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. 2017 Nov-Dec;38(6):510-519.
doi: 10.1016/j.gerinurse.2017.03.013. Epub 2017 May 4.

Identifying distinct risk profiles to predict adverse events among community-dwelling older adults

Melissa O'Connor  1 , Alexandra Hanlon  2 , Elizabeth Mauer  3 , Salimah Meghani  2 , Ruth Masterson-Creber  4 , Sherry Marcantonio  5 , Ken Coburn  5 , Janet Van Cleave  6 , Joan Davitt  7 , Barbara Riegel  2 , Kathryn H Bowles  8 , Susan Keim  2 , Sherry A Greenberg  6 , Justine S Sefcik  2 , Maxim Topaz  9 , Dexia Kong  2 , Mary Naylor  2
Affiliations

Identifying distinct risk profiles to predict adverse events among community-dwelling older adults

Melissa O'Connor et al. Geriatr Nurs. 2017 Nov-Dec.

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: Chronic illness; Community-dwelling older adults; Latent class analysis; Nurse care management model; Risk profiles.

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Figures

Fig. 1
Fig. 1
Behavioral model of health service use.
Fig. 2
Fig. 2
Risk endorsing probabilities of indicator variables.
Fig. 3
Fig. 3
Time to first hospitalization Kaplan Meier curve by class with survival probabilities, log-rank (p < 0.001).
Fig. 4
Fig. 4
Time to first emergency department visit Kaplan Meier curve by class with survival probabilities, log-rank (p < 0.001).
Fig. 5
Fig. 5
Overall survival Kaplan Meier curve by class with survival probabilities, log-rank (p < 0.001).
See this image and copyright information in PMC

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