Real-world drug use in ATC and ICD-10: an expert-curated drug–diagnosis resource based on UK primary care and Danish hospitalization electronic health records
Year: 2026
Type: preprint
Abstract: ABSTRACT As the use of electronic health records in drug repositioning research increases, so does the need for a well-curated resource describing real-world drug-diagnosis relationships. This need is particularly important in the context of polypharmacy. Although literature-based drug-disease maps exist, they are typically based on mechanistic disease ontologies, which are not widely used in clinical settings and do not align well with the ICD system, which is most often used in healthcare. Here, we used real-world primary and secondary healthcare data from approximately 1.5 million individuals to identify drug-diagnosis co-occurrences ( 736,000 pairs), significant associations (7,763 pairs), and assess direct drug usage through medical expert curation. The final resource comprises 7,763 associations with odds ratios > 3.5, manually annotated by six independent clinicians (3 in the UK and 3 in Denmark). Finally, the clinician annotations were scored using an Expectation-Maximization-based framework providing a confidence score for each pair. Our resource shows that the vast majority of significantly associated drugs and diagnoses in healthcare records are not due to direct treatment of the diagnosis. Additionally, through the annotation results, we demonstrate the importance of accounting for systematic differences among annotators when working with real-world data.
Source: medRxiv
Institutions: University of Copenhagen, Novo Nordisk Foundation, University of Oxford, University College London, Copenhagen University Hospital, Gentofte Hospital, Rigshospitalet, University College London Hospitals NHS Foundation Trust, King's College London, National and Kapodistrian University of Athens, British Heart Foundation, Interdisciplinary Transformation University Austria
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Wellcome Trust
OpenAlex ID: W7212077971
