Artificial Intelligence (AI) Application Implementation In Radiology: Impediments And Enablers

Abstract

The aim of this study was to determine the obstacles and enablers related to the adoption of artificial intelligence (AI) in clinical radiology within the Netherlands.

Materials and techniques: An exploratory, qualitative research design was used with an embedded multiple case study. 24 semi-structured interviews from seven Dutch hospitals made up the data collection process. The Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework for new medical technologies in healthcare organizations was recently published, and it served as a guide for the analysis of barriers and facilitators. Implementation processes must be carried out in an organized way in order to provide evidence of the clinical added value of AI applications and help improve the quality and effectiveness of clinical radiology.