Evidence map›Paper›PMID 39709192›Full record

ArticleBMJ open quality2024

Multifaceted approach to reduce duplicate therapy errors in the emergency department.

Huiling Huang, Srivatsava Sunku, Hui Shan Ong, Jonathan Kim Yang Chan, Guek Gwee Sim

Abstract read
In one paragraph

Article in BMJ open quality, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Huiling HuangDepartment of Emergency Medicine, Changi General Hospital, Singapore huiling145@hotmail.com.ORCID 0009-0007-4916-5083
Srivatsava SunkuDepartment of Emergency Medicine, Changi General Hospital, Singapore.ORCID 0009-0000-1872-7767
Hui Shan OngDepartment of Emergency Medicine, Changi General Hospital, Singapore.ORCID 0009-0003-2522-4318
Jonathan Kim Yang ChanDepartment of Emergency Medicine, Singapore General Hospital, Singapore.ORCID 0009-0004-9027-0721
Guek Gwee SimDepartment of Emergency Medicine, Changi General Hospital, Singapore.ORCID 0000-0002-1961-7452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medication errors continue to pose a significant risk to patient safety, accounting for half of the avoidable harm in healthcare systems around the world. In emergency departments (EDs), factors such as high patient loads and emergent nature of care increase the likelihood of such errors. An audit conducted at the ED of Changi General Hospital Singapore from January 2019 to July 2022 revealed that the duplicate therapy error comprised 31% of all reported medication errors. Therapeutic duplication occurs when the same or pharmacologically equivalent agents are prescribed concurrently to a patient. These errors not only jeopardise patient safety but also place additional strain on healthcare resources and lead to stress among the staff involved.This quality improvement (QI) project aims to reduce duplicate therapy error by 50% 3 months post-intervention at the ED. Beginning in August 2022 and continuing through December 2023, the project followed a structured approach comprising four phases: problem identification, identifying root causes, developing of targeted interventions and ensuring sustainability. Phase 1 involved an audit from January 2019 to July 2022 to determine the extent and types of medication errors in the ED. In phase 2, a root cause analysis (RCA) of the medication error identified key issues such as system knowledge deficits, inadequate IT processes, environment, policies and procedures and gaps in care coordination. Based on these findings, targeted interventions were developed and implemented in phase 3. Phase 4 focused on sustaining improvements through ongoing audits.The QI project successfully met its goal of reducing duplicate therapy error rates by 50% post-intervention. Additionally, it completely eliminated duplicate therapy errors in certain medication categories.In conclusion, through targeted interventions, active engagement of relevant stakeholders and ongoing efforts to sustain and enhance improvement, a safer healthcare environment can be achieved for patients.

Indexed as

Emergency Service, HospitalMedication ErrorsQuality ImprovementHumansPatient SafetyRoot Cause AnalysisSingaporeContinuous quality improvementMedication safetyQuality improvement

Identifiers

PMID39709192
PMCPMC11667450

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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.