title: Predictors of nursing home residents' time to hospitalization.
abstract: OBJECTIVE
  To model the predictors of the time to first acute hospitalization for nursing home residents, and accounting for previous hospitalizations, model the predictors of time between subsequent hospitalizations.
  
  
  METHODS
  Merged file from New York State for the period 1998-2004 consisting of nursing home information from the minimum dataset and hospitalization information from the Statewide Planning and Research Cooperative System.
  
  
  METHODS
  Accelerated failure time models were used to estimate the model parameters and predict survival times. The models were fit to observations from 50 percent of the nursing homes and validated on the remaining observations.
  
  
  RESULTS
  Pressure ulcers and facility-level deficiencies were associated with a decreased time to first hospitalization, while the presence of advance directives and facility staffing was associated with an increased time. These predictors of the time to first hospitalization model had effects of similar magnitude in predicting the time between subsequent hospitalizations.
  
  
  CONCLUSIONS
  This study provides novel evidence suggesting modifiable patient and nursing home characteristics are associated with the time to first hospitalization and time to subsequent hospitalizations for nursing home residents.
authors.affiliation: Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115-5899, USA. omalley@hcp.med.harvard.edu
authors.forename: A James
authors.initials: AJ
authors.lastname: O'Malley
authors.forename: Daryl J
authors.initials: DJ
authors.lastname: Caudry
authors.forename: David C
authors.initials: DC
authors.lastname: Grabowski
mesh_terms: D016223:Advance Directives / Q000706:statistics & numerical data; D000368:Aged; D002908:Chronic Disease; D005260:Female; D006707:Homes for the Aged / Q000458:organization & administration / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D053208:Kaplan-Meier Estimate; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D006278:Medicare / Q000706:statistics & numerical data; D015233:Models, Statistical; D009518:New York; D009735:Nursing Homes / Q000458:organization & administration / Q000706:statistics & numerical data*; D010561:Personnel Staffing and Scheduling / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000706:statistics & numerical data*; D012737:Sex Factors; D012959:Socioeconomic Factors; D013997:Time Factors; D014481:United States