Admission-related migration by older nursing home residents.
OBJECTIVE
To examine recent admissions of older adults to intermediate care facilities in order to identify the factors associated with whether the individual originated in another county, a non-adjacent county, and another state.


METHODS
Employing a conceptual framework based upon migration theory and the long-term care decision process and a data set derived from multiple sources, logistic regression was used to examine whether characteristics of the county of residence prior to admission, the admission facility, and the individual are significant net predictors of the three types of mobility. Separate analyses were conducted for married and unmarried individuals.


RESULTS
The analytical models tended to have relatively good fit but only moderate predictive accuracy. In general, persons on Medicaid payment status were more likely to move to another county and to a non-adjacent county, whereas Medicaid payment was associated with a lower likelihood of migrating to Virginia from another state. Individuals originating in counties with higher bed rates had lower rates of migration to another county and non-adjacent county, whereas those from counties with higher occupancy rates were more likely to leave their county of origin.


CONCLUSIONS
Examination of factors associated with the distance and patterns of nursing home mobility improves our understanding of the nursing home selection process and helps to illuminate the impact of public policy, market forces, and nursing home staff on who goes where to be admitted to a nursing home.
McAuley
W J
WJ
Oklahoma Center on Aging, University of Oklahoma Health Sciences Center, Oklahoma City, USA. jim-mcauley@ouhsc.edu
Pecchioni
L
L
Grant
J A
JA
D000368:Aged; D000369:Aged, 80 and over; D003657:Decision Making; D004641:Emigration and Immigration; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D009735:Nursing Homes / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data*; D011640:Public Policy