Identifying distinct risk profiles to predict adverse events among community-dwelling older adults
Journal article
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, Bowles, Kathryn H., Keim, Susan, Greenberg, Sherry A., Sefcik, Justine S., Topaz, Maxim, Kong, Dexia and Naylor, Mary D.. (2017). Identifying distinct risk profiles to predict adverse events among community-dwelling older adults. Geriatric Nursing. 38(6), pp. 510 - 519. https://doi.org/10.1016/j.gerinurse.2017.03.013
Authors | 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, Bowles, Kathryn H., Keim, Susan, Greenberg, Sherry A., Sefcik, Justine S., Topaz, Maxim, Kong, Dexia and Naylor, Mary D. |
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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. |
Year | 2017 |
Journal | Geriatric Nursing |
Journal citation | 38 (6), pp. 510 - 519 |
Publisher | Mosby Inc. |
ISSN | 0197-4572 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.gerinurse.2017.03.013 |
Scopus EID | 2-s2.0-85018949500 |
Page range | 510 - 519 |
Research Group | Mary MacKillop Institute for Health Research |
Publisher's version | File Access Level Controlled |
Place of publication | United States |
Editors | B. Resnick |
https://acuresearchbank.acu.edu.au/item/8qy0q/identifying-distinct-risk-profiles-to-predict-adverse-events-among-community-dwelling-older-adults
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