Evidence map›Paper›PMID 34223095›Full record

ArticleJAC-antimicrobial resistance2021

Feasibility study of hospital antimicrobial stewardship analytics using electronic health records.

P F Dutey-Magni, M J Gill, D McNulty, G Sohal, A Hayward, L Shallcross, Niall Anderson, Elise Crayton, Gillian Forbes, Arnoupe Jhass and 23 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JAC-antimicrobial resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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  10. Dedicated team to ambulatory care for patients with COVID-19 requiring oxygen: Low rate of hospital readmission.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
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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

33 authors at 2 institutions in 1 country.

P F Dutey-MagniInstitute of Health Informatics, University College London, London, UK.ORCID https://orcid.org/0000-0002-8942-9836
M J GillUniversity Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
D McNultyUniversity Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
G SohalUniversity Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
A HaywardInstitute of Epidemiology & Health Care, University College London, London, UK.
L ShallcrossInstitute of Health Informatics, University College London, London, UK.ORCID https://orcid.org/0000-0003-1713-2555
Niall AndersonInstitute of Health Informatics, University College London, London, UK.
Elise CraytonInstitute of Health Informatics, University College London, London, UK.
Gillian ForbesInstitute of Health Informatics, University College London, London, UK.
Arnoupe JhassInstitute of Health Informatics, University College London, London, UK.
Emma RichardsonInstitute of Health Informatics, University College London, London, UK.
Michelle RichardsonInstitute of Health Informatics, University College London, London, UK.
Patrick RockenschaubInstitute of Health Informatics, University College London, London, UK.
Catherine SmithInstitute of Health Informatics, University College London, London, UK.
Elizabeth SuttonInstitute of Health Informatics, University College London, London, UK.
Rosanna TrainaInstitute of Health Informatics, University College London, London, UK.
Lou AtkinsInstitute of Health Informatics, University College London, London, UK.
Anne ConollyInstitute of Health Informatics, University College London, London, UK.
Spiros DenaxasInstitute of Health Informatics, University College London, London, UK.
Ellen FragaszyInstitute of Health Informatics, University College London, London, UK.
Rob HorneInstitute of Health Informatics, University College London, London, UK.
Patty KostkovaInstitute of Health Informatics, University College London, London, UK.
Fabiana LorencattoInstitute of Health Informatics, University College London, London, UK.
Susan MichieInstitute of Health Informatics, University College London, London, UK.
Jennifer MindellInstitute of Health Informatics, University College London, London, UK.
John RobsonInstitute of Health Informatics, University College London, London, UK.
Claire RoystonInstitute of Health Informatics, University College London, London, UK.
Carolyn TarrantInstitute of Health Informatics, University College London, London, UK.
James ThomasInstitute of Health Informatics, University College London, London, UK.
Jonathan WestInstitute of Health Informatics, University College London, London, UK.
Haydn WilliamsInstitute of Health Informatics, University College London, London, UK.
Nadia ElsayInstitute of Health Informatics, University College London, London, UK.
Chris FullerInstitute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust · GBUniversity College London · GB

Funding

Medical Research Council MR/K006584/1
6 · The paper itself

Abstract

backgroundHospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimize antimicrobial use. Most hospitals depend on time-consuming manual audits to monitor clinicians' prescribing. But much of the information needed could be sourced from electronic health records (EHRs).

objectivesTo develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records.

methodsFeasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialities at Queen Elizabeth Hospital, Birmingham, UK (September 2017-August 2018). The study involved: (i) a review of AMS standards of care; (ii) their translation into concepts measurable from commonly available EHRs; and (iii) a pilot application in an EHR cohort study (

resultsWe developed data modelling methods to characterize antimicrobial use (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy 5.8 days), enabling several actionable findings. For example, 22% of therapy episodes for low-severity community-acquired pneumonia were congruent with prescribing guidelines, with a tendency to use broader-spectrum antibiotics. Analysis of therapy changes revealed IV to oral therapy switching was delayed by an average 3.6 days (95% CI: 3.4-3.7). Microbial cultures were performed prior to treatment initiation in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice down to specialities, wards and individual clinical teams by case mix, enabling more meaningful peer comparison.

conclusionsIt is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimizing prescribing, and AMS impact evaluation studies.

Identifiers

PMID34223095
PMCPMC8210026
OpenAlexW3124898425

What OpenQuestion holds

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LicenceCC BY
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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.