Real-time monitoring of drug-laboratory test interactions with an automated decision support application

J. van Balveren, W. Verboeket-Van de Venne, L. Erdem-Eraslan, A. de Graaf, R. Musson, W. Oosterhuis, I. van der Sijs, R. Verheul, R. Kusters, R. Hoedemakers

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Background-aim: The lack of knowledge of the presence of Drug-Laboratory Test Interactions (DLTIs) can cause misinterpretation of laboratory test results and delayed or erroneous diagnosis with extra healthcare costs and even harm to patients. There are over 50.000 physiological and/or analytical drug-test interactions described. In this pilot study, an automated decision support application was used to detect drug laboratory test interactions in real-time.

Methods: In this multicentre study, 34 clinical rules about DLTI were programmed and validated in an automated decision support application (Gaston, Medecs B.V.). The DLTIs were described in a validated database from the Dutch Society for Clinical Chemistry. The application is able to generate a DLTI-based advisory text based on predefined aberrant laboratory test results and medication data from individual patients and present this alert text to the laboratory specialist in the laboratory information system. The software application was successfully connected and installed in one hospital laboratory in 2018 with two other hospitals to follow in 2019. Generated real-time DLTI alerts were collected and monitored during 4 weeks.

Results: A mean of 45 DLTI alerts were generated per day. Twenty-one out of 34 clinical rules were generated at least once in this period. The most frequently reported interactions were magnesium - proton pump inhibitors (14%), creatine kinase – statins (13%) and potassium - ACE-inhibitors (13%). Most DLTI alerts were from the internal medicine department (43%), cardiology department (22%) and the emergency department (10%).

Conclusions: In this study, an automated decision support application was implemented to facilitate signalling the presence of drug laboratory test interactions. A mean of 45 DLTI alerts per day were generated in this study. The clinical relevance of the alerts for laboratory specialists and physicians will be examined.
Original languageEnglish
Pages (from-to)S531-S532
JournalClinica Chimica Acta
Issue numberSuppl. 1
Publication statusPublished - Jun 2019
Event23rd IFCC-EFLM European Congress of Clinical Chemistry and Laboratory Medicine, EuroMedLab 2019 - Barcelona, Spain
Duration: 19 May 201923 May 2019
Conference number: 23


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