Background Clinical decision support systems (CDSSs) have shown promise in improving diagnosis in primary care, particularly for chronic diseases. The SATURN (Smart Physician Portal for Patients With Unclear Disease) project developed a CDSS prototype for primary care in Germany that uses artificial intelligence to reduce diagnostic uncertainty in unclear and rare diseases. It generates recommendations based on clinical data from university hospitals stored in a standardized common data model. However, integrating primary care data in Germany remains challenging due to the use of country-specific vocabularies and heterogeneous data structures. Therefore, integration of medical concepts into general practitioners’ user interfaces (UIs) and improved workflow design is needed. Objective This study investigates how the UI of a CDSS for primary care should be designed to facilitate the user-friendly entry of medical concepts. Methods A structured, iterative user-centered design process of five steps was applied: (1) conceptualization, including analysis of requirements and objectives, (2) implementation of the CDSS UI, (3) analysis of user and expert feedback, (4) workshop with experts in the primary care electronic health record system, and (5) development of an extended concept for the system UI. Results This study identified requirements and options for supporting data entry in the UI of a CDSS for primary care, thus providing a framework for future implementation and prototype development. Usability testing revealed the need to refine input support, particularly the language used to make the system easy for general practitioners to use. Further effort is required to map this. In addition, we have identified a system interface to electronic patient records in primary care as essential for the system. Conclusions This paper demonstrates how standardized medical terminologies can be integrated into a CDSS UI for primary care. The user-centered design approach has been effective in developing CDSS UIs that align with clinicians’ workflows and provide a user-friendly experience. Although the current technical infrastructure presents significant challenges when connecting to primary care electronic health record systems, collaborating with experts enabled us to identify potential interface solutions. Overall, the results indicate a need for optimized physician language input support and interoperability, including standardized data entry, automated tools, and artificial intelligence–based approaches to enhance data quality and usability.
Neff et al. (Fri,) studied this question.