Repository logo
 

Identifying dementia cases with routinely collected health data: A systematic review.

Published version
Peer-reviewed

Change log

Authors

Wilkinson, Tim 
Ly, Amanda 
Schnier, Christian 
Rannikmäe, Kristiina 
Bush, Kathryn 

Abstract

INTRODUCTION: Prospective, population-based studies can be rich resources for dementia research. Follow-up in many such studies is through linkage to routinely collected, coded health-care data sets. We evaluated the accuracy of these data sets for dementia case identification. METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely collected data sets to any expert-led reference standard. We recorded study characteristics and two accuracy measures-positive predictive value (PPV) and sensitivity. RESULTS: We identified 27 eligible studies with 25 estimating PPV and eight estimating sensitivity. Study settings and methods varied widely. For all-cause dementia, PPVs ranged from 33%-100%, but 16/27 were >75%. Sensitivities ranged from 21% to 86%. PPVs for Alzheimer's disease (range 57%-100%) were generally higher than those for vascular dementia (range 19%-91%). DISCUSSION: Linkage to routine health-care data can achieve a high PPV and reasonable sensitivity in certain settings. Given the heterogeneity in accuracy estimates, cohorts should ideally conduct their own setting-specific validation.

Description

Keywords

Alzheimer's disease, Clinical coding, Cohort studies, Dementia, Epidemiology, Positive predictive value, Predictive value of tests, Prospective studies, Sensitivity, Vascular, Alzheimer Disease, Clinical Coding, Data Collection, Delivery of Health Care, Dementia, Vascular, Humans, Sensitivity and Specificity

Journal Title

Alzheimers Dement

Conference Name

Journal ISSN

1552-5260
1552-5279

Volume Title

14

Publisher

Wiley