Evidence map›Paper›PMID 36168472›Full record

ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2021

Cost-effectiveness analysis of whole-genome sequencing during an outbreak of carbapenem-resistant

Thomas M Elliott, Patrick N Harris, Leah W Roberts, Michelle Doidge, Trish Hurst, Krispin Hajkowicz, Brian Forde, David L Paterson, Louisa G Gordon

Abstract read
In one paragraph

Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Carbapenem-resistantMicrobiology spectrum · 2026
    Article
  4. Burden and Economic Impact of Antimicrobial Resistance inThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2026
    Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
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

9 authors.

Thomas M ElliottQIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-7702-7688
Patrick N HarrisThe University of Queensland, Centre for Clinical Research, Herston, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-2895-0345
Leah W RobertsSchool of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-1024-0564
Michelle DoidgeInfectious Diseases Unit, Royal Brisbane and Womens' Hospital, Herston, Brisbane, Queensland, Australia.
Trish HurstInfectious Diseases Unit, Royal Brisbane and Womens' Hospital, Herston, Brisbane, Queensland, Australia.
Krispin HajkowiczCentral Microbiology, Pathology Queensland, Royal Brisbane and Women's Hospital, Herston, Brisbane, Queensland, Australia.
Brian FordeThe University of Queensland, Centre for Clinical Research, Herston, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-2264-4785
David L PatersonThe University of Queensland, Centre for Clinical Research, Herston, Brisbane, Queensland, Australia.
Louisa G GordonQIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia.ORCID https://orcid.org/0000-0002-3159-4249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Whole-genome sequencing (WGS) shotgun metagenomics (metagenomics) attempts to sequence the entire genetic content straight from the sample. Diagnostic advantages lie in the ability to detect unsuspected, uncultivatable, or very slow-growing organisms. Objective: To evaluate the clinical and economic effects of using WGS and metagenomics for outbreak management in a large metropolitan hospital. Design: Cost-effectiveness study. Setting: Intensive care unit and burn unit of large metropolitan hospital. Patients: Simulated intensive care unit and burn unit patients. Methods: We built a complex simulation model to estimate pathogen transmission, associated hospital costs, and quality-adjusted life years (QALYs) during a 32-month outbreak of carbapenem-resistant Results: On average compared with scenario 1, scenario 2 resulted in 14 fewer patients with CRAB, 59 additional QALYs, and $75,099 cost savings. Scenario 3, compared with scenario 1, resulted in 18 fewer patients with CRAB, 74 additional QALYs, and $93,822 in hospital cost savings. The likelihoods that scenario 2 and scenario 3 were cost-effective were 57% and 60%, respectively. Conclusions: The use of WGS and metagenomics in infection control processes were predicted to produce favorable economic and clinical outcomes.

Identifiers

PMID36168472
PMCPMC9495627

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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.