title: Predictive model of length of stay and discharge destination in neuroscience admissions.
abstract: BACKGROUND
  The purpose of this study was to try and determine the best predictors of hospital length of stay and discharge destination in patients admitted to a neuroscience service.
  
  
  METHODS
  Valid data was collected for 170 patients. Variables included age, gender, location prior to admission, principle diagnosis, various physiological measurements upon admission, comorbidity, independence in various activities of daily living prior to admission, length of stay, and disposition upon discharge. Study design was a correlational descriptive study performed through the analysis of data and the development and validation of statistically significant factors in determining the length of stay.
  
  
  RESULTS
  All factors with a strong (P< 0.05) relationship with the length of stay were entered into a forward stepwise linear regression with length of stay as the dependent variable. The three most significant variables in predicting length of stay in this study were admission from an outpatient setting, modified Rankin score on admission, and systolic blood pressure on admission.
  
  
  CONCLUSIONS
  Functional status at admission, specifically, a higher modified Rankin score and a lower systolic blood pressure along with the acquisition of deep vein thrombosis, catheter associated urinary tract infections, intubation, and admission to an intensive care unit all have a statistically significant effect on the hospital length of stay.
authors.affiliation: Winthrop University Hospital, Mineola, New York, USA.
authors.forename: M M
authors.initials: MM
authors.lastname: Stecker
authors.affiliation: Winthrop University Hospital, Mineola, New York, USA.
authors.forename: M
authors.initials: M
authors.lastname: Stecker
authors.affiliation: Colgate University, Hamilton, NY, USA.
authors.forename: J
authors.initials: J
authors.lastname: Falotico
keywords: Comorbidity; functional status; length of stay