Evidence map›Paper›PMID 26614882›Full record

SynthesisJournal of the American College of Radiology : JACR2015

Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis.

Joshua R Vest, Hye-Young Jung, Aaron Ostrovsky, Lala Tanmoy Das, Geraldine B McGinty

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of the American College of Radiology : JACR, 2015. 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. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Racial differences in patient consent policy preferences for electronic health information exchange.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  9. The Enterprise Imaging Value Proposition.Journal of digital imaging · 2020
    Review
  10. Usage of and Attitudes Toward Health Information Exchange Before and After System Implementation in a VA Medical Center.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2019
    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

5 authors.

Joshua R VestDepartment of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York. Electronic address: joshvest@iu.edu.
Hye-Young JungDepartment of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York.
Aaron OstrovskyDepartment of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York.
Lala Tanmoy DasDepartment of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York; Greenberg Division of Cardiology, Weill Cornell Medical College, New York, New York.
Geraldine B McGintyDepartment of Radiology, Weill Cornell Medical College, New York, New York; New York-Presbyterian Hospital, New York, New York.

Funding

TRAINing in Aging Health & Health Services for Alzheimer's Disease and Related Dementias (TRAIN-ADRD)T32AG023482 · NIA · BROWN UNIVERSITY · PI Vincent Mor, Theresa I. Shireman · 2004 to 2026
$3.0M
NIA NIH HHS T32 AG023482
6 · The paper itself

Abstract

introductionImage sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization.

methodsQuantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004-2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models.

resultsA total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = -0.17; 95% confidence interval [CI] = [-0.25, -0.09]; P < .001). However, image sharing technology was associated with a significant increase in any imaging utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias.

conclusionsImage sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings.

Indexed as

Diagnostic ImagingEfficiency, OrganizationalElectronic Health RecordsHospital Shared ServicesInternationalityMedical OveruseRadiology Information SystemsUtilization Reviewdata sharingevaluationHealth information exchangeradiology information systemsutilization

Identifiers

PMID26614882
PMCPMC4730956

What OpenQuestion holds

Textmetadata
LicenceTDM
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.