SynthesisArthritis care & research2026
Accuracy of Diagnostic Codes and Algorithms Used to Identify Rheumatoid Arthritis and Juvenile Idiopathic Arthritis in Administrative Claims and Electronic Health Records: Systematic Review and Meta-Analysis.
Synthesis in Arthritis care & research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between COVID-19 and New-Onset Autoimmune Diseases: Updated Systematic Review and Meta-Analysis of 97 Million Individuals.Clinical reviews in allergy & immunology · 2025Pooled it
- Association of Clonal Hematopoiesis With Incident, Late-Onset, Seropositive Rheumatoid Arthritis.Arthritis & rheumatology (Hoboken, N.J.) · 2026Article
- Physical activity, genetic predisposition and the risk of rheumatoid arthritis: a prospective cohort study.Frontiers in sports and active living · 2026Article
- Technophobia and Its Associated Factors Among Registered Nurses in China: A Cross-Sectional Multicenter Study.Journal of nursing management · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
objectiveThis systematic review aimed to assess the diagnostic accuracy of algorithms used to identify rheumatoid arthritis and juvenile idiopathic arthritis in electronic health records.
methodsWe searched Medline, Embase, and Cochrane Central Register for Controlled Trials databases and included studies that validated case definitions against a reference standard, such as rheumatologist-confirmed diagnosis or American College of Rheumatology/EULAR classification criteria. Title and abstract screening, full-text review, data extraction, and quality assessment were all completed in duplicate. Results were synthesized narratively and using a bivariate random-effects meta-analysis of sensitivity and specificity.
resultsA total of 35 studies were included. Algorithms varied widely in complexity, ranging from single International Classification of Diseases (ICD) codes to combinations including disease-modifying antirheumatic drugs (DMARDs), hospitalization records, and specialist diagnosis. Algorithms combining ICD codes with DMARD prescriptions (pooled sensitivity 0.79 [95% confidence interval (CI) 0.61-0.90], specificity 0.96 [95% CI 0.72-1.00], positive predictive value [PPV] 0.78 [95% CI 0.63-0.88]) or requiring an ICD code assigned by a rheumatologist (pooled sensitivity 0.91 [95% CI 0.70-0.98], specificity 0.94 [95% CI 0.49-1.00], PPV 0.70 [95% CI 0.64-0.75]) showed the highest accuracy, with balanced sensitivity, specificity, and PPV. Less restrictive algorithms demonstrated high sensitivity but lower PPV. Substantial heterogeneity was observed across studies, likely due to differences in algorithm structure, data sources, and validation methods. Despite this variability, we used conceptually coherent categories to allow for meaningful synthesis, prioritizing clinical interpretability.
conclusionsThese findings support the use of more specific algorithms when diagnostic certainty is essential and highlight the need for further validation of high-performing algorithms across diverse health care systems.
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