Literature DB >> 34811600

Determination of potential drug-drug interactions in prescription orders dispensed in a community pharmacy setting using Micromedex® and Lexicomp®: a retrospective observational study.

Afraa Abbas1, Samaher Al-Shaibi1, Sowndramalingam Sankaralingam1, Ahmed Awaisu1, Vyas S Kattezhathu2, Supakit Wongwiwatthananukit3, Yaw B Owusu4.   

Abstract

Background Community pharmacists have a role in identifying drug-drug interactions (DDIs) when processing prescription orders and dispensing medications to patients. The harmful effects of DDIs can be prevented or minimized by using an electronic DDI checker to screen for potential DDIs (pDDIs). However, different DDI checkers have variable rates of detecting pDDIs. Aim To estimate the prevalence of pDDIs in prescriptions dispensed in a community pharmacy setting using two electronic DDI databases and to evaluate the association between the pDDIs and contributory factors. Method Eligible prescription orders dispensed by a community pharmacy chain in Qatar from January to July 2020 were included in this retrospective observational study. For each prescription, Micromedex® and Lexicomp® were simultaneously used to identify pDDIs, and the interactions categorized based on severity and risk rating. Results Seven hundred-twenty prescriptions met the inclusion criteria, of which Micromedex® and Lexicomp® respectively identified 125 prescriptions (17.4%) and 230 prescriptions (31.9%) as having at least one pDDI. Moderate strength of agreement was found between Lexicomp® and Micromedex® in identifying pDDIs (Cohen's Kappa = 0.546). Micromedex® classified 61.6% of DDIs as major severity, while Lexicomp® classified 30.8% as major severity. The number of concurrent medications per prescription was significantly and positively associated with pDDI. Conclusion This study demonstrates a high prevalence of pDDIs among prescriptions dispensed in a community pharmacy setting. It is advisable that community pharmacists in Qatar, who typically do not have access to computerized patient profiles, use these DDI checkers to ensure all pDDIs are communicated to respective prescribers for appropriate action.
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Entities:  

Keywords:  Community pharmacy; Drug prescription; Drug–drug interactions; Lexicomp®; Micromedex®; Pharmacist

Mesh:

Year:  2021        PMID: 34811600     DOI: 10.1007/s11096-021-01346-8

Source DB:  PubMed          Journal:  Int J Clin Pharm


  30 in total

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Journal:  Pharmacoepidemiol Drug Saf       Date:  2007-06       Impact factor: 2.890

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Authors:  Johanna Strandell; Andrew Bate; Marie Lindquist; I Ralph Edwards
Journal:  Br J Clin Pharmacol       Date:  2007-07-17       Impact factor: 4.335

3.  A limited number of prescribed drugs account for the great majority of drug-drug interactions.

Authors:  Johan Holm; Birgit Eiermann; Erik Eliasson; Buster Mannheimer
Journal:  Eur J Clin Pharmacol       Date:  2014-09-06       Impact factor: 2.953

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Authors:  David N Juurlink; Muhammad Mamdani; Alexander Kopp; Andreas Laupacis; Donald A Redelmeier
Journal:  JAMA       Date:  2003-04-02       Impact factor: 56.272

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Authors:  Eva Montané; Ana Lucía Arellano; Yolanda Sanz; Josep Roca; Magí Farré
Journal:  Br J Clin Pharmacol       Date:  2018-01-11       Impact factor: 4.335

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Authors:  Srinivasan V Iyer; Rave Harpaz; Paea LePendu; Anna Bauer-Mehren; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2013-10-24       Impact factor: 4.497

7.  Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients.

Authors:  Munir Pirmohamed; Sally James; Shaun Meakin; Chris Green; Andrew K Scott; Thomas J Walley; Keith Farrar; B Kevin Park; Alasdair M Breckenridge
Journal:  BMJ       Date:  2004-07-03

8.  Adverse drug events associated with hospital admission.

Authors:  Hélène Peyriere; Stéphanie Cassan; Edith Floutard; Sophie Riviere; Jean-Pierre Blayac; Dominique Hillaire-Buys; Alain Le Quellec; Sylvie Hansel
Journal:  Ann Pharmacother       Date:  2003-01       Impact factor: 3.154

9.  Comparison of potential drug-drug interactions with metabolic syndrome medications detected by two databases.

Authors:  Bovornpat Suriyapakorn; Pun Chairat; Suwanan Boonyoprakarn; Pimonwan Rojanarattanangkul; Wassana Pisetcheep; Natthaphon Hunsakunachai; Pornpun Vivithanaporn; Supakit Wongwiwatthananukit; Phisit Khemawoot
Journal:  PLoS One       Date:  2019-11-14       Impact factor: 3.240

10.  The frequency of adverse drug reaction related admissions according to method of detection, admission urgency and medical department specialty.

Authors:  Miran Brvar; Nina Fokter; Matjaz Bunc; Martin Mozina
Journal:  BMC Clin Pharmacol       Date:  2009-05-04
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