Table 3_Implementation of artificial intelligence-based decision support systems for antibiotic prescribing in hospitals: a Delphi study.docx

IntroductionNumerous 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.
MethodsA Delphi study was conducted to investigate factors influencing the implementation of AI-based DSSs in the hospital setting.
ResultsThe 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.
DiscussionThe 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.

【引言】近年来，针对抗菌药物耐药性（antimicrobial resistance）的多项防控举措已相继启动。基于人工智能（Artificial Intelligence, AI）的决策支持系统（Decision Support Systems, DSS）为医院内抗生素治疗的自动化提供了全新契机。尽管基于AI的DSS可优化抗菌药物使用、改善患者预后并降低医疗成本，但其落地、优化与推广过程中面临的挑战仍不容忽视。
【方法】本研究采用德尔菲法，探究医院场景下基于AI的DSS落地所涉及的影响因素。
【结果】本次研究共纳入36名兼具医院场景认知与DSS研发视角的专家。研究就34项影响因素的重要性达成共识，通过对各落地因素当前实现程度的排序与评估，明确了制定落地策略的核心切入点。
【讨论】研究结果显示，尽管DSS落地涉及诸多关键影响因素，但部分因素应获得更多关注，例如推动DSS面向应用与用户的研发、构建用户友好型组织结构，以及通过组织与法律层面的宣传教育，满足各方对信任、透明性与责任性的要求。此外，有2项因素的重要性未达成共识，这表明在医院场景中落地基于AI的DSS时，无需将所有关键因素全部纳入考量范畴。