Dataset Information

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.

ABSTRACT:

Background

National administrative healthcare data may be used as a case-finding method for prevalence studies of chronic disease in the United States, but the completeness of ascertainment likely varies depending on the disease under study.

Methods

We used 3 case-finding sources (Medicare, Medicaid, and Veterans Administration data) to estimate the prevalence of amyotrophic lateral sclerosis (ALS) in the United States for 2002-2004, and applied the capture-recapture methodology to estimate the degree of under-ascertainment when relying solely on these sources for case identification.

Results

Case-finding completeness was 76% overall and did not vary by race, but was lower for males (77%) than for females (88%), and lower for patients under age 65 (66%) than patients over age 65 (79%). The uncorrected ALS prevalence ratio was 2.8/100,000 in 2002, 3.3/100,000 in 2003, and 3.7/100,000 in 2004. After correcting for under-ascertainment, the annual prevalence increased by approximately 1 per 100,000 to 3.7/100,000 in 2002 (95% CI 3.66-3.80), 4.4/100,000 in 2003 (95% CI 4.34-4.50), and 4.8/100,000 in 2004 (95% CI 4.76-4.91).

Conclusions

Federal healthcare claims databases ascertained are a very efficient method for identifying the majority of ALS-prevalent cases in the National ALS Registry, and may be enhanced by having patients self-register through the registry web portal.

SUBMITTER: Nelson LM

PROVIDER: S-EPMC6250049 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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.

Nelson Lorene M LM Topol Barbara B Kaye Wendy W Williamson David D Horton D Kevin DK Mehta Paul P Wagner Todd T

Neuroepidemiology 20180809 3-4

<h4>Background</h4>National administrative healthcare data may be used as a case-finding method for prevalence studies of chronic disease in the United States, but the completeness of ascertainment likely varies depending on the disease under study.<h4>Methods</h4>We used 3 case-finding sources (Medicare, Medicaid, and Veterans Administration data) to estimate the prevalence of amyotrophic lateral sclerosis (ALS) in the United States for 2002-2004, and applied the capture-recapture methodology t ...[more]

PMID: 30092573

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Project description:Estimating population sizes has long been of interest, from the estimation of the human or ecological population size within regions or countries to the hidden number of civilian casualties in a war. Total enumeration of the population, for example, via a census, is often infeasible or simply impractical. However, a series of partial enumerations or observations of the population is often possible. This has led to the ideas of capture-recapture methods, which have been extensively used within ecology to estimate the size of wildlife populations, with an associated measure of uncertainty, and are most effectively applied when there are multiple capture occasions. Capture-recapture ideology can be more widely applied to multiple data-sources, by the linkage of individuals across the multiple lists. This is often referred to as Multiple Systems Estimation (MSE). The MSE approach has been preferred when estimating "capture-shy" or hard-to-reach populations, including those caught up in the criminal justice system; or homeless; or trafficked; or civilian casualties of war. Motivated by a range of public policy applications of MSE, each briefly introduced, we discuss practical problems with potentially substantial methodological implications. They include: "period" definition; "case" definition; when an observed count is not a true count of the population of interest but an upper bound due to mismatched definitions; exact or probabilistic matching of "cases" across different lists; demographic or other information about the "case" which may influence capture-propensities; required permissions to access extant-lists; list-creation by research-teams or interested parties; referrals (if presence on list A results - almost surely - in presence on list B); different mathematical models leading to widely different estimated population sizes; uncertainty in estimation; computational efficiency; external validation; hypothesis-generation; and additional independent external information. Returning to our motivational applications, we focus on whether the uncertainty which qualified their estimates was sufficiently narrow to orient public policy; and, if not, what options were available and/or taken to reduce the uncertainty or to seek external validation. We also consider whether MSE was hypothesis-generating: in the sense of having spawned new lines of inquiry.

Dataset Information

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.

Background

Methods

Results

Conclusions

Publications

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.

Similar Datasets

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