Factors influencing the implementation of AI-based decision support systems for antibiotic prescription in hospitals: a qualitative analysis from the perspective of health professionals

Abstract

Decision support systems based on artificial intelligence might optimize antibiotic prescribing in hospitals and prevent the development of antimicrobial resistance. The aim of this study was to identify impeding and facilitating factors for successful implementation from the perspective of health professionals. Problem-centered individual interviews were conducted with health professionals working in hospitals. Data evaluation was based on the structured qualitative content analysis according Kuckartz. Attitudes of health professionals were presented along the Human-Organization -Technology-fit model. Technological and organizational themes were the most important factors for system implementation. Especially, compatibility with existing systems and user-friendliness were seen to play a major role in successful implementation. Additionally, the training of potential users and the technical equipment of the organization were considered essential. Finally, the importance of promoting technical skills of potential users in the long term and creating trust in the benefits of the system were highlighted. The identified factors provide a basis for prioritizing and quantifying needs and attitudes in a next step. It becomes clear that, beside technological factors, attention to context-specific and user-related conditions are of fundamental importance to ensure successful implementation and system trust in the long term.