Evidence map›Paper›PMID 31659589›Full record

ArticleJournal of digital imaging2020

Musculoskeletal Radiology Reports: Overlooked or Valuable?

Sadaf Sahraian, Matthew D Alvin, Arya Haj-Mirzaian, Rozita Jalilianhasanpour, Elham Beheshtian, Evan Honig, Mona Shahriari, Mert Uzner, Shadpour Demehri, David M Yousem

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of digital imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Structured reporting in knee MRI.Skeletal radiology · 2026
    Review
  2. 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

10 authors at 1 institution in 1 country.

Sadaf SahraianRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA. dyousem1@jhu.edu.ORCID 0000-0003-3550-6231
Matthew D AlvinRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Arya Haj-MirzaianRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Rozita JalilianhasanpourRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Elham BeheshtianRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Evan HonigRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Mona ShahriariRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Mert UznerRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Shadpour DemehriRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
David M YousemRussell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, 600 N. Wolfe Street, Phipps B100F, Baltimore, MD, 21287, USA.
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The electronic medical record (EMR) can reveal preferences of clinicians regarding imaging services. We sought to evaluate viewing habits for reports and images of musculoskeletal (MSK) studies by ordering clinicians. We hypothesized that MSK reports are important to clinical management, especially for advanced imaging modalities. We tracked the image and report access of all MSK studies ordered in September 2016 over 8 months using logs of the EMR (Epic Systems, Verona, WI), and by an independent analysis of the institutional PACS (Picture Archiving and Communication Systems) (Carestream Health, Rochester, NY). The time stamps were extracted for when images and reports were viewed. We categorized MSK studies by modality and provider department. We also compared the rates of viewing reports and images among different modalities and departments using the chi-square test. Of the 8143 viewed MSK studies, 7842 (96.3%) reports (with/without images) and 3916 (48.1%) imaging data (with/without reports) were viewed. Viewing reports alone occurred in 4227 (51.9%) studies. CT and MRI reports alone views occurred more often in comparison to radiographs ([482/706; 68.3%] for CT and [981/1713; 57.3%] for MRI vs. [2764/5724; 48.3%] for radiography, p < 0.001). Orthopedists ordered the highest number of MSK studies and viewed reports 99.2% (3216/3242) of the time, including a 54.6% (1770/3242) rate of viewing reports alone and a 44.6% (1446/3242) rate of viewing both reports and images. They viewed images without reports in 0.8% (27/3242) of cases. MSK reports were viewed significantly more frequently than the images across all modalities and all relevant specialties.

Indexed as

RadiologyComputer SystemsElectronic Health RecordsHumansRadiographyRadiology Information SystemsEMRMusculoskeletalPACSValueViewing imagingViewing report

Identifiers

PMID31659589
PMCPMC7165200
OpenAlexW2982598086

What OpenQuestion holds

Textmetadata
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.