Predictors of discharges to a nursing home in a hospital-based cohort.
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.


CONCLUSIONS
In conclusion, these results could help develop hospital-based interventions to postpone or prevent NH placement among high-risk patients.
Smith
Emily R
ER
Scott and White Healthcare, Program on Aging and Care, Temple, TX, USA. esmith@swmail.sw.org
Stevens
Alan B
AB
D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D016001:Confidence Intervals; D003266:Continuity of Patient Care / Q000706:statistics & numerical data* / Q000639:trends; D005260:Female; D006707:Homes for the Aged / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D057187:Independent Living / Q000706:statistics & numerical data / Q000639:trends; D016015:Logistic Models; D008134:Long-Term Care / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009735:Nursing Homes / Q000706:statistics & numerical data*; D016017:Odds Ratio; D010343:Patient Admission / Q000706:statistics & numerical data / Q000639:trends; D010351:Patient Discharge / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D011336:Probability; D012189:Retrospective Studies; D012307:Risk Factors; D012959:Socioeconomic Factors; D013997:Time Factors; D014481:United States