Implementation of artificial intelligence-based decision support systems for antibiotic prescribing in hospitals: a Delphi study

Abstract

Introduction: Numerous initiatives against antimicrobial resistance have been initiated in recent years. Decision support systems (DSSs) based on artificial intelligence (AI) provide new opportunities for automating antibiotic therapy in hospitals. While AI-based DSSs may improve antimicrobial use and patient outcomes and reduce healthcare costs, the challenges associated with their implementation, optimization, and adoption cannot be ignored. Methods: A Delphi study was conducted to investigate factors influencing the implementation of AI-based DSSs in the hospital setting. Results: The study included 36 experts with perspectives on the hospital setting and DSS development. A consensus was reached on the importance of 34 factors and the ranking as well as assessment of current realization of implementation factors revealed important starting points for implementation strategies. Discussion: The study results indicate that whilst there are multiple factors of importance in DSS implementation, some factors, as e.g., promoting application- and user-orientated development of DSSs, establishing user-friendly organizational structures, and fulfilling demands of trust, transparency, and responsibility through sensitization and education on organizational but also legal level should gain more attention. In addition, two factors did not reach a consensus in terms of importance, indicating that it may not be practical to consider all factors of importance when implementing AI-based DSSs in the hospital setting.

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