128 Chapter 5 systems, with a focus on nurses, highlights key barriers to address. These include inadequate computer skills, limited access to information and a lack of awareness of AI availability, insufficient flexibility, and concerns about trust and credibility [22, 35]. Additional determinants derived from clinical practice were contributed by the project team. Based on the identified determinants, the project team – comprising nurse champions and nurse managers – selected thirteen implementation strategies using the Expert Recommendations for Implementing Change (ERIC) taxonomy [36, 37]. Choosing these strategies was based on the expected acceptability, feasibility, and potential impact on implementation success. These strategies, spanning six ERIC domains, were operationalized following the reporting guidelines of Proctor, Powell and McMillen [39] (see Supplemental file S1). The primary actors of most of the implementation strategies were members of the project team. Local implementation teams were established on each ward, consisting of nurse champions, senior nurses, and nurse managers. During team meetings, project team members explicitly outlined their intentions, expectations, and contributions to ensure successful implementation. Educational sessions were also organized to support the process. In the initial two weeks following DRAAI’s rollout on each ward, the project team actively participated in daily stand-up meetings. During these sessions, a project team member, a local implementation team member, or a nurse familiar with DRAAI introduced and explained the system to the rest of the team. After the initial rollout period, the project team continued to provide support, addressing technical questions and challenges throughout the pilot study. They maintained regular contact by visiting the wards weekly to address challenges, answer questions, and provide additional support as needed. The hypothesized mechanisms of change, represented in the third column of Figure 2, illustrate how implementation strategies can influence various implementation outcomes. For example, nurses with limited digital skills will likely benefit from local technical assistance, particularly in enhancing acceptance and feasibility. The project team brought together interdisciplinary expertise, including data scientists, a quality advisor with a nursing background, a PhD student specializing in implementation science with a nursing background, and a project manager. Notably, the researchers and developers of DRAAI were actively involved in the implementation process, contributing to the evaluation of the implementation process. Supervised by DS, this integration of the development and implementation teams proved advantageous for feasibility, as it allowed the developers to adapt the intervention (DRAAI) and implementation strategies during the pilot phase.
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