Reducing case ascertainment costs in U.S. population studies of Alzheimer's disease, dementia, and cognitive impairment-Part 1.

TitleReducing case ascertainment costs in U.S. population studies of Alzheimer's disease, dementia, and cognitive impairment-Part 1.
Publication TypeJournal Article
Year of Publication2011
AuthorsWeir, DR, Wallace, RB, Langa, KM, Plassman, BL, Wilson, RS, Bennett, DA, Duara, R, Loewenstein, D, Ganguli, M, Sano, M
JournalAlzheimers Dement
Volume7
Issue1
Pagination94-109
Date Published2011 Jan
ISSN Number1552-5279
Call Numbernewpubs20110328_Weir.pdf
KeywordsAging, Algorithms, Alzheimer disease, Cognition Disorders, Community Health Planning, Cost-Benefit Analysis, Dementia, Health Surveys, Humans, Internet, Reproducibility of Results, United States
Abstract

Establishing methods for ascertainment of dementia and cognitive impairment that are accurate and also cost-effective is a challenging enterprise. Large population-based studies often using administrative data sets offer relatively inexpensive and reliable estimates of severe conditions including moderate to advanced dementia that are useful for public health planning, but they can miss less severe cognitive impairment which may be the most effective point for intervention. Clinical and epidemiological cohorts, intensively assessed, provide more sensitive detection of less severe cognitive impairment but are often costly. In this article, several approaches to ascertainment are evaluated for validity, reliability, and cost. In particular, the methods of ascertainment from the Health and Retirement Study are described briefly, along with those of the Aging, Demographics, and Memory Study (ADAMS). ADAMS, a resource-intense sub-study of the Health and Retirement Study, was designed to provide diagnostic accuracy among persons with more advanced dementia. A proposal to streamline future ADAMS assessments is offered. Also considered are algorithmic and Web-based approaches to diagnosis that can reduce the expense of clinical expertise and, in some contexts, can reduce the extent of data collection. These approaches are intended for intensively assessed epidemiological cohorts where goal is valid and reliable case detection with efficient and cost-effective tools.

URLhttp://mgetit.lib.umich.edu/sfx_local?ctx_enc=info 3Aofi 2Fenc 3AUTF-8;ctx_id=10_1;ctx_tim=2011-03-28T16 3A26 3A0EDT;ctx_ver=Z39.88-2004;rfr_id=info 3Asid 2Fsfxit.com 3Acitation;rft.genre=article;rft_id=info 3Apmid 2F21255747;rft_val_fmt=info 3Aofi 2Ffmt
DOI10.1016/j.jalz.2010.11.004
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/21255747?dopt=Abstract

Endnote Keywords

Alzheimers disease/Dementia/Mild cognitive impairment/Cognitive impairment not dementia/Diagnostic algorithms/Cognition/Epidemiology/Screening/Technology/Education/Ethnicity

Endnote ID

24600

Alternate JournalAlzheimers Dement
Citation Key7566
PubMed ID21255747
PubMed Central IDPMC3044596
Grant ListP50AG025711 / AG / NIA NIH HHS / United States
K24AG022035 / AG / NIA NIH HHS / United States
R01 AG017917 / AG / NIA NIH HHS / United States
R01AG030561 / AG / NIA NIH HHS / United States
P30 AG010161 / AG / NIA NIH HHS / United States
K24 AG022035 / AG / NIA NIH HHS / United States
P30AG010161 / AG / NIA NIH HHS / United States
R01AG015819 / AG / NIA NIH HHS / United States
U01 AG009740 / AG / NIA NIH HHS / United States
P50AG005138 / AG / NIA NIH HHS / United States
R01AG017917 / AG / NIA NIH HHS / United States
R01 AG023651 / AG / NIA NIH HHS / United States
U01AG009740 / AG / NIA NIH HHS / United States
P50 AG005138 / AG / NIA NIH HHS / United States
P50 AG025711 / AG / NIA NIH HHS / United States
R01AG023651 / AG / NIA NIH HHS / United States
R01 AG015819 / AG / NIA NIH HHS / United States
U01 AG009740-21 / AG / NIA NIH HHS / United States