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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Identifying distinct risk profiles to predict adverse events among community-dwelling older adults
Geriatric nursing (New York), v 38(6), pp 510-519
01 Nov 2017
PMID: 28479081
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Preventing adverse events among chronically ill older adults living in the community is a national health priority. The purpose of this study was to generate distinct risk profiles and compare these profiles in time to: hospitalization, emergency department (ED) visit or death in 371 community-dwelling older adults enrolled in a Medicare demonstration project. Guided by the Behavioral Model of Health Service Use, a secondary analysis was conducted using Latent Class Analysis to generate the risk profiles with Kaplan Meier methodology and log rank statistics to compare risk profiles. The Vuong-Lo-Mendell-Rubin Likelihood Ratio Test demonstrated optimal fit for three risk profiles (High, Medium, and Low Risk). The High Risk profile had significantly shorter time to hospitalization, ED visit, and death (p < 0.001 for each). These findings provide a road map for generating risk profiles that could enable more effective targeting of interventions and be instrumental in reducing health care costs for subgroups of chronically ill community-dwelling older adults. (C) 2017 Elsevier Inc. All rights reserved.
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Details
- Title
- Identifying distinct risk profiles to predict adverse events among community-dwelling older adults
- Creators
- Melissa O'Connor - University of PennsylvaniaAlexandra Hanlon - University of PennsylvaniaElizabeth Mauer - Weill Cornell MedicineSalimah Meghani - University of PennsylvaniaRuth Masterson-Creber - Columbia UniversitySherry Marcantonio - Product Innovation and Engineering (United States) (United States, Saint James) - LLCKen Coburn - Product Innovation and Engineering (United States) (United States, Saint James) - LLCJanet Van Cleave - University of PennsylvaniaJoan Davitt - University of PennsylvaniaBarbara Riegel - University of PennsylvaniaKathryn H. Bowles - VNS HealthSusan Keim - University of PennsylvaniaSherry A. Greenberg - University of PennsylvaniaJustine S. Sefcik - University of PennsylvaniaMaxim Topaz - Harvard UniversityDexia Kong - University of PennsylvaniaMary Naylor - University of Pennsylvania
- Publication Details
- Geriatric nursing (New York), v 38(6), pp 510-519
- Publisher
- Elsevier
- Number of pages
- 10
- Grant note
- NewCourtland Center for Transitions and Health F31NR015693 / NATIONAL INSTITUTE OF NURSING RESEARCH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Nursing Research (NINR)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Doctoral Nursing
- Web of Science ID
- WOS:000419087200006
- Scopus ID
- 2-s2.0-85018949500
- Other Identifier
- 991020099922904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Geriatrics & Gerontology
- Gerontology
- Nursing