Expectations of general practitioners on a practice based research network in Germany- a qualitative study within the Bavarian Research Practice Network (BayFoNet).

BACKGROUND: Despite general practitioners' (GPs') key role in Germany`s primary health care, clinical research in general practice is scarce. Clinical research is mainly conducted at inpatient facilities, although their results are rarely transferable. German GPs have no extra time or funding for research, as well as limited research training. To support clinical research in German primary health care, practice-based research networks (PBRNs) are developed. As they will be based on an active involvement of GPs, we need more information on GPs` participation-readiness. The aim of this study was to explore facilitators and barriers to participation in the Bavarian Research Practice Network (BayFoNet) from the GPs`perspective before clinical trials will be performed. METHODS: We have performed semi-structured qualitative interviews with a purposive sample of 20 Bavarian GPs in 2022 under the application of the consolidated framework for implementation research (CFIR). Transcriptions were analysed according to Kuckartz` qualitative content analysis. The five domains of the CFIR framework served as initial deductive codes. RESULTS: N = 14 interviewees already agreed to participate in BayFoNet, whereas n = 6 interviewees opted not to participate in BayFoNet at the time of data collection. Main facilitators to conduct clinical research within BayFoNet were the motivation to contribute to evidence strength and quality in general practice, professional development and training of practice staff, as well as networking. Barriers for an active participation were bad experiences with previous clinical studies and lack of resources. CONCLUSIONS: PBRNS in Germany have to be promoted and the entire practice team has to be involved at an early stage of development. Professional training of general practice staff and a living network might enhance engagement. Participatory approaches could help to develop acceptable and feasible study designs. Furthermore, PBRNs should support patient recruitment and data collection in general practices and disseminate the results of their research projects regularly to maintain GPs` engagement. TRIAL REGISTRATION: DRKS00028805, NCT05667207.

Modelling Adverse Events with the TOP Phenotyping Framework.

The detection and prevention of medication-related health risks, such as medication-associated adverse events (AEs), is a major challenge in patient care. A systematic review on the incidence and nature of in-hospital AEs found that 9.2% of hospitalised patients suffer an AE, and approximately 43% of these AEs are considered to be preventable. Adverse events can be identified using algorithms that operate on electronic medical records (EMRs) and research databases. Such algorithms normally consist of structured filter criteria and rules to identify individuals with certain phenotypic traits, thus are referred to as phenotype algorithms. Many attempts have been made to create tools that support the development of algorithms and their application to EMRs. However, there are still gaps in terms of functionalities of such tools, such as standardised representation of algorithms and complex Boolean and temporal logic. In this work, we focus on the AE delirium, an acute brain disorder affecting mental status and attention, thus not trivial to operationalise in EMR data. We use this AE as an example to demonstrate the modelling process in our ontology-based framework (TOP Framework) for modelling and executing phenotype algorithms. The resulting semantically modelled delirium phenotype algorithm is independent of data structure, query languages and other technical aspects, and can be run on a variety of source systems in different institutions.

Process evaluation in practice based research networks: a study protocol for a mixed-methods implementation study.

INTRODUCTION: General practitioners often criticise clinical trials for their poor applicability in primary care, which may at least partially explain why their engagement in primary care research remains limited. In order to enhance primary care research, the German government has funded six regional practice based research networks (PBRNs). Within the Bavarian PBRN (BayFoNet), two cluster-randomised pilot trials will be conducted. This paper presents the protocol of the process evaluation accompanying both trials, which aims to explore relevance, feasibility, acceptability and credibility of clinical research in primary care from the perspectives of BayFoNet researchers, general practitioners, and patients. METHODS AND ANALYSIS: The BayFoNet will be established by recruiting general practices (GPs) as prospective research collaborators in two cluster randomised pilot trials. Research teams will provide training in good clinical practice, and support practices in patient recruitment, data collection and documentation. Our process evaluation explores barriers and facilitators in the set up of the BayFoNet PBRN and both cluster randomised pilot trials, under the application of the consolidated framework for implementation research and the theoretical domains framework. In a mixed-methods concept, we will use qualitative and quantitative approaches to evaluate both pilot cluster-randomised trials as well as the BayFoNet itself: focus groups with researchers, semi-structured interviews with general practitioners and questionnaires for patients participating in the pilot cluster-randomised trials at three different time points. ETHICS AND DISSEMINATION: Research ethical approval for this study was granted by the Ethics Committee of the Medical Department, Ludwig-Maximilians-University Munich (AZ 21-1135). Results will be published in international peer-reviewed journals and summaries will be provided to the funders of the study as well as other PBRNs, GP teams and patients. TRIAL REGISTRATION NUMBERS: DRKS00028805, NCT05667207.