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Conference Paper: Predicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0

TitlePredicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0
Authors
Issue Date2017
PublisherOxford University Press. The Journal's web site is located at https://academic.oup.com/innovateage/
Citation
The 21st International Association of Gerontology and Geriatrics (IAGG) World Congress, San Francisco, USA, 23-27 July 2017. In Innovation in Aging, 2017, v. 1 n. S1, p. 673-674 How to Cite?
AbstractThis study was to create a simple frailty measure for nursing home residents using the Minimum Data Set (MDS). Method: MDS items comparable with the FRAIL-NH scale were extracted. Frailty status was calculated based on the following eight components: fatigue, resistance, ambulation, incontinence, polypharmacy, loss of weight, nutritional approach, and help with dressing. We included 2,380 elders residing in six nursing homes in Hong Kong between 2005 and 2013 to test the predictive validity of the resulted scale against major adverse health outcomes. Results: The proposed frailty scale was independently predictive of incident falls, worsening function, incident hospitalization, and mortality, with hazard ratios ranging from 2.00 to 3.73, adjusting for gender, age, education, cognitive performance, and the presence of prevalent diseases. Implications: We provided a simple and reliable scale to identify frail persons in nursing homes and for developing effective intervention schemes.
DescriptionSession 3140 (Symposium): Physical Frailty, A Target for the Promotion of Health and Social Outcomes
Persistent Identifierhttp://hdl.handle.net/10722/261642
ISSN
2023 Impact Factor: 4.9
2023 SCImago Journal Rankings: 1.052

 

DC FieldValueLanguage
dc.contributor.authorLuo, H-
dc.contributor.authorLum, TYS-
dc.contributor.authorWong, GHY-
dc.contributor.authorKwan, JSK-
dc.contributor.authorTang, YMJ-
dc.date.accessioned2018-09-28T04:45:10Z-
dc.date.available2018-09-28T04:45:10Z-
dc.date.issued2017-
dc.identifier.citationThe 21st International Association of Gerontology and Geriatrics (IAGG) World Congress, San Francisco, USA, 23-27 July 2017. In Innovation in Aging, 2017, v. 1 n. S1, p. 673-674-
dc.identifier.issn2399-5300-
dc.identifier.urihttp://hdl.handle.net/10722/261642-
dc.descriptionSession 3140 (Symposium): Physical Frailty, A Target for the Promotion of Health and Social Outcomes-
dc.description.abstractThis study was to create a simple frailty measure for nursing home residents using the Minimum Data Set (MDS). Method: MDS items comparable with the FRAIL-NH scale were extracted. Frailty status was calculated based on the following eight components: fatigue, resistance, ambulation, incontinence, polypharmacy, loss of weight, nutritional approach, and help with dressing. We included 2,380 elders residing in six nursing homes in Hong Kong between 2005 and 2013 to test the predictive validity of the resulted scale against major adverse health outcomes. Results: The proposed frailty scale was independently predictive of incident falls, worsening function, incident hospitalization, and mortality, with hazard ratios ranging from 2.00 to 3.73, adjusting for gender, age, education, cognitive performance, and the presence of prevalent diseases. Implications: We provided a simple and reliable scale to identify frail persons in nursing homes and for developing effective intervention schemes.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at https://academic.oup.com/innovateage/-
dc.relation.ispartofInnovation in Aging-
dc.relation.ispartofThe 21st International Association of Gerontology and Geriatrics World Congress, IAGG 2017-
dc.titlePredicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0-
dc.typeConference_Paper-
dc.identifier.emailLuo, H: haoluo@hku.hk-
dc.identifier.emailLum, TYS: tlum@hku.hk-
dc.identifier.emailWong, GHY: ghywong@hku.hk-
dc.identifier.emailKwan, JSK: jskkwan@hku.hk-
dc.identifier.emailTang, YMJ: jennitym@hku.hk-
dc.identifier.authorityLuo, H=rp02317-
dc.identifier.authorityLum, TYS=rp01513-
dc.identifier.authorityWong, GHY=rp01850-
dc.identifier.authorityKwan, JSK=rp01868-
dc.identifier.authorityTang, YMJ=rp01997-
dc.identifier.hkuros293064-
dc.identifier.volume1-
dc.identifier.issueS1-
dc.identifier.spage673-
dc.identifier.epage674-
dc.publisher.placeUnited States-
dc.identifier.issnl2399-5300-

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