Aim To analyze geographical variation in use of glucose-lowering drugs (GLDs) for type-2 diabetes (T2DM) in Denmark. Methods We included all adults who filled a prescription for a non-insulin GLD indicated for T2DM from 2010 to 2023 in Denmark. Stratified by each of the five regions, we calculated the annual incidence rate, the annual prevalence proportion, and the total volume of dispensed GLDs from 2010 to 2023. We calculated the proportion of incident prescriptions for GLDs that was issued by different prescriber types and characterized non-insulin GLD users in each region in 2023. Finally, we analyzed variation at the municipal level. Results Totally, data from 478,118 adults were included. In all regions, general practitioners were the main prescribers of GLDs. There were minor regional differences in the use of GLDs with a predominant and increasing use of metformin, accelerating use of SGLT-2is and GLP-1RAs, and declining use of SUs over time. There were some differences in characteristics of GLD users across regions with a slightly higher prevalence of diabetes-related complications and larger involvement of hospital physicians in the Capital Region compared to the other regions. We identified four municipality clusters that differed marginally in the prescribing pattern of non-insulin GLD. Conclusion The small differences in use of GLDs indicate equal access to GLDs across Denmark. Differences at the municipal level calls for future studies to investigate if these reflect differences in clinical practice or differences in T2DM populations.

Purpose The use of common data models (CDMs) is increasing, however, the complexity of many CDM frameworks constitute a barrier for their use. For many local and collaborative use cases, simpler CDMs can suffice. Here, we propose the EpiCore CDM, a simple CDM framework for use in Scandinavian pharmacoepidemiological studies. Methods The EpiCore CDM was developed based on a set of guiding principles. It should (i) be accessible to users without needing advanced technical expertise or extensive infrastructure, (ii) accommodate the most common elements of typical data sources in the field and region, while allowing easy customization for specific use cases, (iii) prioritize syntactic harmonization of data and defer clinical concept mapping to the analytical phase, (iv) be useable in both collaborative and single site settings, and (v) include support for quality control procedures. Results The EpiCore CDM comprise two mandatory administrative tables (person and observation), six optional event tables (diagnosis, procedure, encounter, drug, primcare and cancer) and three optional lookup tables (drug_info, organisation_info and prescriber_info). Each table, along with its columns and constraints is specified according to a CDM specification template. This facilitates easy customization while providing detailed documentation. Its use is supported by an R-package called EpiCoreAssistant, which also provides quality control tools for testing compliance of a CDM instance with the agreed CDM specification. A step-by-step description is presented, demonstrating the steps involved in a typical CDM-based collaborative pharmacoepidemiologic study. Conclusions We present the EpiCore CDM, a specification template and an R package that offers a simple framework for improved workflows, standardizations and collaboration, focused on Scandinavian pharmacoepidemiological studies and with relevance for a broad palette of register-based health care researchers.

In pharmacoepidemiological analysis, one covariate that might act as a confounder is the type of prescriber issuing a prescription. The type of prescriber typically fulfills the criteria for confounding, as it is associated both with the exposure (e.g., prescriber types may differ in their choice of first-line treatment) and with the outcome (as different types of prescribers often treat patients with different disease severity). Additionally, the type of prescriber may correlate with other factors such as treatment adherence, surveillance, or coding practices. While information on the type of prescriber is often available to researchers, it is rarely employed to control for confounding in pharmacoepidemiological analyses. In an applied example, we conducted a cohort study using Danish healthcare registers from 2011 to 2018 to assess the risk of ischemic stroke associated with the use of direct oral anticoagulants (DOACs) compared to warfarin. We found a hazard ratio (HR) of 0.95 (95% CI: 0.90-1.01) for DOACs versus warfarin when adjusting only for age and sex. Further adjustment for prescriber type showed an effect of similar magnitude (HR 0.93; 95% CI: 0.87-0.98). However, in stratified analyses, we observed higher estimates in the group of general practitioners (HR 1.06; 95% CI: 0.94-1.2) compared to hospital prescribers (HR 0.88; 95% CI: 0.82-0.95), indicating potential effect modification. This highlights the potential value of prescriber type as an important covariate in pharmacoepidemiological analyses. Further research is needed to fully establish the importance of prescriber type in such analyses.

Purpose To describe utilization patterns, characteristics of users and prescriber responsibility of the new oral antiviral medication, molnupiravir, indicated for mild-to-moderate COVID-19. Methods Using nationwide registries, we identified all Danish adults who filled a prescription for molnupiravir from December 16 th, 2021, to August 31 st, 2022. We described weekly incidence rates and patient characteristics over time, prescriber responsibility as well as time between molnupiravir initiation and a positive SARs-CoV-2 test. Patient characteristics were compared to an untreated SARS-CoV-2 positive cohort. Results By August 31 st, 2022, 5,847 individuals had filled a prescription for molnupiravir. The incidence rate gradually increased to 2,000 weekly prescriptions per 100,000 RT-PCR SARS-CoV-2 positives. Users of molnupiravir were most often men (55% vs. 45% women). The majority (81%) had a positive RT-PCR SARS-CoV-2 test and few (2.9%) redeemed molnupiravir outside the recommended window of 5 days from the positive test result. Compared to an untreated SARS-CoV-2 positive cohort, users of molnupiravir had a median age of 74 years vs. 44 years, a higher proportion resided in a nursing home (12% vs. 1.1%) and had a higher number of comorbidities (median of 3 vs. 0); most commonly hypertension (38%), chronic lung disease (35%), diabetes (20%) and mood disorders (20%). General practitioners were the primary prescribers of molnupiravir (91%). Conclusions Molnupiravir was mainly prescribed by general practitioners to RT-PCR SARS-CoV-2 positive individuals who had a potentially increased risk of severe COVID-19. Though some off-label prescribing occurred, our study indicates a high level of adherence to contemporary guidelines.