title: Association between hospital imaging use and venous thromboembolism events rates based on clinical data.
abstract: OBJECTIVE
  The objective was to assess the presence and extent of venous thromboembolic (VTE) surveillance bias using high-quality clinical data.
  
  
  BACKGROUND
  Hospital VTE rates are publicly reported and used in pay-for-performance programs. Prior work suggested surveillance bias: hospitals that look more for VTE with imaging studies find more VTE, thereby incorrectly seem to have worse performance. However, these results have been questioned as the risk adjustment and VTE measurement relied on administrative data.
  
  
  METHODS
  Data (2009-2010) from 208 hospitals were available for analysis. Hospitals were divided into quartiles according to VTE imaging use rates (Medicare claims). Observed and risk-adjusted postoperative VTE event rates (regression models using American College of Surgeons National Surgical Quality Improvement Project data) were examined across VTE imaging use rate quartiles. Multivariable linear regression models were developed to assess the impact of hospital characteristics (American Hospital Association) and hospital imaging use rates on VTE event rates.
  
  
  RESULTS
  The mean risk-adjusted VTE event rates at 30 days after surgery increased across VTE imaging use rate quartiles: 1.13% in the lowest quartile to 1.92% in the highest quartile (P < 0.001). This statistically significant trend remained when examining only the inpatient period. Hospital VTE imaging use rate was the dominant driver of hospital VTE event rates (P < 0.001), as no other hospital characteristics had significant associations.
  
  
  CONCLUSIONS
  Even when examined with clinically ascertained outcomes and detailed risk adjustment, VTE rates reflect hospital imaging use and perhaps signify vigilant, high-quality care. The VTE outcome measure may not be an accurate quality indicator and should likely not be used in public reporting or pay-for-performance programs.
authors.affiliation: *Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL †Surgical Outcomes and Quality Improvement Center, Department of Surgery, Northwestern University, Chicago, IL ‡Department of Surgery, University of California, Los Angeles (UCLA), and VA Greater Los Angeles Healthcare System, Los Angeles, CA.
authors.forename: Mila H
authors.initials: MH
authors.lastname: Ju
authors.forename: Jeanette W
authors.initials: JW
authors.lastname: Chung
authors.forename: Christine V
authors.initials: CV
authors.lastname: Kinnier
authors.forename: David J
authors.initials: DJ
authors.lastname: Bentrem
authors.forename: David M
authors.initials: DM
authors.lastname: Mahvi
authors.forename: Clifford Y
authors.initials: CY
authors.lastname: Ko
authors.forename: Karl Y
authors.initials: KY
authors.lastname: Bilimoria
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D011183:Postoperative Complications / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control; D019984:Quality Indicators, Health Care; D018570:Risk Assessment; D054556:Venous Thromboembolism / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control