Evidence map›Paper›PMID 24887257›Full record

SynthesisPloS one2014

Image-based medical expert teleconsultation in acute care of injuries. A systematic review of effects on information accuracy, diagnostic validity, clinical outcome, and user satisfaction.

Marie Hasselberg, Netta Beer, Lisa Blom, Lee A Wallis, Lucie Laflamme

Open access · goldAbstract readSystematic ReviewValidation Study
In one paragraph

Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 5 pooled it
3.9field-weighted citation impact, top 7% 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

20 citing papers in PubMed, 5 syntheses or guidelines pooled it, 42 citations in OpenAlex.

  1. Pooled it
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  4. Pooled it
  5. Pooled it
  6. Telemedicine and public health-pearls and pitfalls.World journal of methodology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Review of Systematic Reviews in the Field of Telemedicine.Medical journal of the Islamic Republic of Iran · 2021
    Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Teleconsultation and Clinical Decision Making: a Systematic Review.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2016
    Article
  18. Article
  19. Can We Trust the Use of Smartphone Cameras in Clinical Practice? Laypeople Assessment of Their Image Quality.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2015
    Article
  20. Review
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

5 authors at 2 institutions in 2 countries.

Marie HasselbergDepartment of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Netta BeerDepartment of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Lisa BlomDepartment of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Lee A WallisDivision of Emergency Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Lucie LaflammeDepartment of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden; University of South Africa, Pretoria, South Africa.
Karolinska Institutet · SEWestern Cape Department of Health · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo systematically review the literature on image-based telemedicine for medical expert consultation in acute care of injuries, considering system, user, and clinical aspects.

designSystematic review of peer-reviewed journal articles. DATA SOURCES: Searches of five databases and in eligible articles, relevant reviews, and specialized peer-reviewed journals. ELIGIBILITY CRITERIA: Studies were included that covered teleconsultation systems based on image capture and transfer with the objective of seeking medical expertise for the diagnostic and treatment of acute injury care and that presented the evaluation of one or several aspects of the system based on empirical data. Studies of systems not under routine practice or including real-time interactive video conferencing were excluded.

methodThe procedures used in this review followed the PRISMA Statement. Predefined criteria were used for the assessment of the risk of bias. The DeLone and McLean Information System Success Model was used as a framework to synthesise the results according to system quality, user satisfaction, information quality and net benefits. All data extractions were done by at least two reviewers independently.

resultsOut of 331 articles, 24 were found eligible. Diagnostic validity and management outcomes were often studied; fewer studies focused on system quality and user satisfaction. Most systems were evaluated at a feasibility stage or during small-scale pilot testing. Although the results of the evaluations were generally positive, biases in the methodology of evaluation were concerning selection, performance and exclusion. Gold standards and statistical tests were not always used when assessing diagnostic validity and patient management.

conclusionsImage-based telemedicine systems for injury emergency care tend to support valid diagnosis and influence patient management. The evidence relates to a few clinical fields, and has substantial methodological shortcomings. As in the case of telemedicine in general, user and system quality aspects are poorly documented, both of which affect scale up of such programs.

Indexed as

Consumer BehaviorTelemedicineHumansWounds and Injuries

Identifiers

PMID24887257
PMCPMC4041890
OpenAlexW1971049752

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.