146 Chapter 6 The aim of our current study was to combine and use large registries to help identify patient - and practice associated determinants of antimicrobial prescribing and cues for further improvement. Our approach was to follow the number and trends of antimicrobial prescriptions for primary care patients with an acute infection over a period of ten years. Methods Study design and setting In this observational study, we analysed antimicrobial prescriptions in primary care for appropriateness, based on a large set of routine healthcare data combined with socioeconomic data from Statistics Netherlands (SN) over a period of ten years. As the aim of the study was to examine trends in antimicrobial treatment of acute infections, prophylactic antimicrobial prescriptions with the intention to prevent infections (like recurrent urinary tract infections), were excluded. The potential determinants selected for analysis were derived from a previously conducted literature review (1). The study was approved by the Medical Ethical Review Committee of Leiden University Medical Centre (file number G20.020). Data collection through combining two large registries This study used pseudonymized routine healthcare data derived from a data registry covering EMR data from approximately 450,000 patients. Patient EMR data registered from 2012-2021 were extracted from 115 primary care practices affiliated with the Extramural LUMC Academic Network (ELAN), located in the Leiden-The Hague area of The Netherlands (the northern part of the province of South Holland). This network covers 2.6% of the general Dutch population, and previous studies have established that patient data from the network are well generalizable to the average Dutch population (11, 12). Primary care practices involved in the network provide continuous access to the pseudonymized EMR data of their practice population. An informed patient opt-out procedure concerning use of pseudonymized data for research and population health management is in place. Patients have been informed in writing about use of their pseudonymized data. The Medical Ethical Review Committee of the LUMC regards the opt-out procedure as written consent from patients. Using data from the ELAN data warehouse, the comorbidities (Supplement 1) and antimicrobial allergies of each patient were linked to each antimicrobial prescription. Statistics Netherlands (SN) hosts the other database, we were able to link data from both databases on a pseudonymized individual level. SN collects data on individual Dutch inhabitants both databases are
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