Evaluating Adoption Factors for Robotic-Assisted Surgery With the Analytical Hierarchical Process

Abstract

The objective of this master's dissertation is to evaluate adoption factors for robotic-assisted surgery (RAS) using the Analytical Hierarchy Process (AHP) as its evaluation methodology. Robotic-assisted surgery is used in various surgical fields. It is mainly used as a tool in numerous disciplines' minimally invasive surgery procedures (MIS). Since it has so many different application areas and actors, the determination of its adoption factors and evaluation process of these factors' priorities for surgeons is a highly complex issue that includes multicriteria of decision-making and numerous surgeons. A comprehensive list of these possible adoption factors recognized by conducting an extensive literature review, was picked and chosen. First, we had 310 factors mentioned in the literature that have a potential impact on the adoption process of the RAS. We have reduced these to 20 factors that are categorized under five different main criteria. By this, a unique AHP tree that is this thesis' contribution to the literature was developed. The research data was collected by an online survey from the surgeons of various disciplines working in Türkiye. Our final sample to evaluate priorities consisted of forty-one surgeon responses in total. The evaluation process consists of three steps: analyzing individual-based pairwise comparison matrices, their consistency rations, and their priority vectors. We executed the same workflow for the aggregated analysis for disciplined-based and all aggregation. Results are examined in detail and concluded with insightful interpretations. © 2024 PICMET.