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Identifying distinct risk profiles to predict adverse events among community-dwelling older adults
O'Connor, Melissa Hanlon, Alexandra L. Mauer, Elizabeth Meghani, Salimah H. Creber, Ruth M. Marcantonio, Sherry Coburn, Ken Van Cleave, Janet Davitt, Joan Riegel, Barbara
O'Connor, Melissa
Hanlon, Alexandra L.
Mauer, Elizabeth
Meghani, Salimah H.
Creber, Ruth M.
Marcantonio, Sherry
Coburn, Ken
Van Cleave, Janet
Davitt, Joan
Riegel, Barbara
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.
Keywords
Date
2017
Type
Journal article
Journal
Geriatric Nursing
Book
Volume
38
Issue
6
Page Range
510-519
Article Number
ACU Department
Mary MacKillop Institute for Health Research
Faculty of Health Sciences
Faculty of Health Sciences
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Event URL
Open Access Status
License
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Controlled