Current treatment status and medical cost for multiple sclerosis based on analysis of a Japanese claims database. Issue 2 (23rd March 2016)

• Record Type: Journal Article
• Authors: Ogino, Mieko; Kawachi, Izumi; Otake, Kazuyoshi; Ohta, Hiroyuki; Otsuka, Yujiro; Iwasaki, Kosuke; Hiroi, Shinzo
• Is Part Of: Clinical & experimental neuroimmunology. Volume 7:Issue 2(2016)
• Page Start: 158
• Page End: 167
• Publication Date: 2016-03-23
• Subjects: claims database -- disease‐modifying therapy -- health economics -- multiple sclerosis; 616.80479
• DOI: 10.1111/cen3.12299
• Languages: English
• ISSNs: 1759-1961

Abstract

Abstract: Objective: To assist policymakers as they reflect on treatment protocols and approaches for the efficient delivery of medical care for multiple sclerosis (MS) patients in Japan. Methods: We analyzed data from a large Japanese health insurance claims database. Using an algorithm based on diagnosis codes, all patients with a diagnosis of MS were identified; patients having a non‐MS demyelinating disease were excluded from the population. MS patient data were used for cross‐sectional analysis carried out on the data collected at a certain period. We identified a total of 1808 MS patients, and we analyzed data for 1133 patients with an observation period of ≥6 months from October 2013 to September 2014. Newly diagnosed MS patients were identified within the MS patients, and their data were used for longitudinal analysis, tracking each patient over a period of time. Results: The total per patient per month cost for MS was ¥93 542 (US$781, €695 as of October 2015). Disease‐modifying therapy drugs costs constituted half of the overall medical costs. For newly diagnosed MS patients, hospitalization costs were the largest component in the initial month, while drug costs were the largest component more than several months after the initial visit. There was a positive correlation between relapse frequency and medical cost. Conclusions: These results provide up‐to‐date information on the demographics, medical treatment and cost status of MS in almost real‐time by using a claims database. They suggest that claims data analysis can effectively support medical policymaking.