Development and Validation of Algorithms for Systemic Sclerosis Identification in Electronic Health Record Data
Gulsen Ozen; Michael O'Rorke; Paul Romitti; Robyn Domsic · 2026 · ACR Open Rheumatology
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Objective The aim of this study was to develop and validate International Classification of Diseases (ICD) code–based algorithms for identifying systemic sclerosis (SSc) cases within electronic health record (EHR) data and to evaluate algorithm performance. Methods We identified patients with at least one ICD, Ninth Revision (ICD‐9)/ICD‐10 code for SSc in a large multicenter EHR dataset (TriNetX Research Network). A random sample of patients underwent detailed medical record review to confirm SSc diagnosis (gold standard). All ICD‐9/10 codes assigned during inpatient or outpatient encounters a
Abstract by Gulsen Ozen; Michael O'Rorke; Paul Romitti; Robyn Domsic, ACR Open Rheumatology (2026) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.1002/acr2.90091