Abstract
Objective: To develop a claims-based algorithm to identify undiagnosed chronic migraine among patients enrolled in a healthcare system. Methods: 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. Results: 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: ≥15 versus <15 claims for acute treatment of migraine, including opioids (odds ratio = 5.87 [95% confidence interval: 1.34–25.63]); ≥24 versus <24 healthcare visits (odds ratio = 2.80 [confidence interval: 1.08–7.25]); female versus male sex (odds ratio = 9.17 [confidence interval: 1.26–66.50); claims for ≥2 versus 0 unique migraine preventive classes (odds ratio = 4.39 [confidence interval: 1.19–16.22]). Model sensitivity was 78.1%; specificity was 72.7%. Conclusions: 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.
Original language | English (US) |
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Pages (from-to) | 465-476 |
Number of pages | 12 |
Journal | Cephalalgia |
Volume | 39 |
Issue number | 4 |
DOIs | |
State | Published - Apr 1 2019 |
Keywords
- Chronic migraine
- case-finding tool
- diagnosis predictors
- health claims data
ASJC Scopus subject areas
- Clinical Neurology