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Conference Paper: Predicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0
Title | Predicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0 |
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Authors | |
Issue Date | 2017 |
Publisher | Oxford 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? |
Abstract | This 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. |
Description | Session 3140 (Symposium): Physical Frailty, A Target for the Promotion of Health and Social Outcomes |
Persistent Identifier | http://hdl.handle.net/10722/261642 |
ISSN | 2023 Impact Factor: 4.9 2023 SCImago Journal Rankings: 1.052 |
DC Field | Value | Language |
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dc.contributor.author | Luo, H | - |
dc.contributor.author | Lum, TYS | - |
dc.contributor.author | Wong, GHY | - |
dc.contributor.author | Kwan, JSK | - |
dc.contributor.author | Tang, YMJ | - |
dc.date.accessioned | 2018-09-28T04:45:10Z | - |
dc.date.available | 2018-09-28T04:45:10Z | - |
dc.date.issued | 2017 | - |
dc.identifier.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 | - |
dc.identifier.issn | 2399-5300 | - |
dc.identifier.uri | http://hdl.handle.net/10722/261642 | - |
dc.description | Session 3140 (Symposium): Physical Frailty, A Target for the Promotion of Health and Social Outcomes | - |
dc.description.abstract | This 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.language | eng | - |
dc.publisher | Oxford University Press. The Journal's web site is located at https://academic.oup.com/innovateage/ | - |
dc.relation.ispartof | Innovation in Aging | - |
dc.relation.ispartof | The 21st International Association of Gerontology and Geriatrics World Congress, IAGG 2017 | - |
dc.title | Predicting Adverse Health Outcomes in Nursing Home: A Frailty Measure Using Minimum Data Set 2.0 | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Luo, H: haoluo@hku.hk | - |
dc.identifier.email | Lum, TYS: tlum@hku.hk | - |
dc.identifier.email | Wong, GHY: ghywong@hku.hk | - |
dc.identifier.email | Kwan, JSK: jskkwan@hku.hk | - |
dc.identifier.email | Tang, YMJ: jennitym@hku.hk | - |
dc.identifier.authority | Luo, H=rp02317 | - |
dc.identifier.authority | Lum, TYS=rp01513 | - |
dc.identifier.authority | Wong, GHY=rp01850 | - |
dc.identifier.authority | Kwan, JSK=rp01868 | - |
dc.identifier.authority | Tang, YMJ=rp01997 | - |
dc.identifier.hkuros | 293064 | - |
dc.identifier.volume | 1 | - |
dc.identifier.issue | S1 | - |
dc.identifier.spage | 673 | - |
dc.identifier.epage | 674 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 2399-5300 | - |