Journal Article
Research Support, Non-U.S. Gov't
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Determinants of high cost in multiple sclerosis patients: a claims and chart review study.

OBJECTIVE: To identify factors associated with high cost multiple sclerosis (MS) patients using integrated administrative claims and medical charts data.

METHODS: This study identified newly diagnosed MS patients (≥18 years) in a large United States managed care claims database between 1 January 2007 and 30 April 2011 using the ICD-9-CM code (340.xx). Mean annualized MS-related costs higher than the third quartile were categorized as high cost, lower than the first quartile as low, and the rest as medium. Patients were compared across cohorts with descriptive and inferential statistics. Baseline high cost factors were identified with multivariable logistic regression models.

RESULTS: Administrative claims (n = 4342) and medical chart records (n = 400) data was evaluated. Mean (SD) annualized MS-related costs were $6313 ($14,177) for patients overall and $18,398 ($24,483) for high cost patients. Inpatient costs accounted for the largest proportion (49.69%) of MS-related costs among high cost patients. MS relapses and MS-related comorbidities were more prevalent in the high cost patients. In the multivariable analyses, patients with baseline use of antidepressants or corticosteroids, baseline muscle weakness, and initial treatment from a non-neurologist were likelier to be high cost MS patients.

LIMITATIONS: MS-related clinical information was not completely available from medical chart data. The specificity of true MS-related costs may have been limited and the definition of the cost-based cohort segmentations was arbitrary.

CONCLUSIONS: Overall, baseline use of MS-related medications, the presence of baseline MS-related comorbidities, MS relapses, and MS-related hospitalizations were significantly associated with high cost patients. Future comparative effectiveness studies of currently approved disease modifying therapies for MS may help to identify best strategies for individual patients to minimize clinical events that are associated with high disease related costs.

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