Literature DB >> 28224645

Clinical decision support systems differ in their ability to identify clinically relevant drug interactions of immunosuppressants in kidney transplant patients.

J Amkreutz1,2, A Koch2, L Buendgens2, C Trautwein2, A Eisert1.   

Abstract

WHAT IS KNOWN AND
OBJECTIVE: In kidney transplant patients, clinically relevant drug-drug interactions (DDIs) with immunosuppressants potentially lead to serious adverse drug events (ADEs). The aim of this study was (i) to show that five clinical decision support systems (CDSSs) differ in their ability to identify clinically relevant potential DDIs (pDDIs) of immunosuppressants in kidney transplant patients and (ii) to compare CDSSs in terms of their ability to identify clinically relevant pDDIs in this context.
METHODS: All pDDIs being possible between nine immunosuppressants and 234 comedication drugs were identified for 264 intensive care unit (ICU) kidney transplant patients from 1999 to 2010. For pDDI identification, five CDSSs were used: DRUG-REAX® , ID PHARMA CHECK® , Lexi-Interact, mediQ and Meona. PDDIs from high severity categories were defined as clinically relevant. Classification of pDDIs as clinically relevant/non-clinically relevant by a clinical pharmacist using Stockley's Drug Interactions was employed as benchmark. We analysed inter-rater agreement, sensitivity, specificity, positive predictive value and negative predictive value. RESULTS AND DISCUSSION: Clinical decision support systems generated a total of 759 pDDI alerts. A total of 240 pDDI alerts were in high severity categories. A total of 391 different pDDIs were identified. Only 5% (n = 35) of different pDDIs were identified by all CDSSs. A total of 49 pDDIs were classified as clinically relevant by clinical pharmacists' rating using Stockley's Drug Interactions. Meona (0·72) has the highest inter-rater agreement with the benchmark for clinically relevant pDDIs. ID PHARMA CHECK® and mediQ show highest sensitivities (0·74, respectively). Meona has the highest specificity (0·99) and positive predictive value (0·89). WHAT IS NEW AND
CONCLUSION: Five CDSSs differ in their ability to identify clinically relevant pDDIs of immunosuppressants in kidney transplant patients. Data may assist in selecting CDSSs for kidney transplant patients in the ICU. Using CDSSs to identify clinically relevant pDDIs could prevent ADEs and contribute to the overall goal of avoiding patient harm and increasing patient safety.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  computerized decision support; drug-drug interactions; evidence-based pharmacotherapy; polypharmacy; renal transplantation

Mesh:

Substances:

Year:  2017        PMID: 28224645     DOI: 10.1111/jcpt.12508

Source DB:  PubMed          Journal:  J Clin Pharm Ther        ISSN: 0269-4727            Impact factor:   2.512


  6 in total

1.  Prevalence and nature of potential drug-drug interactions among kidney transplant patients in a German intensive care unit.

Authors:  Julia Amkreutz; Alexander Koch; Lukas Buendgens; Anja Muehlfeld; Christian Trautwein; Albrecht Eisert
Journal:  Int J Clin Pharm       Date:  2017-08-19

2.  Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study.

Authors:  Ramzi Shawahna
Journal:  BMC Med Inform Decis Mak       Date:  2019-11-08       Impact factor: 2.796

3.  Real clinical impact of drug-drug interactions of immunosuppressants in transplant patients.

Authors:  Ana Isabel Gago-Sánchez; Pilar Font; Manuel Cárdenas; María Dolores Aumente; José Ramón Del Prado; Miguel Ángel Calleja
Journal:  Pharmacol Res Perspect       Date:  2021-12

4.  Screening for severe drug-drug interactions in patients with multiple sclerosis: A comparison of three drug interaction databases.

Authors:  Michael Hecker; Niklas Frahm; Paula Bachmann; Jane Louisa Debus; Marie-Celine Haker; Pegah Mashhadiakbar; Silvan Elias Langhorst; Julia Baldt; Barbara Streckenbach; Felicita Heidler; Uwe Klaus Zettl
Journal:  Front Pharmacol       Date:  2022-08-05       Impact factor: 5.988

5.  Comparison of Clinical Importance of Drug Interactions Identified by Hospital Pharmacists and a Local Clinical Decision Support System.

Authors:  Louise Lau; Harkaryn Bagri; Michael Legal; Karen Dahri
Journal:  Can J Hosp Pharm       Date:  2021-07-01

6.  Translation of evidence into kidney transplant clinical practice: managing drug-lab interactions by a context-aware clinical decision support system.

Authors:  Zahra Niazkhani; Mahsa Fereidoni; Parviz Rashidi Khazaee; Afshin Shiva; Khadijeh Makhdoomi; Andrew Georgiou; Habibollah Pirnejad
Journal:  BMC Med Inform Decis Mak       Date:  2020-08-20       Impact factor: 2.796

  6 in total

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