OBJECTIVES

Multiple sclerosis (MS) is a chronic autoimmune disease that impacts the central nervous system and is characterized by demyelination, resulting in a range of severe symptoms. The estimated 400,000 people in the US with MS have significantly reduced health-related quality-of-life, increased mortality and morbidity, and increased healthcare costs. Currently, few claims-based algorithms are available to predict disease severity. This study replicated a previously developed predictive algorithm which estimated disease severity.

METHODS

: A sample of 7,972 Medicare patients with Humana US adjudicated claims (2007 -2012) was used to develop a regression model predicting total healthcare costs (excluding disease modifying therapy, or DMT) during the 12-month follow-up period. A 12-month baseline period was used to capture potential predictors of severity and costs: MS symptoms, DMT use (oral/injection/intravenous), durable medical equipment (DME) use (yes/no), number of MS-related hospitalizations, and number of MS relapses. In addition, weights were assigned to these predictors based on the previous algorithm to calculate a MS disease severity score, which was then mapped to follow-up healthcare costs (excluding DMTs).

RESULTS

: Although the overall multiple regression was statistically significant (p = 0.0001), it explained less than 10% of the variation in total healthcare costs (excluding DMT) during the follow-up period (r² = 0.08). Eye, speech, sensory, brainstem and pyramidal symptoms, as well as DMT or DME use, were not statically significant. When weights from the previous algorithm were assigned to the predictors in order to calculate MS disease severity scores, the coefficient of determination (r²= 0.76) comparing severity scores with total healthcare costs (excluding DMT) was 76%.

CONCLUSIONS

: The multiple regression using the same predictors was adequate in predicting total health care (cost excluding DMT cost). The MS disease severity scores were strongly correlated with total healthcare cost (excluding DMT). Further study is needed to validate this further.