Identifying dementia cases with routinely-collected health data: a systematic review

UK Biobank Neurodegenerative Outcomes Group; Dementias Platform UK; Tim Wilkinson; Amanda Ly; Christian Schnier; Kristiina  Rannikmäe; Kathryn Bush; C. Brayne; TJ Quinn; Cathie L. M. Sudlow

doi:10.1016/j.jalz.2018.02.016

Identifying dementia cases with routinely-collected health data: a systematic review

UK Biobank Neurodegenerative Outcomes Group, Dementias Platform UK, Tim Wilkinson, Amanda Ly, Christian Schnier, Kristiina Rannikmäe, Kathryn Bush, C. Brayne, TJ Quinn, Cathie L. M. Sudlow

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

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 healthcare datasets. We evaluated the accuracy of these datasets for dementia case identification.
METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely-collected datasets 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 21-86%. PPVs for Alzheimer’s disease (range 57-100%) were generally higher than for vascular dementia (range 19-91%).
DISCUSSION: Linkage to routine healthcare 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.

Original language	English
Pages (from-to)	1038-1051
Number of pages	14
Journal	Alzheimer's & Dementia: The Journal of the Alzheimer's Association
Volume	14
Issue number	8
Early online date	2 Apr 2018
DOIs	https://doi.org/10.1016/j.jalz.2018.02.016
Publication status	Published - Aug 2018

Keywords / Materials (for Non-textual outputs)

Key words: dementia; Alzheimer disease; dementia, vascular; clinical coding; epidemiology; prospective studies; cohort studies; sensitivity; positive predictive value; predictive value of tests

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10.1016/j.jalz.2018.02.016Licence: Creative Commons: Attribution (CC-BY)

https://www.sciencedirect.com/science/article/pii/S1552526018300700Licence: Creative Commons: Attribution (CC-BY)

Predicting dementia outcomes using simple, non-invasive assessments: a prospective population-based study.
Sudlow, C. & Wilkinson, T.
MRC
1/08/16 → 31/07/19
Project: Research
How do peripheral and central vascular markers relate to cognitive decline? (Project 8)
Deary, I.
UK-based charities
10/08/15 → 31/08/17
Project: Research

Cite this

UK Biobank Neurodegenerative Outcomes Group, Dementias Platform UK, Wilkinson, T., Ly, A., Schnier, C., Rannikmäe, K., Bush, K., Brayne, C., Quinn, TJ., & Sudlow, C. L. M. (2018). Identifying dementia cases with routinely-collected health data: a systematic review. Alzheimer's & Dementia: The Journal of the Alzheimer's Association, 14(8), 1038-1051. https://doi.org/10.1016/j.jalz.2018.02.016

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title = "Identifying dementia cases with routinely-collected health data: a systematic review",

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 healthcare datasets. We evaluated the accuracy of these datasets for dementia case identification.METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely-collected datasets 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 21-86%. PPVs for Alzheimer{\textquoteright}s disease (range 57-100%) were generally higher than for vascular dementia (range 19-91%).DISCUSSION: Linkage to routine healthcare 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. ",

keywords = "Key words: dementia; Alzheimer disease; dementia, vascular; clinical coding; epidemiology; prospective studies; cohort studies; sensitivity; positive predictive value; predictive value of tests",

author = "{UK Biobank Neurodegenerative Outcomes Group} and {Dementias Platform UK} and Tim Wilkinson and Amanda Ly and Christian Schnier and Kristiina Rannikm{\"a}e and Kathryn Bush and C. Brayne and TJ Quinn and Sudlow, {Cathie L. M.}",

year = "2018",

month = aug,

doi = "10.1016/j.jalz.2018.02.016",

language = "English",

volume = "14",

pages = "1038--1051",

journal = "Alzheimer's & Dementia: The Journal of the Alzheimer's Association",

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UK Biobank Neurodegenerative Outcomes Group, Dementias Platform UK, Wilkinson, T, Ly, A, Schnier, C, Rannikmäe, K, Bush, K, Brayne, C, Quinn, TJ & Sudlow, CLM 2018, 'Identifying dementia cases with routinely-collected health data: a systematic review', Alzheimer's & Dementia: The Journal of the Alzheimer's Association, vol. 14, no. 8, pp. 1038-1051. https://doi.org/10.1016/j.jalz.2018.02.016

TY - JOUR

T1 - Identifying dementia cases with routinely-collected health data: a systematic review

AU - UK Biobank Neurodegenerative Outcomes Group

AU - Dementias Platform UK

AU - Wilkinson, Tim

AU - Ly, Amanda

AU - Schnier, Christian

AU - Rannikmäe, Kristiina

AU - Bush, Kathryn

AU - Brayne, C.

AU - Quinn, TJ

AU - Sudlow, Cathie L. M.

PY - 2018/8

Y1 - 2018/8

N2 - 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 healthcare datasets. We evaluated the accuracy of these datasets for dementia case identification.METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely-collected datasets 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 21-86%. PPVs for Alzheimer’s disease (range 57-100%) were generally higher than for vascular dementia (range 19-91%).DISCUSSION: Linkage to routine healthcare 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.

AB - 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 healthcare datasets. We evaluated the accuracy of these datasets for dementia case identification.METHODS: We systematically reviewed the literature for studies comparing dementia coding in routinely-collected datasets 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 21-86%. PPVs for Alzheimer’s disease (range 57-100%) were generally higher than for vascular dementia (range 19-91%).DISCUSSION: Linkage to routine healthcare 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.

KW - Key words: dementia; Alzheimer disease; dementia, vascular; clinical coding; epidemiology; prospective studies; cohort studies; sensitivity; positive predictive value; predictive value of tests

U2 - 10.1016/j.jalz.2018.02.016

DO - 10.1016/j.jalz.2018.02.016

M3 - Article

SN - 1552-5260

VL - 14

SP - 1038

EP - 1051

JO - Alzheimer's & Dementia: The Journal of the Alzheimer's Association

JF - Alzheimer's & Dementia: The Journal of the Alzheimer's Association

IS - 8

ER -

Identifying dementia cases with routinely-collected health data: a systematic review

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Keywords / Materials (for Non-textual outputs)

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Projects

Predicting dementia outcomes using simple, non-invasive assessments: a prospective population-based study.

How do peripheral and central vascular markers relate to cognitive decline? (Project 8)

Cite this