ArticleiScience2026
Association between radiological CDSS availability and quality of imaging referrals graded using RI-RADS.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deficiencies in clinical information within imaging referrals can affect imaging justification and the quality of radiology reporting. This pragmatic controlled before-and-after implementation study evaluated cervical and lumbar spine X-ray referral quality in an emergency department before and after the availability of a standalone clinical decision support system (CDSS) alongside existing workflows. Referrals were assessed using the reason for exam imaging reporting and data system (RI-RADS), grades A-D. Approximately three-quarters were classified as deficient, grade D. Logistic regression and mixed-effects modeling demonstrated no statistical significance between-group effect, although temporal confounding prevents firm conclusions regarding CDSS effectiveness. Both groups showed reductions in deficient referrals over time, with no additional improvement associated with CDSS availability beyond observed secular trends. These findings highlight challenges associated with standalone CDSS implementation and emphasize the importance of workflow and health-technology integration when designing decision support to improve imaging referral quality.
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