ArticleJournal of the American Medical Informatics Association : JAMIA2016
Assessing Strength of Evidence of Appropriate Use Criteria for Diagnostic Imaging Examinations.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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Who cites it
12 citing papers in PubMed.
- Effectiveness of the clinical decision support tool ESR eGUIDE for teaching medical students the appropriate selection of imaging tests: randomized cross-over evaluation.European radiology · 2020Trial
- Article
- Impact of a Clinical Decision Support System on CT Pulmonary Angiography Yield and Utilization in Hospitalized Patients.Journal of the American College of Radiology : JACR · 2025Article
- CT Pulmonary Angiogram Clinical Pretest Probability Tool: Impact on Emergency Department Utilization.Journal of the American College of Radiology : JACR · 2024Article
- Machine Learning Model Drift: Predicting Diagnostic Imaging Follow-Up as a Case Example.Journal of the American College of Radiology : JACR · 2022Article
- Article
- Can emergency department provider notes help to achieve more dynamic clinical decision support?Journal of the American College of Emergency Physicians open · 2020Article
- Physician Agreement With Recommendations Contained in a National Guideline for the Management of Incidental Pulmonary Nodules: A Case Study.Journal of the American College of Radiology : JACR · 2020Article
- Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study.JMIR medical informatics · 2019Article
- Impact of a Health Information Technology-Enabled Appropriate Use Criterion on Utilization of Emergency Department CT for Renal Colic.AJR. American journal of roentgenology · 2019Article
- Characteristics of knowledge content in a curated online evidence library.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveFor health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations.
methodsThe annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence.
resultsEighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99).
conclusionsA novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams.
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Registered trials
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.