Tokgöz Pinar, Hafner Jessica, Dockweiler Christoph
Department für Digitale Gesundheitswissenschaften und Biomedizin; Professur für Digital Public Health, Universität Siegen Fakultät V Lebenswissenschaftliche Fakultät, Germany.
Gesundheitswesen. 2023 Dec;85(12):1220-1228. doi: 10.1055/a-2098-3108. Epub 2023 Jul 14.
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.
基于人工智能的决策支持系统可能会优化医院的抗生素处方并防止抗菌药物耐药性的发展。本研究的目的是从卫生专业人员的角度确定成功实施的阻碍因素和促进因素。
对在医院工作的卫生专业人员进行以问题为中心的个人访谈。数据评估基于根据库卡茨进行的结构化定性内容分析。
卫生专业人员的态度按照人-组织-技术适配模型呈现。技术和组织主题是系统实施的最重要因素。特别是,与现有系统的兼容性和用户友好性被认为在成功实施中起主要作用。此外,对潜在用户的培训和组织的技术设备被认为是必不可少的。最后,强调了长期提升潜在用户技术技能以及建立对系统益处的信任的重要性。
所确定的因素为下一步确定需求和态度的优先级及量化提供了基础。很明显,除了技术因素外,关注特定背景和用户相关条件对于确保长期成功实施和系统信任至关重要。