Development and validation of a claims-based algorithm to identify patients with Neuromyelitis Optica Spectrum disorder

Abstract

IntroductionNo validated algorithm exists to identify patients with neuromyelitis optica spectrum disorder (NMOSD) in healthcare claims data. We developed and tested the performance of a healthcare claims–based algorithm to identify patients with NMOSD. MethodsUsing medical record data of 101 adults with NMOSD, multiple sclerosis (MS), or myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), we tested the sensitivity and specificity of claims-based algorithms developed through interviews with neurologists. We tested the best-performing algorithm's face validity using 2016–2019 data from IBM MarketScan Commercial and Medicare Supplemental databases. Demographics and clinical characteristics were reported. ResultsAlgorithm inclusion criteria were age ≥ 18 years and (≥1 NMO diagnosis [or ≥ 1 transverse myelitis (TM) and ≥ 1 optic neuritis (ON) diagnosis] and ≥ 1 NMOSD drug) or (≥2 NMO diagnoses ≥90 days apart). Exclusion criteria were MS diagnosis or use of MS-specific drug after last NMO diagnosis or NMOSD drug; sarcoidosis diagnosis after last NMO diagnosis; or use of ≥1 immune checkpoint inhibitor. In medical record billing data of 50 patients with NMOSD, 30 with MS, and 21 with MOGAD, the algorithm had 82.0% sensitivity and 70.6% specificity. When applied to healthcare claims data, demographic and clinical features of the identified cohort were similar to known demographics of NMOSD. ConclusionsThis clinically derived algorithm performed well in medical records. When tested in healthcare claims, demographics and clinical characteristics were consistent with previous clinical findings. This algorithm will enable a more accurate estimation of NMOSD disease burden using insurance claims datasets.