title: Revisiting hospital length of stay: what matters?
abstract: OBJECTIVE
  To explore actionable information that can be used to reduce hospital acute care length of stay (LOS) and to assess racial and income disparities in LOS in an integrated healthcare network.
  
  
  METHODS
  Retrospective analysis of 8718 inpatients in an integrated healthcare network. The LOS was examined by using linear, log-linear, Poisson, generalized Poisson, and negative binomial (NB) models to control for confounding factors. The performances of the 5 models were compared, and the NB model was selected for the final analysis and report.
  
  
  RESULTS
  Over 50% of the inpatients were not married. The LOS was 22% longer for the unmarried patients compared with their married counterparts after controlling for confounding factors. No income or racial disparities were found.
  
  
  CONCLUSIONS
  The prolonged LOS of the unmarried patients and the potential lack of post discharge care support warrant greater attention from discharge planners at hospital level and from policy makers at both the national and local levels. Racial and income disparities are not unavoidable; the way in which care is paid for and delivered may play a role.
authors.affiliation: Department of Veterans Affairs, Stratton VA Medical Center, 113 Holland Ave, Albany, NY 12208. E-mail: mshulan@msn.com.
authors.forename: Mollie
authors.initials: M
authors.lastname: Shulan
authors.forename: Kelly
authors.initials: K
authors.lastname: Gao
mesh_terms: D000208:Acute Disease / Q000191:economics* / Q000523:psychology / Q000628:therapy; D000328:Adult; D000704:Analysis of Variance; D015331:Cohort Studies; D017046:Cost Savings; D005260:Female; D006291:Health Policy; D017721:Hospital Costs; D006760:Hospitalization / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000331:legislation & jurisprudence*; D016014:Linear Models; D008297:Male; D017533:Marital Status / Q000706:statistics & numerical data; D008875:Middle Aged; D015999:Multivariate Analysis; D016012:Poisson Distribution; D011050:Policy Making; D012189:Retrospective Studies; D018570:Risk Assessment; D012959:Socioeconomic Factors; D014481:United States