Mapping Outcomes and Registries Used in Current Danish Pharmacoepidemiological Research

Purpose: There is an increasing need for national and international pharmacoepidemiological studies based on high-quality real -world data of which the Danish registries are a valuable source. In lack of a complete overview of which data are used to assess real -world drug safety and effectiveness outcomes, we aimed to map the outcomes, data sources, and the reporting of outcome quality in recent pharmacoepidemiological studies. Methods: We conducted a systematic mapping review of pharmacoepidemiological studies based on Danish registries investigating drug safety and/or effectiveness, published in the period 2018-2019, identified in PubMed and Scopus. Extraction included: Anatomical Therapeutic Chemical level 2 code for drug exposures, outcomes, outcome data sources, and quality of outcomes. Results: Of the 210 included studies, 96% used outcomes categorized as Clinical, 4% utilized outcomes categorized as Society-related, 5% used outcomes categorized as Healthcare cost and utilization, and 3% of the studies applied outcomes categorized as Patient-reported in which the percentages are not mutually exclusive. Diagnosis (66%) and Mortality (38%) were the two most utilized subcategories among those categorized as Clinical outcomes. Danish Health Data Authority and Statistics Denmark registries were the most reported outcome data sources (90%). Ninety-six studies (46%) reported one or more quality parameters related to their outcomes of interest with accuracy/validity being the most reported parameter (22%). Conclusion: The Danish registries support a wide range of outcomes. Across therapeutic areas, most studies investigate traditional clinical outcomes of disease and mortality based on data from a small number of available registries. In contrast, clinical and biochemical databases, despite potentially offering outcomes with high responsiveness, and the high-quality social and healthcare cost registries were rarely used as outcome data sources.