Pharmacy and medical claims data identified migraine sufferers with high specificity but modest sensitivity

Abstract

Objective: Claims data are often used to identify and monitor individuals with particular conditions, but many health conditions are not easily recognizable from claims data alone. Patient characteristics routinely available in claims data were used to develop model-based claims signatures to identify migraineurs.

Study design and setting: A validated telephone interview was administered to 23,299 continuously enrolled managed care members aged 18-55 to identify 1,265 migraineurs and 1,178 controls. Responses were linked to medical and prescription claims. Claims variables were evaluated for sensitivity, specificity, and positive and negative predictive value in predicting migraine status. Regression models for predicting migraine status were developed.

Results: Regression-based claims signature models were successful in case-finding, as indicated by fairly sizable odds ratios (OR). In the full model (including demographic, medical, pharmacy, and comorbidity claims variables), a claim for a migraine drug, gender, and a claims-based headache diagnosis were strongly associated with migraine case status (OR=3.9, 3.2, and 3.0, respectively).

Conclusion: Using either medical or pharmacy claims provided highly specific and moderately sensitive case-findings. Strategies that combined medical and pharmacy information improved sensitivity and may increase the usefulness of claims for identifying migraine and improving the quality of migraine care.