Evidence map›Paper›PMID 29058038›Full record

SynthesisEuropean journal of clinical pharmacology2018

Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis.

Wu Yi Zheng, L C Richardson, L Li, R O Day, J I Westbrook, M T Baysari

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in European journal of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 14 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 14 pooled it
7.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 14 syntheses or guidelines pooled it, 161 citations in OpenAlex.

  1. Effect of electronic drug-drug interaction alerts on patient and clinician outcomes: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025
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  10. Prevalence of drug interactions in hospitalised elderly patients: a systematic review.European journal of hospital pharmacy : science and practice · 2021
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  16. Assessment of potential drug interactions in rheumatology: a comparative study of decision support software.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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

6 authors at 3 institutions in 1 country.

Wu Yi ZhengCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia. wuyi.zheng@mq.edu.au.ORCID http://orcid.org/0000-0002-1159-4700
L C RichardsonCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia.
L LiCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia.
R O DayDepartment of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Darlinghurst, Australia.
J I WestbrookCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia.
M T BaysariCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia.
Macquarie University · AUSt Vincent's Clinic · AUSt Vincent's Hospital Sydney · AU

Funding

Australian National Health and Medical Research Council Program Grant 1054146
6 · The paper itself

Abstract

purposeDrug-drug interactions (DDIs) are often avoidable and, if undetected, can lead to patient harm. This review aimed to determine the prevalence of potential DDIs (pDDIs), clinically relevant DDIs (DDIs that could lead to measurable patient harm, taking into account the patient's individual clinical profile) and DDIs that resulted in actual patient harm during hospitalisation.

methodFour databases were scanned for English papers published from 2000 to 2016. Papers that reported prevalence of DDIs in the outpatient setting, at admission or discharge, involving only specific drugs, or in specific disease populations or age groups were excluded.

resultsTwenty-seven papers met the inclusion criteria and were graded for quality using the Critical Appraisal Skills Programme (CASP) cohort study checklist. Ten papers were rated as 'poor', 14 as 'fair' and only three papers as 'good'. Overall, the meta-analysis revealed that 33% of general patients and 67% of intensive care patients experienced a pDDI during their hospital stay. It was not possible to determine the prevalence of clinically relevant DDIs or DDIs that resulted in actual patient harm as data on these categories were limited. Of the very few studies that reported on harm, only a small proportion of DDIs were found to have resulted in actual patient harm.

conclusionsStandardisation of DDI definitions and research methods are required to allow meaningful prevalence rates to be obtained and compared. Studies that go further than measuring pDDIs are critically needed to determine the impact of DDIs on patient safety.

Indexed as

Drug InteractionsDrug-Related Side Effects and Adverse ReactionsInpatientsHospitalizationHumansMedication ErrorsPatient SafetyPrevalenceClinical relevanceDrug-drug interactionMedication errorsPatient safety

Identifiers

PMID29058038
OpenAlexW2766129742

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.