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Mult Scler Relat Disord. 2014 Mar;3(2):227-36. doi: 10.1016/j.msard.2013.09.004. Epub 2013 Nov 2.

Burden of multiple sclerosis on direct, indirect costs and quality of life: National US estimates.

Author information

1
University of Colorado, Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA. Electronic address: Jon.Campbell@ucdenver.edu.
2
University of Colorado, Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA. Electronic address: Vahram.Ghushchyan@ucdenver.edu.
3
University of Colorado, Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA. Electronic address: Robert.McQueen@ucdenver.edu.
4
Biogen Idec, Medical and Outcomes Science, Weston, MA, USA. Electronic address: sharon.cahoon-metzger@biogenidec.com.
5
Biogen Idec, Medical and Outcomes Science, Weston, MA, USA. Electronic address: terrie.pang.livingston@biogenidec.com.
6
University of Colorado School of Medicine, Department of Neurology, Aurora, CO, USA. Electronic address: Timothy.Vollmer@ucdenver.edu.
7
University of Colorado School of Medicine, Department of Neurology, Aurora, CO, USA. Electronic address: John.Corboy@ucdenver.edu.
8
University of Colorado School of Medicine, Department of Neurology, Aurora, CO, USA. Electronic address: Augusto.Miravalle@ucdenver.edu.
9
University of Colorado School of Medicine, Department of Neurology, Aurora, CO, USA. Electronic address: Teri.Schreiner@ucdenver.edu.
10
Mastic Beach, NY, USA. Electronic address: veepjean@msn.com.
11
University of Colorado, Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA. Electronic address: kavita.nair@ucdenver.edu.

Abstract

BACKGROUND:

MS imposes a significant burden on patients, caregivers, employers, and the healthcare system.

OBJECTIVE:

To comprehensively evaluate the US MS burden using nationally representative data from the Medical Expenditure Panel Survey.

METHODS:

We identified non-institutionalized patients aged ≥18 with MS (ICD-9 code 340) from 1998 to 2009 and compared them to individuals without an MS diagnosis (non-MS) during the interview year. The cohorts were compared using multivariate regression on direct costs, indirect costs (measured in terms of employment status, annual wages, and workdays missed), and health-related quality of life (HRQoL; measured using Short Form 12, SF-6 Dimensions, and quality-adjusted life years [QALYs]).

RESULTS:

MS prevalence was 572,312 (95% CI: 397,004, 747,619). Annual direct costs were $24,327 higher for the MS population (n=526) vs. the non-MS population (n=270,345) (95% CI: $22,320, $26,333). MS patients had an adjusted 3.3-fold (95% CI: 2.4, 4.5) increase in the odds of not being employed vs. non-MS individuals and a 4.4-fold higher adjusted number of days in bed (95% CI 2.97, 6.45). On average, MS patients lost 10.04 QALYs vs. non-MS cohort.

CONCLUSIONS:

MS was associated with higher healthcare costs across all components, reduced productivity due to unemployment and days spent in bed, and lower HRQoL.

KEYWORDS:

Burden of illness; Direct costs; MEPS; Multiple sclerosis; Quality of life; Reduced productivity

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