gms | German Medical Science

Introduction: Clinical trials are fundamental to evidence-based medicine [1]. Challenges such as insufficient participant numbers can compromise their significance and validity [2]. To this end, clinical trials are often conducted within healthcare settings to identify and enroll patients into a trial in the context of clinical care [3]. Digital systems present an opportunity to enhance trial recruitment by leveraging patient data from clinical care and facilitating automated participant identification [4]. The aim of this study is therefore to understand the data flow in clinical documentation practice and the recruitment strategies currently used. By examining these aspects, starting points for the integration of IT systems into the recruitment process through digital solutions will be identified and discussed.

Methods: Semi-structured expert interviews were conducted across various specialist departments at University Hospital Erlangen using a developed interview guide. Ten employees specializing in clinical trials were interviewed to gather insights into the structures and processes within their medical departments. In the first part of the interview, information on documentation practices throughout the treatment process was recorded on paper and used to develop process models of clinical treatment using BPMN, which were validated by interviewees. The second section, focusing on recruitment process, was recorded and transcribed. The content was classified using Mayring’s qualitative content analysis [5] and analyzed with MAXQDA software.

Results: The analysis of the clinical care processes surveyed showed a heterogeneous use of documentation systems. In addition, the documented patient data is available in a mixture of structured and unstructured elements. Study information is mainly shared within the specialist staff in departments, mostly through team meetings (8/10), e-mails (5/10) and personal contact (2/10). Study registers (3/10) serve as an additional source of information. Common recruitment strategies include the manual search of study personnel in documentation systems, team meetings/tumor conferences and the identification of potentially suitable patients by medical staff during outpatient appointments. Out of the 10 surveyed clinics, all reported that trial recruitment is currently conducted manually without the use of digital solutions. Six experts see screening and filtering functions as helpful in identifying patients with the required inclusion and exclusion criteria, and half of the experts interviewed also recommend implementing functions such as alerts and automatic notifications.

Discussion: Insufficient structuring of clinical patient data and the fragmentation of documentation systems make it difficult for study personnel to identify suitable patients. Furthermore, successful integration of IT systems necessitates transparency regarding existing system design, data architecture and the recruitment processes [3]. In addition, communication with clinical staff is crucial to enable smooth integration and to obtain valuable feedback for the further development of the systems.

Conclusion: Effective IT-supported recruitment design requires analyzing recruitment processes and clinical structures. By addressing challenges like improving data quality and completeness and integrating digital solutions into clinical systems - features such as filtering, screening tools and automatic notification functionalities - healthcare institutions can enhance recruitment processes. This ultimately contributes to the advancement of evidence-based medicine by leveraging technology and ensuring better data structure and completeness.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.