title: How you look determines what you find: severity of illness and variation in blood transfusion for hip fracture.
abstract: OBJECTIVE
  Utilization report cards are commonly used to assess hospitals. However, in practice, they rarely account for differences in patient populations among hospitals. Our study questions were: (1) How does transfusion utilization for hip fracture patients vary among hospitals? (2) What patient characteristics are associated with transfusion and how do those characteristics vary among hospitals? (3) Is the apparent pattern of variation of utilization among hospitals altered by controlling for these patient characteristics?
  
  
  METHODS
  We included consecutive hip fracture patients aged 60 years or older who underwent surgical repair between 1982 and 1993 in 19 hospitals from four states, excluding those who refused blood transfusion, had multiple trauma, metastatic cancer, multiple myeloma, an above the knee amputation, or were paraplegic or quadriplegic. The outcome of interest was postoperative blood transfusion. "Trigger hemoglobin" was the lowest hemoglobin recorded before transfusion or recorded at any time during the week before or after surgery for patients who were not transfused.
  
  
  RESULTS
  There was considerable variation in transfusion among hospitals postoperatively (range 31.2% to 54.0%, P = 0.001). Trigger hemoglobin also varied considerably among hospitals. In unadjusted analyses, four of nine teaching and two of nine nonteaching hospitals had postoperative transfusion rates significantly higher than the reference (teaching) hospital, while one nonteaching hospital had a lower rate. In an analysis controlling for trigger hemoglobin and multiple clinical variables, one of nine teaching and four of nine nonteaching hospitals had rates higher than the reference hospital, while four teaching hospitals and one nonteaching hospital had lower rates.
  
  
  CONCLUSIONS
  The apparent pattern of variation of transfusion among hospitals varies according to how one adjusts for relevant patient characteristics. Utilization report cards that fail to adjust for these characteristics may be misleading.
authors.affiliation: Department of Medicine, Brown University School of Medicine, Providence, Rhode Island, USA.
authors.forename: R M
authors.initials: RM
authors.lastname: Poses
authors.forename: J A
authors.initials: JA
authors.lastname: Berlin
authors.forename: H
authors.initials: H
authors.lastname: Noveck
authors.forename: V A
authors.initials: VA
authors.lastname: Lawrence
authors.forename: E C
authors.initials: EC
authors.lastname: Huber
authors.forename: D A
authors.initials: DA
authors.lastname: O'Hara
authors.forename: R K
authors.initials: RK
authors.lastname: Spence
authors.forename: A
authors.initials: A
authors.lastname: Duff
authors.forename: B L
authors.initials: BL
authors.lastname: Strom
authors.forename: J L
authors.initials: JL
authors.lastname: Carson
mesh_terms: D001803:Blood Transfusion / Q000706:statistics & numerical data*; D015331:Cohort Studies; D006620:Hip Fractures / Q000150:complications / Q000601:surgery / Q000628:therapy*; D006801:Humans; D016015:Logistic Models; D015999:Multivariate Analysis; D016017:Odds Ratio; D011184:Postoperative Period; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012720:Severity of Illness Index