%0 Journal Article
%T Development of a claims
%A Anand R Shewale
%A Firas Dabbous
%A Hema N Viswanathan
%A Jelena M Pavlovic
%A Jonathan W Kowalski
%A Justin S Yu
%A Karen L Campbell
%A Michael L Reed
%A Richard B Lipton
%A Riya Pulicharam
%A Robert P Cowan
%A Stephen D Silberstein
%A Steve H Kawahara
%J Cephalalgia
%@ 1468-2982
%D 2019
%R 10.1177/0333102418825373
%X To develop a claims-based algorithm to identify undiagnosed chronic migraine among patients enrolled in a healthcare system. An observational study using claims and patient survey data was conducted in a large medical group. Eligible patients had an International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) migraine diagnosis, without a chronic migraine diagnosis, in the 12 months before screening and did not have a migraine-related onabotulinumtoxinA claim in the 12 months before enrollment. Trained clinicians administered a semi-structured diagnostic interview, which served as the gold standard to diagnose chronic migraine, to enrolled patients. Potential claims-based predictors of chronic migraine that differentiated semi-structured diagnostic interview-positive (chronic migraine) and semi-structured diagnostic interview-negative (non-chronic migraine) patients were identified in bivariate analyses for inclusion in a logistic regression model. The final sample included 108 patients (chronic migraine£¿=£¿64; non-chronic migraine£¿=£¿44). Four significant predictors for chronic migraine were identified using claims in the 12 months before enrollment: ¡Ư15 versus <15 claims for acute treatment of migraine, including opioids (odds ratio£¿=£¿5.87 [95% confidence interval: 1.34¨C25.63]); ¡Ư24 versus <24 healthcare visits (odds ratio£¿=£¿2.80 [confidence interval: 1.08¨C7.25]); female versus male sex (odds ratio£¿=£¿9.17 [confidence interval: 1.26¨C66.50); claims for ¡Ư2 versus 0 unique migraine preventive classes (odds ratio£¿=£¿4.39 [confidence interval: 1.19¨C16.22]). Model sensitivity was 78.1%; specificity was 72.7%. The claims-based algorithm identified undiagnosed chronic migraine with sufficient sensitivity and specificity to have potential utility as a chronic migraine case-finding tool using health claims data. Research to further validate the algorithm is recommended
%K Chronic migraine
%K diagnosis predictors
%K case-finding tool
%K health claims data
%U https://journals.sagepub.com/doi/full/10.1177/0333102418825373