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. 2022 Sep;88(9):4067-4079.
doi: 10.1111/bcp.15341. Epub 2022 Apr 12.

Similarity and consistency assessment of three major online drug-drug interaction resources

Elpida Kontsioti  1   2 , Simon Maskell  1 , Amina Bensalem  3 , Bhaskar Dutta  4 , Munir Pirmohamed  5
Affiliations

Similarity and consistency assessment of three major online drug-drug interaction resources

Elpida Kontsioti et al. Br J Clin Pharmacol. 2022 Sep.

Abstract

Aims: The aim of this study was to explore the level of agreement on drug-drug interaction (DDI) information listed in three major online drug information resources (DIRs) in terms of: (1) interacting drug pairs; (2) severity rating; (3) evidence rating; and (4) clinical management recommendations.

Methods: We extracted information from the British National Formulary (BNF), Thesaurus and Micromedex. Following drug name normalisation, we estimated the overlap of the DIRs in terms of DDI. We annotated clinical management recommendations either manually, where possible, or through application of a machine learning algorithm.

Results: The DIRs contained 51 481 (BNF), 38 037 (Thesaurus) and 65 446 (Micromedex) drug pairs involved in DDIs. The number of common DDIs across the three DIRs was 6970 (13.54% of BNF, 18.32% of Thesaurus and 10.65% of Micromedex). Micromedex and Thesaurus overall showed higher levels of similarity in their severity ratings, while the BNF agreed more with Micromedex on the critical severity ratings and with Thesaurus on the least significant ones. Evidence rating agreement between BNF and Micromedex was generally poor. Variation in clinical management recommendations was also identified, with some categories (i.e., Monitor and Adjust dose) showing higher levels of agreement compared to others (i.e., Use with caution, Wash-out, Modify administration).

Conclusions: There is considerable variation in the DDIs included in the examined DIRs, together with variability in categorisation of severity and clinical advice given. DDIs labelled as critical were more likely to appear in multiple DIRs. Such variability in information could have deleterious consequences for patient safety, and there is a need for harmonisation and standardisation.

Keywords: clinical decision support; clinical management of drug interactions; drug information; drug-drug interaction; drug-drug interaction software.

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Conflict of interest statement

E.K. receives a PhD studentship that is jointly funded by AstraZeneca and the EPSRC. She also worked on a fixed‐term employment contract for AstraZeneca when this article was prepared. A.B. is an employee of Ceva Santé Animale. M.P. has received partnership funding for the following: MRC Clinical Pharmacology Training Scheme (co‐funded by MRC and Roche, UCB, Eli Lilly and Novartis); and grant funding from Vistagen Therapeutics. He also has unrestricted educational grant support for the UK Pharmacogenetics and Stratified Medicine Network from Bristol‐Myers Squibb and UCB. He has developed an HLA genotyping panel with MC Diagnostics, but does not benefit financially from this. M.P. is part of the IMI Consortium ARDAT (www.ardat.org). B.D. was AstraZeneca's employee and shareholder when this article was prepared but has since ended his relationship with both. S.M. has no conflict of interest to declare.

Figures

FIGURE 1
FIGURE 1
Venn diagrams illustrating the intersections in terms of: (A) drug ingredients; (B) unique drug–drug interaction pairs included in the drug information resources; and (C) drug–drug interaction pairs included in the drug information resources only for the ingredient intersection subset. Each circle represents a drug information resource and their intersections show the number of ingredients/drug–drug interactions they share with each one of the other drug information resources
FIGURE 2
FIGURE 2
Pairwise comparison tables for the different drug–drug interaction severity levels. For tables (A)–(C), row labels contain the severity ratings of the drug information resource under consideration, while column labels represent the severity ratings of the remaining two drug information resources. A separate column has been added to include the numbers of unique drug–drug interactions missing from each of the other drug information resources. Each row contains the number of unique drug–drug interactions per severity rating of the drug information resource under consideration, subcategorised by the severity ratings of the other drug information resources. The numbers in parentheses represent the corresponding percentages of the various sets per severity rating of the drug information resource under consideration. Colour gradient shows the relative differences in the percentages mentioned among the various overlapping sets
FIGURE 3
FIGURE 3
Heatmap for evidence rating comparison between BNF and Micromedex, including counts and coverage rates
FIGURE 4
FIGURE 4
Venn diagrams of the overlap in clinical management advice relating to drug–drug interactions in the drug information resources
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