Background: Polypharmacy in older people is steadily increasing and a combination of many medicines may result in adverse effects, especially if the medicines interact pharmacodynamically. Examples are additive or synergistic effects increasing the risk of falls, haemorrhage, serotonin syndrome and torsade de pointes. The clinical decision support system Janusmed Risk Profile has been developed to find such risks based on a patients' medication list.
View Article and Find Full Text PDFJanusmed Renal Function is a clinical decision support system (CDSS) that provides evidence-based dosage recommendations for adult patients with renal impairment. Dosage recommendations are presented for each drug/active substance in relation to four stages of chronic kidney disease (CKD). In addition, substances that are nephrotoxic are labelled with a warning.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2021
Background: Data-driven process analysis is an important area that relies on software support. Process variant analysis is a sort of analysis technique in which analysts compare executed process variants, a.k.
View Article and Find Full Text PDFJanusmed interactions is a drug-drug interactions (DDI) database available online for healthcare professionals (HCP) at all levels of the healthcare system including pharmacies. The database is aimed at HCP but is also open to the public for free, for those individuals who register for a personal account. The aim of this study was to investigate why and how patients use the database Janusmed interactions, how they perceive content and usability, and how they would react if they found an interaction.
View Article and Find Full Text PDFStud Health Technol Inform
August 2019
Janusmed is a clinical decision support system, developed by the Stockholm County Council that supports physicians in identifying drug-drug interactions. To determine how Janusmed is used in and affects the clinical practice, an evaluation study is currently being carried out that analyzes multiple data sources through descriptive statistics. The study focuses on how Janusmed affects the behavior of the physicians, in particular, to what extent physicians reconsider their prescription decisions based on warnings from Janusmed.
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