Background: The primary objective of the DELIVER-CARE study was to evaluate a generic model for the delegation of clinical tasks to medical practice assistants (MPAs) in the outpatient treatment of chronic inflammatory diseases in the form of an MPA consultation. In addition to proving that the model is not inferior to standard care, permanent implementation also requires a positive evaluation by those involved and knowledge of the barriers and success factors. Therefore, the aim of this study was to investigate the perspectives of those involved from the specialist fields of rheumatology, gastroenterology, and dermatology on the delegation of medical activities to MPAs and to identify both success factors and barriers to transferring the model to standard care. The focus here will be on the experience of setting up and running an MPA consultation.
Material and methods: Qualitative, semi-structured guided interviews were conducted with doctors, medical assistants and patients in the fields of rheumatology, gastroenterology, and dermatology (convenience sample). Qualitative content analysis of interview transcripts was used.
Results: In 2022, 61 interviews were conducted with physicians (n = 21), medical assistants (n = 18), and patients (n = 22). In addition to the general willingness expressed by the majority of participants to continue using the delegation or MPA consultation model, aspects from the following areas were identified: (1) goals and motives for participating, (2) the participants' experiences with the intervention as well as current barriers to and challenges of long-term implementation. In summary, the interviewees were mostly pleased with the model and saw advantages, such as easing the workload of doctors, appreciating the work of medical assistants, and improving patient care). However, lack of a funding concept and general staffing conditions (fluctuation, lack of specialist staff) have made it difficult to implement the model.
Discussion: Considering the shortage of medical resources, MPA visits can be a key element in the transformation of outpatient care. However, further research and discussion is needed to specify the delegation model before it can be permanently integrated into standard care (i. e., regarding the mandatory face-to-face encounter between doctors and patients, remuneration for services, and the competency framework for medical assistants).
With the increasing availability of powerful large language models (LLMs), the use of artificial intelligence (AI) in qualitative research is gaining growing attention. This article critically examines the potential and limitations of such systems along key research steps, such as category development, coding, and interpretation. Drawing on our own experiences and recent studies, we discuss both functional benefits and methodological, ethical, and data protection-related challenges. The findings suggest that AI-based systems can be meaningfully employed as complementary tools for reflection - for example, to generate alternative perspectives or serve as a second or third opinion in individual projects. At the same time, it becomes evident that the core principles of qualitative research cannot be automated. We therefore advocate for a research-driven, critically reflective use of AI, grounded in methodological rigor, ethical responsibility, and ongoing scholarly discourse.

