Estimation of the prevalence of amyotrophic lateral sclerosis in the United States using national administrative healthcare data from 2002 to 2004 and capture-recapture methodology
Affiliates | Lorene M. Nelson [1], Barbara Topol [1], Wendy Kaye [2], David Williamson [3], D. Kevin Horton [3], Paul Mehta [3], and Todd Wagner [1,4]
[1] Department of Health Research and Policy, Stanford School of Medicine |
Journal | Neuroepidemiology |
Summary | This study used three sources (Medicare, Medicaid, and Veterans Administration data) to locate persons living with ALS and estimate the prevalence of ALS in the United States for 2002–2004. Additionally, it applied a capture-recapture methodology to estimate the degree to which cases were missing when relying solely on these sources for case identification. Case-finding completeness was 76% overall; this did not vary by race, but by gender and age. Findings from this study suggest that federal healthcare claims databases are very efficient for identifying the majority of ALS-prevalent cases in the National ALS Registry; however, they can be enhanced via patient self-registration in the Registry portal. |
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