Evidence map›Paper›PMID 38655022›Full record

ReviewAntimicrobial stewardship & healthcare epidemiology : ASHE2024

Navigating the network: a narrative overview of AMR surveillance and data flow in the United States.

Darin W Robillard, Alexander J Sundermann, Brian R Raux, Andrea M Prinzi

Abstract readReview
In one paragraph

Review in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2024. 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. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Antimicrobial resistance inScience in One Health · 2025
    Review
  10. Review
  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

4 authors.

Darin W RobillardDivision of Public Health, University of Utah School of Medicine, Salt Lake City, UT, USA.ORCID https://orcid.org/0009-0005-8552-531X
Alexander J SundermannDivision of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0002-2439-6287
Brian R RauxUS Medical Affairs, bioMérieux, Salt Lake City, UT, USA.ORCID https://orcid.org/0000-0003-0183-216X
Andrea M PrinziUS Medical Affairs, bioMérieux, Salt Lake City, UT, USA.ORCID https://orcid.org/0000-0003-2949-5484

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The antimicrobial resistance (AMR) surveillance landscape in the United States consists of a data flow that starts in the clinical setting and is maintained by a network of national and state public health laboratories. These organizations are well established, with robust methodologies to test and confirm antimicrobial susceptibility. Still, the bridge that guides the flow of data is often one directional and caught in a constant state of rush hour that can only be refined with improvements to infrastructure and automation in the data flow. Moreover, there is an absence of information in the literature explaining the processes clinical laboratories use to coalesce and share susceptibility test data for AMR surveillance, further complicated by variability in testing procedures. This knowledge gap limits our understanding of what is needed to improve and streamline data sharing from clinical to public health laboratories. Successful models of AMR surveillance display attributes like 2-way communication between clinical and public health laboratories, centralized databases, standardized data, and the use of electronic health records or data systems, highlighting areas of opportunity and improvement. This article explores the roles and processes of the organizations involved in AMR surveillance in the United States and identifies current knowledge gaps and opportunities to improve communication between them through standardization, communication, and modernization of data flow.

Identifiers

PMID38655022
PMCPMC11036423

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.