Summaries of Must-Read Clinical Literature, Guidelines, and FDA Actions
An Algorithm for Undiagnosed Chronic Migraine
Cephalalgia; ePub 2019 Mar 9; Pavlovic, et al
A claims-based algorithm identified undiagnosed chronic migraine with sufficient sensitivity and specificity and may have potential as a chronic migraine case-finding tool using claims data, a new study found. The observational study using claims and patient survey data was conducted in a large medical group. Eligible patients had an ICD-9/10 migraine diagnosis, without a chronic migraine diagnosis, in the 12 months before screening. Researchers found:
- The final study sample included 108 patients (chronic migraine=64; non-chronic migraine=44).
- 4 significant predictors for chronic migraine were identified using claims in the 12 months before enrollment: ≥15 vs <15 claims for acute treatment of migraine, including opioids; ≥24 vs <24 healthcare visits ; female vs male sex; and claims for ≥2 vs 0 unique migraine preventive classes.
- Model sensitivity was 78.1%, specificity was 72.7%.
Pavlovic JM, Yu JS, Siberstein SD, et al. Development of a claims-based algorithm to identify potentially undiagnosed chronic migraine patients. [Published online ahead of print March 9, 2019]. Cephalalgia. doi:10.1177/0333102418825373.
Chronic migraine (CM) is more disabling than episodic migraine (EM), and patients with CM accrue much more direct and indirect costs (Headache 2016;56:306-322). There are 4 FDA approved medications for CM as of April of 2019, onabotulinumtoxinA, erenumab, fremanezumab, and galcanezumab, so targeted care may result in improved outcome if proper diagnosis can be made. This algorithm attempted to find those patients in a large health care system in whom the CM diagnosis was not made in order to identify them for potential therapeutic interventions. Since costs are known to be higher for CM patients, it is not surprising to find that for migraine patients higher health care utilization predicts CM diagnosis, in both number of claims for acute and preventive migraine medications and higher frequency of health care visits. This algorithm may prove to be useful for both diagnosis and subsequent treatments in health care systems. — Stewart J. Tepper, MD, FAHS, Professor of Neurology, Geisel School of Medicine at Dartmouth, Director, Dartmouth Headache Center, Dartmouth-Hitchcock Medical Center, Lebanon, NH