title: What is the value of adding Medicare data in estimating VA hospital readmission rates?
abstract: OBJECTIVE
  To determine the effects of including diagnostic and utilization data from a secondary payer on readmission rates and hospital profiles.
  
  
  METHODS
  Veterans Health Administration (VA) and Medicare inpatient and outpatient administrative data for veterans discharged from 153 VA hospitals during FY 2008-2010 with a principal diagnosis of acute myocardial infarction, heart failure, or pneumonia.
  
  
  METHODS
  We estimated hospital-level risk-standardized readmission rates derived using VA data only. We then used data from both VA and Medicare to reestimate readmission rates and compared hospital profiles using two methods: Hospital Compare and the CMS implementation of the Hospital Readmissions Reduction Program (HRRP).
  
  
  METHODS
  Retrospective data analysis using VA hospital discharge and outpatient data matched with Medicare fee-for-service claims by scrambled Social Security numbers.
  
  
  RESULTS
  Less than 2 percent of hospitals in any cohort were classified discordantly by the Hospital Compare method when using VA-only compared with VA/Medicare data. In contrast, using the HRRP method, 13 percent of hospitals had differences in whether they were flagged as having excessive readmission rates in at least one cohort.
  
  
  CONCLUSIONS
  Inclusion of secondary payer data may cause changes in hospital profiles, depending on the methodology used. An assessment of readmission rates should include, to the extent possible, all available information about patients' utilization of care.
authors.affiliation: VA Boston Healthcare System - Center for Healthcare Organization and Implementation Research, Boston, MA.
authors.forename: William J
authors.initials: WJ
authors.lastname: O'Brien
authors.forename: Qi
authors.initials: Q
authors.lastname: Chen
authors.forename: Hillary J
authors.initials: HJ
authors.lastname: Mull
authors.forename: Michael
authors.initials: M
authors.lastname: Shwartz
authors.forename: Ann M
authors.initials: AM
authors.lastname: Borzecki
authors.forename: Amresh
authors.initials: A
authors.lastname: Hanchate
authors.forename: Amy K
authors.initials: AK
authors.lastname: Rosen
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D014487:Centers for Medicare and Medicaid Services, U.S.; D015331:Cohort Studies; D005260:Female; D006302:Health Services Research / Q000379:methods*; D006333:Heart Failure / Q000175:diagnosis / Q000628:therapy; D006787:Hospitals, Veterans / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data*; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000175:diagnosis / Q000628:therapy; D016017:Odds Ratio; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011014:Pneumonia / Q000175:diagnosis / Q000628:therapy; D012189:Retrospective Studies; D012307:Risk Factors; D014481:United States
keywords: Medicare; Readmissions; Veterans Affairs (U.S.); public reporting; quality assessment