Evidence map›Paper›PMID 31151485›Full record

ArticleBMC pharmacology & toxicology2019

Countrywide prevalence of critical drug interactions in Hungarian outpatients: a retrospective analysis of pharmacy dispensing data.

Anna Somogyi-Végh, Zsófia Ludányi, Ábel Erdős, Lajos Botz

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Anna Somogyi-VéghDepartment of Pharmaceutics and Central Clinical Pharmacy, Clinical Centre, University of Pécs, Honvéd u. 3, Pécs, H-7624, Hungary. vegh.anna@pte.hu.ORCID 0000-0002-1755-0768
Zsófia LudányiIQVIA Solutions Services Kft., Váci út 1-3, Budapest, H-1062, Hungary.
Ábel ErdősIQVIA Solutions Services Kft., Váci út 1-3, Budapest, H-1062, Hungary.
Lajos BotzDepartment of Pharmaceutics and Central Clinical Pharmacy, Clinical Centre, University of Pécs, Honvéd u. 3, Pécs, H-7624, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug-drug interactions (DDIs) present a significant source of adverse drug reactions. Despite being one of the commonly cited risks to patient safety, prevention of DDIs still poses a challenge to healthcare systems. The prevalence of DDIs can be used as a quality indicator for the safety of prescribing. With the analysis of drug utilization databases, real-world data on critical DDIs can be obtained. The aim of this study was to establish a list of critical DDIs and estimate their prevalence in the Hungarian outpatient population.

methodsSince there is no conclusive and generally accepted repository of high-risk DDIs, a systematic search of the literature for consensus-based lists was performed. Based on these results and their analysis with 5 interaction compendia, we propose a simple methodology to identify critical combinations. Present study focused on DDIs which are (1) of high clinical importance thus being most likely to cause significant harm if not detected, (2) well-supported by available evidence and (3) affect drugs which are routinely dispensed in the community pharmacy setting. A retrospective analysis of prescriptions filled between 2013 and 2016 was performed. The source of drug utilization data was the IQVIA's national prescription fill database. The number of interacting drug pairs dispensed at the same time to the same patient was established.

resultsAfter excluding drugs with low dispensing rates, the analysis covered 39 DDIs. The distribution of risk categories of the analysed DDIs was inconsistent among different drug interaction compendia. The total number of prescriptions filled varied between 173924449 and 176368468 per year. The prevalence of the selected potential DDIs ranged from 0.00 to 355.89 per 100000 prescriptions per year. There was significant variation between how the number of cases had changed for each DDI throughout the study period, no general tendency could have been described.

conclusionsThere were 1.8 million cases of co-dispensing each year, where prescribers' and community pharmacists' role in recognizing and managing potentially serious interactions was or would have been critical. The method presented to identify high-risk DDIs can serve as a starting point for the much-needed improvement of routine interaction screening.

Indexed as

Drug InteractionsCommunity Pharmacy ServicesDrug-Related Side Effects and Adverse ReactionsDrug UtilizationHumansHungaryOutpatientsPharmacistsPrevalenceCritical drug combinationsDrug-drug interactionPatient safetyPharmacy dispensing dataPrescription analysis

Identifiers

PMID31151485
PMCPMC6544909

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.