Evidence map›Paper›PMID 38179556›Full record

ArticleFrontiers in public health2023

The barriers and facilitators of implementing a national laboratory-based AMR surveillance system in Cambodia: key informants' perspectives and assessments of microbiology laboratories.

Sovathiro Mao, Chansovannara Soputhy, Sokreaksa Lay, Jan Jacobs, Grace Marie Ku, Darapheak Chau, Chhorvann Chhea, Por Ir

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 12% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Laboratory epidemiology ofOne health (Amsterdam, Netherlands) · 2025
    Article
  8. 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

8 authors at 2 institutions in 2 countries.

Sovathiro MaoNational Institute of Public Health, Phnom Penh, Cambodia.
Chansovannara SoputhyNational Institute of Public Health, Phnom Penh, Cambodia.
Sokreaksa LayNational Institute of Public Health, Phnom Penh, Cambodia.
Jan JacobsInstitute of Tropical Medicine Antwerp, Antwerp, Belgium.
Grace Marie KuInstitute of Tropical Medicine Antwerp, Antwerp, Belgium.
Darapheak ChauNational Institute of Public Health, Phnom Penh, Cambodia.
Chhorvann ChheaNational Institute of Public Health, Phnom Penh, Cambodia.
Por IrNational Institute of Public Health, Phnom Penh, Cambodia.
National Institute of Public Health · KHInstituut voor Tropische Geneeskunde · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Collecting data on antimicrobial resistance (AMR) is an essential approach for defining the scope of the AMR problem, developing evidence-based interventions and detecting new and emerging resistances. Our study aimed to identify key factors influencing the implementation of a laboratory-based AMR surveillance system in Cambodia. This will add additional insights to the development of a sustainable and effective national AMR surveillance system in Cambodia and other low- and middle-income countries. Methods: Key informants with a role in governing or contributing data to the laboratory-based surveillance system were interviewed. Emerging themes were identified using the framework analysis method. Laboratories contributing to the AMR surveillance system were assessed on their capacity to conduct quality testing and report data. The laboratory assessment tool (LAT), developed by the World Health Organisation (WHO), was adapted for assessment of a diagnostic microbiology laboratory covering quality management, financial and human resources, data management, microbiology testing performance and surveillance capacity. Results: Key informants identified inadequate access to laboratory supplies, an unsustainable financing system, limited capacity to collect representative data and a weak workforce to be the main barriers to implementing an effective surveillance system. Consistent engagement between microbiology staff and clinicians were reported to be a key factor in generating more representative data for the surveillance system. The laboratory assessments identified issues with quality assurance and data analysis which may reduce the quality of data being sent to the surveillance system and limit the facility-level utilisation of aggregated data. A weak surveillance network and poor guidance for outbreak response were also identified, which can reduce the laboratories' opportunities in detecting critical or emerging resistance occurring in the community or outside of the hospital's geographical coverage. Conclusion: This study identified two primary concerns: ensuring a sustainable and quality functioning of microbiology services at public healthcare facilities and overcoming sampling bias at sentinel sites. These issues hinder Cambodia's national AMR surveillance system from generating reliable evidence to incorporate into public health measures or clinical interventions. These findings suggest that more investments need to be made into microbiology diagnostics and to reform current surveillance strategies for enhanced sampling of AMR cases at hospitals.

Indexed as

LaboratoriesPublic HealthCambodiaDisease OutbreaksHumansWorld Health Organizationantimicrobial resistanceclinical microbiologylaboratory-based surveillancelaboratory capacity assessmentsqualitative research

Identifiers

PMID38179556
PMCPMC10764616
OpenAlexW4390057187

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.