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

Journal

JAC-antimicrobial resistance
ISSN: 2632-1823
Titre abrégé: JAC Antimicrob Resist
Pays: England
ID NLM: 101765283

Informations de publication

Date de publication:
Mar 2021
Historique:
received: 06 10 2020
accepted: 27 01 2021
entrez: 5 7 2021
pubmed: 6 7 2021
medline: 6 7 2021
Statut: epublish

Résumé

Hospital 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). To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. Feasibility 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 ( We 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. It 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.

Sections du résumé

BACKGROUND BACKGROUND
Hospital 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).
OBJECTIVES OBJECTIVE
To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records.
METHODS METHODS
Feasibility 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 (
RESULTS RESULTS
We 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.
CONCLUSIONS CONCLUSIONS
It 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.

Identifiants

DOI: 10.1093/jacamr/dlab018 PMID: 34223095 PMC: PMC8210026
pubmed: 34223095
doi: 10.1093/jacamr/dlab018
pii: dlab018
pmc: PMC8210026
doi:

Types de publication

Journal Article

Langues

eng

Pagination

dlab018

Subventions

Organisme : Medical Research Council
ID : MR/K006584/1
Pays : United Kingdom

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

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Auteurs

P F Dutey-Magni (PF)

Institute of Health Informatics, University College London, London, UK.
ORCID: 0000-0002-8942-9836

M J Gill (MJ)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

D McNulty (D)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

G Sohal (G)

University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

A Hayward (A)

Institute of Epidemiology & Health Care, University College London, London, UK.

L Shallcross (L)

Institute of Health Informatics, University College London, London, UK.
ORCID: 0000-0003-1713-2555

Niall Anderson (N)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Elise Crayton (E)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Gillian Forbes (G)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Arnoupe Jhass (A)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Emma Richardson (E)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Michelle Richardson (M)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Patrick Rockenschaub (P)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Catherine Smith (C)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Elizabeth Sutton (E)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Rosanna Traina (R)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Lou Atkins (L)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Anne Conolly (A)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Spiros Denaxas (S)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Ellen Fragaszy (E)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Rob Horne (R)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Patty Kostkova (P)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Fabiana Lorencatto (F)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Susan Michie (S)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Jennifer Mindell (J)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

John Robson (J)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Claire Royston (C)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Carolyn Tarrant (C)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

James Thomas (J)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Jonathan West (J)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Haydn Williams (H)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Nadia Elsay (N)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Chris Fuller (C)

Institute of Health Informatics, University College London, London, UK.
University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Institute of Epidemiology & Health Care, University College London, London, UK.

Classifications MeSH