Predictors of discharges to a nursing home in a hospital-based cohort.
Journal Article (Journal Article)
BACKGROUND: Nursing home (NH) placement among older adults is influenced by numerous factors and is associated with multiple problematic outcomes. Interventions to prevent or delay NH placement have mainly been researched in the community. However, prediction of these factors during hospitalization could provide an ideal opportunity to shape targeted interventions among high-risk patients. The purposes of this investigation were to compare characteristics of patients discharged to the community and those discharged to the NH, and to identify predictors of NH placement. METHODS: A retrospective hospital-based cohort design was used to identify predictors of NH placement. Information about the study population was obtained from Scott and White (S&W) Healthcare's Electronic Medical Records and billing records. Study participants included S&W persons discharged to the community (n=5025) or to a nursing home (n=981). Descriptive characteristics were compared between community discharges and NH discharges using chi(2) statistic for categorical data and t test for continuous variables. Multiple logistic regression models were performed to identify the most salient predictors of NH placement. RESULTS: Traditional risk factors, such as having less caregiving support, using more hospital services, being more severely ill, and not understanding their illness, characterized persons discharged to the NH compared with community-discharged persons. Significant predictors of being discharged to the NH included longer hospitalizations, not understanding one's illness, being female, living alone, not having a caregiver, needing assistance with dressing, and having a fall risk. CONCLUSION: In conclusion, these results could help develop hospital-based interventions to postpone or prevent NH placement among high-risk patients.
- Smith, ER; Stevens, AB
- November 2009
Volume / Issue
- 10 / 9
Start / End Page
- 623 - 629
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)
- United States