title: Interpreting risk-adjusted length of stay patterns for VA hospitals.
abstract: OBJECTIVE
  The Veterans Health System must become more competitive with the private sector in terms of efficiency of care. Studies have shown significantly longer lengths-of-stay (LOS) in facilities operated by the Department of Veterans Affairs (VA) compared with private sector facilities. Most comparisons, however, have not controlled well for casemix differences or have involved small numbers of patients. The aims of this study were: (1) controlling for casemix, to accurately measure the degree by which average length of stay in Veterans Affairs facilities exceeds that of private sector hospitals and (2) to demonstrate a methodology with which individual VA facilities can identify clinical and demographic subgroups of patients associated with the higher length-of-stay averages.
  
  
  METHODS
  Subjects of the study were Veterans Health System patients hospitalized during 1991-1993 and veteran respondents to the 1991 National Hospital Discharge Survey. Hospitals' mean length of stay adjusted for patients' diagnosis related groups, severity, demographics, and travel distances were measured.
  
  
  RESULTS
  Veterans Affairs medical centers' average risk-adjusted length of stay was 36% higher (8.9 days compared with 6.5 days) than that of the private sector. For individual hospitals, relative length-of-stay efficiency typically varied by condition. Among 14 hospitals in the VA's midwest region, none were high risk-adjusted length-of-stay outliers in all conditions studied, and four were high outliers for some conditions and low outliers for others.
  
  
  CONCLUSIONS
  Controlling for differences in patient demographic and clinical factors, Veterans Affairs medical centers consumed significantly more days of care than private sector hospitals. Veterans Affairs medical centers will be able to improve efficiency by identifying specific subgroups of patients whose clinical treatment should be examined.
authors.affiliation: Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor 48109, USA.
authors.forename: J W
authors.initials: JW
authors.lastname: Thomas
authors.forename: E W
authors.initials: EW
authors.lastname: Bates
authors.forename: T
authors.initials: T
authors.lastname: Hofer
authors.forename: A
authors.initials: A
authors.lastname: Perkins
authors.forename: N
authors.initials: N
authors.lastname: Foltz-Murphy
authors.forename: C
authors.initials: C
authors.lastname: Webb
mesh_terms: D015897:Comorbidity; D003953:Diagnosis-Related Groups; D005260:Female; D016304:Hospitals, Private / Q000706:statistics & numerical data; D006787:Hospitals, Veterans / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D020379:Risk Adjustment; D014481:United States