Evidence map›Paper›PMID 36513770›Full record

ArticleNPJ digital medicine2022

Short- and long-term effects of an electronic medication management system on paediatric prescribing errors.

Johanna I Westbrook, Ling Li, Magdalena Z Raban, Virginia Mumford, Tim Badgery-Parker, Peter Gates, Erin Fitzpatrick, Alison Merchant, Amanda Woods, Melissa Baysari and 12 more

Abstract read
In one paragraph

Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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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

22 authors.

Johanna I WestbrookAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia. Johanna.westbrook@mq.edu.au.ORCID http://orcid.org/0000-0003-1083-8192
Ling LiAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-1642-142X
Magdalena Z RabanAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-6995-2849
Virginia MumfordAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0001-7915-0615
Tim Badgery-ParkerAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-1275-1130
Peter GatesAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Erin FitzpatrickAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Alison MerchantAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0002-8223-0090
Amanda WoodsAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Melissa BaysariFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Cheryl McCullaghSydney Children's Hospitals Network, Sydney, Australia.
Ric DayFaculty of Medicine and Health, University of New South Wales, Sydney, Australia.
Madlen GazarianFaculty of Medicine and Health, University of New South Wales, Sydney, Australia.ORCID http://orcid.org/0000-0001-9007-0595
Michael DickinsonSydney Children's Hospitals Network, Sydney, Australia.ORCID http://orcid.org/0000-0001-6164-7471
Karla SeamanAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID http://orcid.org/0000-0003-4611-9616
Lucciano Dalla-PozzaSydney Children's Hospitals Network, Sydney, Australia.
Geoffrey AmblerFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Peter BarclaySydney Children's Hospitals Network, Sydney, Australia.
Alan GardoSydney Children's Hospitals Network, Sydney, Australia.
Tracey O'BrienSydney Children's Hospitals Network, Sydney, Australia.
Draga BarbaricSydney Children's Hospitals Network, Sydney, Australia.
Les WhiteAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.

Funding

Department of Health | National Health and Medical Research Council (NHMRC) GNT1174021, 1094878
6 · The paper itself

Abstract

Electronic medication management (eMM) systems are designed to improve safety, but there is little evidence of their effectiveness in paediatrics. This study assesses the short-term (first 70 days of eMM use) and long-term (one-year) effectiveness of an eMM system to reduce prescribing errors, and their potential and actual harm. We use a stepped-wedge cluster randomised controlled trial (SWCRCT) at a paediatric referral hospital, with eight clusters randomised for eMM implementation. We assess long-term effects from an additional random sample of medication orders one-year post-eMM. In the SWCRCT, errors that are potential adverse drug events (ADEs) are assessed for actual harm. The study comprises 35,260 medication orders for 4821 patients. Results show no significant change in overall prescribing error rates in the first 70 days of eMM use (incident rate ratio [IRR] 1.05 [95%CI 0.92-1.21], but a 62% increase (IRR 1.62 [95%CI 1.28-2.04]) in potential ADEs suggesting immediate risks to safety. One-year post-eMM, errors decline by 36% (IRR 0.64 [95%CI 0.56-0.72]) and high-risk medication errors decrease by 33% (IRR 0.67 [95%CI 0.51-0.88]) compared to pre-eMM. In all periods, dose error rates are more than double that of other error types. Few errors are associated with actual harm, but 71% [95%CI 50-86%] of patients with harm experienced a dose error. In the short-term, eMM implementation shows no improvement in error rates, and an increase in some errors. A year after eMM error rates significantly decline suggesting long-term benefits. eMM optimisation should focus on reducing dose errors due to their high frequency and capacity to cause harm.

Identifiers

PMID36513770
PMCPMC9747795

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Registered trials

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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.