a preponderance of an eminence driven model, the clinician/manager relationship, and views around the uptake and expansion of RAS in the future. Early implementation findings revealed role changes for theatre personnel and an enhanced team approach, reliance on industry for training provision, and changes in skill sets and attentional processes. Late implementation factors included equipment maintenance costs, technological limitations, changes to cognition during RAS routine use, and benefits to institutions/healthcare professionals (such as ergonomic improvement).

Together, findings suggest the factors that affect RAS implementation are multi-faceted and change across the life-cycle of intervention adoption. Theory-informed strategies are suggested which can optimise implementation of RAS. Optimisation strategies need planning from the outset.