title: Regional differences in outcomes for hospitalized injured patients.
abstract: BACKGROUND
  Our goal was to use a hospital population-based data set that was a sample of all injured patients admitted to a hospital in the United States to develop universal measures of outcome and processes of care.
  
  
  METHODS
  Patients with a primary discharge diagnosis of injury (ICD-9 800 to 959) in the HCUP/Nationwide Inpatient Sample for the years 1995 to 2000 were used to estimate the annual number of hospitalized injured patients. Using census data, we calculated age- and sex- adjusted average annual incidence rates for four census regions in the United States: Northeast, Midwest, South and West. Outcomes measured were annual rates per million populations of hospitalization rate, death rate, and potentially ineffective care (PIC) rate defined as >28 days of hospitalization ending in death. Length of stay (LOS) was calculated as total number of days annually hospitalized for injury for census regions per million populations.
  
  
  RESULTS
  Incidence rates per million populations and 95% confidence intervals for rate of hospitalizations for injury were: Northeast, 5596 (5338-5853); Midwest, 5516 (5316-5716); South, 5639 (5410-5869); West, 5307 (5071-5543). Incidence rates per million populations and 95% confidence intervals for rate of in-hospital deaths were: Northeast, 129 (119-139); Midwest, 131 (122-139); South, 141 (129-152); West, 114 (106-123). Incidence rates per million populations and 95% confidence intervals for rate of PIC were: Northeast, 11 (10-13); Midwest, 5 (4-5); South, 6 (5-7); West, 4 (3-4). Incidence rates per million populations and 95% confidence intervals for hospital days were: Northeast, 34 (32-36); Midwest, 30 (28-31); South, 30 (29-32); West, 26 (24-27).
  
  
  CONCLUSIONS
  Regional differences in outcomes and processes of care for hospitalized injured patients exist and may be influenced by hospital characteristics and region of the country. Research to identify the factors that cause these hospital and regional variations is needed. These observations suggest that to develop a uniform standard for quality of care, it will be essential to have valid and robust hospital population-based measures.
authors.affiliation: Department of Surgery, Oregon Health and Science University, Portland, 97239, USA. mullinsr@ohsu.edu
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Mullins
authors.forename: Brian S
authors.initials: BS
authors.lastname: Diggs
authors.forename: Jerris R
authors.initials: JR
authors.lastname: Hedges
authors.forename: Craig D
authors.initials: CD
authors.lastname: Newgard
authors.forename: Melanie
authors.initials: M
authors.lastname: Arthur
authors.forename: Annette L
authors.initials: AL
authors.lastname: Adams
authors.forename: Judith
authors.initials: J
authors.lastname: Veum-Stone
authors.forename: Barbara
authors.initials: B
authors.lastname: Lenfesty
authors.forename: Donald D
authors.initials: DD
authors.lastname: Trunkey
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D002648:Child; D002675:Child, Preschool; D016001:Confidence Intervals; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D007223:Infant; D015601:Injury Severity Score; D007902:Length of Stay; D008297:Male; D008875:Middle Aged; D011787:Quality of Health Care; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000145:classification / Q000453:epidemiology* / Q000401:mortality