Title | Reducing case ascertainment costs in U.S. population studies of Alzheimer's disease, dementia, and cognitive impairment-Part 1. |
Publication Type | Journal Article |
Year of Publication | 2011 |
Authors | Weir, DR, Wallace, RB, Langa, KM, Plassman, BL, Wilson, RS, Bennett, DA, Duara, R, Loewenstein, D, Ganguli, M, Sano, M |
Journal | Alzheimers Dement |
Volume | 7 |
Issue | 1 |
Pagination | 94-109 |
Date Published | 2011 Jan |
ISSN Number | 1552-5279 |
Call Number | newpubs20110328_Weir.pdf |
Keywords | Aging, 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. |
URL | http://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 |
DOI | 10.1016/j.jalz.2010.11.004 |
User Guide Notes | |
Endnote Keywords | Alzheimers disease/Dementia/Mild cognitive impairment/Cognitive impairment not dementia/Diagnostic algorithms/Cognition/Epidemiology/Screening/Technology/Education/Ethnicity |
Endnote ID | 24600 |
Alternate Journal | Alzheimers Dement |
Citation Key | 7566 |
PubMed ID | 21255747 |
PubMed Central ID | PMC3044596 |
Grant List | P50AG025711 / 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 |