Feasibility of creating a National ALS Registry using administrative data in the United States.

Uncertainty about the incidence and prevalence of amyotrophic lateral sclerosis (ALS), as well as the role of the environment in the etiology of ALS, supports the need for a surveillance system/registry for this disease. Our aim was to evaluate the feasibility of using existing administrative data to identify cases of ALS. The Agency for Toxic Substances and Disease Registry (ATSDR) funded four pilot projects at tertiary care facilities for ALS, HMOs, and state based organizations. Data from Medicare, Medicaid, the Veterans Health Administration, and Veterans Benefits Administration were matched to data available from site-specific administrative and clinical databases for a five-year time-period (1 January 2001-31 December 2005). Review of information in the medical records by a neurologist was considered the gold standard for determining an ALS case. We developed an algorithm using variables from the administrative data that identified true cases of ALS (verified by a neurologist). Individuals could be categorized into ALS, possible ALS, and not ALS. The best algorithm had sensitivity of 87% and specificity of 85%. We concluded that administrative data can be used to develop a surveillance system/registry for ALS. These methods can be explored for creating surveillance systems for other neurodegenerative diseases.