Study Description

Objective

To generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets.

Data Source

Several AHC datasets representing the US private and government-sponsored insurance programs which included Optum (OP), Truven Health (TH), Kaiser Permanente Southern California (KPSC), Centers for Medicare & Medicaid Services, Department of Defense and Veteran Affairs.

Methods

A validated algorithm was applied to each dataset, to determine the 3-year cumulative prevalence overall and stratified by age, sex, and census region for adults (≥18 years of age). Insurance-specific and stratum-specific estimates were applied to the 2010 US Census data. The findings were pooled to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. The study estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated the estimate to 2017.

Study Outcomes

Estimated 2010 US MS prevalence accumulated over 10 years. Also, extrapolated date to 2017 prevalence.

Generalizability

Results may not be generalizable to the entire US population. This study assessed 100% of publicly funded population but not the uninsured population or children 18 years of age within the US.

Limitations

• The study did not include children, the Indian Health Service, the US prison system, or undocumented US residents in our prevalence estimates.
• Those with MS not followed in the traditional health care system (e.g., alternative medicine or cash health care practices that bypass health insurance reimbursement) would be missed by our method. This would result in an underestimate of MS cases.
• Study did not characterize the racial or ethnic demographics of our MS population in this report because race and ethnicity were not uniformly collected in the AHC datasets used.
• The majority of datasets, except VA, contained less than 10 years of data.