Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.

<h4>Background</h4>The ability to perform basic daily activities ("functional status") is key to older adults' quality of life and strongly predicts health outcomes. However, data on functional status are seldom collected during routine clinical care in a way that makes th...

Full description

Bibliographic Details
Main Authors: Rebecca T Brown, Kiya D Komaiko, Ying Shi, Kathy Z Fung, W John Boscardin, Alvin Au-Yeung, Gary Tarasovsky, Riya Jacob, Michael A Steinman
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0178726
id doaj-d93f5d0a7e094ef38c8269d7963b1a7d
record_format Article
spelling doaj-d93f5d0a7e094ef38c8269d7963b1a7d2021-03-04T05:52:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01126e017872610.1371/journal.pone.0178726Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.Rebecca T BrownKiya D KomaikoYing ShiKathy Z FungW John BoscardinAlvin Au-YeungGary TarasovskyRiya JacobMichael A Steinman<h4>Background</h4>The ability to perform basic daily activities ("functional status") is key to older adults' quality of life and strongly predicts health outcomes. However, data on functional status are seldom collected during routine clinical care in a way that makes them available for clinical use and research.<h4>Objectives</h4>To validate functional status data that Veterans Affairs (VA) medical centers recently started collecting during routine clinical care, compared to the same data collected in a structured research setting.<h4>Design</h4>Prospective validation study.<h4>Setting</h4>Seven VA medical centers that collected complete data on 5 activities of daily living (ADLs) and 8 instrumental activities of daily living (IADLs) from older patients attending primary care appointments.<h4>Participants</h4>Randomly selected patients aged 75 and older who had new ADL and IADL data collected during a primary care appointment (N = 252). We oversampled patients with ADL dependence and applied these sampling weights to our analyses.<h4>Measurements</h4>Telephone-based interviews using a validated measure to assess the same 5 ADLs and 8 IADLs.<h4>Results</h4>Mean age was 83 years, 96% were male, and 75% were white. Of 85 participants whom VA data identified as dependent in 1 or more ADLs, 74 (87%) reported being dependent by interview; of 167 whom VA data identified as independent in ADLs, 149 (89%) reported being independent. The sample-weighted sensitivity of the VA data for identifying ADL dependence was 45% (95% CI, 29%, 62%) compared to the reference standard, the specificity was 99% (95% CI, 99%, >99%), and the positive predictive value was 87% (95% CI, 79%, 93%). The weighted kappa statistic was 0.55 (95% CI, 0.41, 0.68) for the agreement between VA data and research-collected data in identifying ADL dependence.<h4>Conclusion</h4>Overall agreement of VA functional status data with a reference standard was moderate, with fair sensitivity but high specificity and positive predictive value.https://doi.org/10.1371/journal.pone.0178726
collection DOAJ
language English
format Article
sources DOAJ
author Rebecca T Brown
Kiya D Komaiko
Ying Shi
Kathy Z Fung
W John Boscardin
Alvin Au-Yeung
Gary Tarasovsky
Riya Jacob
Michael A Steinman
spellingShingle Rebecca T Brown
Kiya D Komaiko
Ying Shi
Kathy Z Fung
W John Boscardin
Alvin Au-Yeung
Gary Tarasovsky
Riya Jacob
Michael A Steinman
Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
PLoS ONE
author_facet Rebecca T Brown
Kiya D Komaiko
Ying Shi
Kathy Z Fung
W John Boscardin
Alvin Au-Yeung
Gary Tarasovsky
Riya Jacob
Michael A Steinman
author_sort Rebecca T Brown
title Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
title_short Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
title_full Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
title_fullStr Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
title_full_unstemmed Bringing functional status into a big data world: Validation of national Veterans Affairs functional status data.
title_sort bringing functional status into a big data world: validation of national veterans affairs functional status data.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description <h4>Background</h4>The ability to perform basic daily activities ("functional status") is key to older adults' quality of life and strongly predicts health outcomes. However, data on functional status are seldom collected during routine clinical care in a way that makes them available for clinical use and research.<h4>Objectives</h4>To validate functional status data that Veterans Affairs (VA) medical centers recently started collecting during routine clinical care, compared to the same data collected in a structured research setting.<h4>Design</h4>Prospective validation study.<h4>Setting</h4>Seven VA medical centers that collected complete data on 5 activities of daily living (ADLs) and 8 instrumental activities of daily living (IADLs) from older patients attending primary care appointments.<h4>Participants</h4>Randomly selected patients aged 75 and older who had new ADL and IADL data collected during a primary care appointment (N = 252). We oversampled patients with ADL dependence and applied these sampling weights to our analyses.<h4>Measurements</h4>Telephone-based interviews using a validated measure to assess the same 5 ADLs and 8 IADLs.<h4>Results</h4>Mean age was 83 years, 96% were male, and 75% were white. Of 85 participants whom VA data identified as dependent in 1 or more ADLs, 74 (87%) reported being dependent by interview; of 167 whom VA data identified as independent in ADLs, 149 (89%) reported being independent. The sample-weighted sensitivity of the VA data for identifying ADL dependence was 45% (95% CI, 29%, 62%) compared to the reference standard, the specificity was 99% (95% CI, 99%, >99%), and the positive predictive value was 87% (95% CI, 79%, 93%). The weighted kappa statistic was 0.55 (95% CI, 0.41, 0.68) for the agreement between VA data and research-collected data in identifying ADL dependence.<h4>Conclusion</h4>Overall agreement of VA functional status data with a reference standard was moderate, with fair sensitivity but high specificity and positive predictive value.
url https://doi.org/10.1371/journal.pone.0178726
work_keys_str_mv AT rebeccatbrown bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT kiyadkomaiko bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT yingshi bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT kathyzfung bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT wjohnboscardin bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT alvinauyeung bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT garytarasovsky bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT riyajacob bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
AT michaelasteinman bringingfunctionalstatusintoabigdataworldvalidationofnationalveteransaffairsfunctionalstatusdata
_version_ 1714808453903417344