Data collection
UTI
Electronic health record systems in Germany are diverse and not standardised, therefore, an automated extraction of patient files was not feasible. Instead, a medical practice assistant in each practice was trained by the research team to follow a detailed, standardised procedure for data extraction (supplementary material S1) to identify cases (instances of UTI diagnosis) and prescribed antibiotics from the electronic medical record. Data extraction was carried out at the end of each quarter over a 12 month period (Q1-Q4) in the intervention group and after 12 months in the control group. We documented first, second, and third antibiotic prescription for each instance of UTI. Information about non-antibiotic treatments such as painkiller, phytotherapy, or no documented treatment was also collected. Baseline data (Qb) was collected retrospectively using the data of the first quarter of 2020, one year before the study start. All data were verified by the relevant GPs. Data validation was performed once in the first quarter in each intervention practice. Research nurses randomly selected 10% of the UTI cases (three to five patients per practice) and compared all information in the patient file with the extracted data (supplementary material S2). Any inconsistency was clarified through personal contact with the medical practice assistants or, if required, with the GP.All data were collected at practice level and transferred in an aggregated form each quarter to the coordinating study site. Data were extracted from the control practices 12 months after inclusion of the practice in the study. Data collection and analysis was unblinded.Female patients with a documented uncomplicated UTI were identified via ICD 10 German modification-2020 code (N30.0, N30.9, N39.0, R30.0, R30.9). The GP’s clinical diagnosis of UTI was accepted in keeping with the pragmatic nature of the trial.