| Autor: |
Riya Pulicharam, Stephen D. Silberstein, Anand R. Shewale, Robert Cowan, Karen Campbell, Richard B. Lipton, Justin S. Yu, Hema N. Viswanathan, Firas Dabbous, Jelena M. Pavlovic, Jonathan W. Kowalski, Michael L. Reed, Steve H. Kawahara |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Cephalalgia : an international journal of headache. 39(4) |
| ISSN: |
1468-2982 |
| Popis: |
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 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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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