Evidence map›Paper›PMID 39049093›Full record

ArticleBMC health services research2024

Strategies used to detect and mitigate system-related errors over time: A qualitative study in an Australian health district.

Madaline Kinlay, Wu Yi Zheng, Rosemary Burke, Ilona Juraskova, Lai Mun Ho, Hannah Turton, Jason Trinh, Melissa T Baysari

Abstract read
In one paragraph

Article in BMC health services research, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Madaline KinlayBiomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia.
Wu Yi ZhengBlack Dog Institute, Sydney, Australia.
Rosemary BurkePharmacy Services, Sydney Local Health District, Sydney, Australia.
Ilona JuraskovaSchool of Psychology, Faculty of Science, The University of Sydney, Sydney, Australia.
Lai Mun HoPharmacy Services, Sydney Local Health District, Sydney, Australia.
Hannah TurtonPharmacy Services, Sydney Local Health District, Sydney, Australia.
Jason TrinhPharmacy Services, Sydney Local Health District, Sydney, Australia.
Melissa T BaysariBiomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia. melissa.baysari@sydney.edu.au.

Funding

Australian Government Research Training Program (RTP) Scholarship
6 · The paper itself

Abstract

backgroundElectronic medical record (EMR) systems provide timely access to clinical information and have been shown to improve medication safety. However, EMRs can also create opportunities for error, including system-related errors or errors that were unlikely or not possible with the use of paper medication charts. This study aimed to determine the detection and mitigation strategies adopted by a health district in Australia to target system-related errors and to explore stakeholder views on strategies needed to curb future system-related errors from emerging.

methodsA qualitative descriptive study design was used comprising semi-structured interviews. Data were collected from three hospitals within a health district in Sydney, Australia, between September 2020 and May 2021. Interviews were conducted with EMR users and other key stakeholders (e.g. clinical informatics team members). Participants were asked to reflect on how system-related errors changed over time, and to describe approaches taken by their organisation to detect and mitigate these errors. Thematic analysis was conducted iteratively using a general inductive approach, where codes were assigned as themes emerged from the data.

resultsInterviews were conducted with 25 stakeholders. Participants reported that most system-related errors were detected by front-line clinicians. Following error detection, clinicians either reported system-related errors directly to the clinical informatics team or submitted reports to the incident information management system. System-related errors were also reported to be detected via reports run within the EMR, or during organisational processes such as incident investigations or system enhancement projects. EMR redesign was the main approach described by participants for mitigating system-related errors, however other strategies, like regular user education and minimising the use of hybrid systems, were also reported.

conclusionsInitial detection of system-related errors relies heavily on front-line clinicians, however other organisational strategies that are proactive and layered can improve the systemic detection, investigation, and management of errors. Together with EMR design changes, complementary error mitigation strategies, including targeted staff education, can support safe EMR use and development.

Indexed as

Electronic Health RecordsQualitative ResearchAustraliaHumansInterviews as TopicMedical ErrorsMedication ErrorsPatient SafetyElectronic medical recordError detectionError preventionHospitalPatient safetySystem-related errors

Identifiers

PMID39049093
PMCPMC11270877

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LicenceCC BY
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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.