Journal of Medical Economics | 2019

Treatment patterns and predictors of costs among patients with migraine: evidence from the United States medical expenditure panel survey

 
 
 
 
 

Abstract


Abstract Aim: Within a treated migraine population, to evaluate if the sub-group meeting criteria for high disease-specific total costs is significantly different to the sub-group with medium and/or low-costs, and to identify the associated risk factors. Methods: Data from the Household Component of Medical Expenditure Panel Survey (MEPS-HC, 2008–2012), a nationally representative survey of non-institutionalized civilians in the US, were analyzed. Key inclusion criteria were migraine diagnosis (ICD-9 code: 346.XX) and prescribed treatment for migraine. Patients were categorized into high (>top 10th percentile), low (<bottom 10th percentile), and medium (between high and low) cost sub-groups per migraine-specific total costs. Logistic regression models were applied to identify predictors of high vs medium and medium vs low-costs. Preventive eligibility, defined as (i) past/current use of migraine preventives or (ii) overuse of acute medications, was compared to non-preventive eligibility. Results: Within the treated migraine cohort (n\u2009=\u20091,735), the mean age was 39\u2009years, 80% were female, and the majority were in the medium-cost sub-group (n\u2009=\u20091,360) (low-cost n\u2009=\u2009190, high-cost n\u2009=\u2009195). Significant predictors of high vs medium-costs were low SF-12 Physical Composite Scores (OR\u2009=\u20090.95; 95% CI\u2009=\u20090.92–0.97), low SF-6D health utility index scores (OR\u2009=\u20090.019; 95% CI\u2009=\u20090.002–0.193), preventive eligibility-i (OR\u2009=\u20090.019; 95% CI\u2009=\u20090.002–0.193), and preventive-eligibility-ii (OR\u2009=\u20093.10; 95% CI\u2009=\u20091.62–5.91). Statistically significant (p\u2009<\u20090.05) predictors of medium vs low-costs included anxiety, Fleishman score, preventive-eligible-i, and preventive-eligible-ii. Conclusions: Among patients treated for migraine, distinct characteristics, including patient-functioning measures and comorbidities, are predictive of high vs medium-costs, and medium vs low-costs. Preventive eligibility is a predictor of being in the higher cost sub-groups; however, preventive treatments that improve functioning and reduce acute medication use have the potential to reduce migraine-specific costs. Limitations: The results are limited to a population that is diagnosed and treated for migraine. Over-the-counter medication use, and migraine headache frequency and severity were not captured.

Volume 22
Pages 849 - 858
DOI 10.1080/13696998.2019.1607358
Language English
Journal Journal of Medical Economics

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