title: Using same-hospital readmission rates to estimate all-hospital readmission rates.
abstract: BACKGROUND
  Since October of 2012, Medicare's Hospital Readmissions Reduction Program has fined 2,200 hospitals a total of $500 million. Although the program penalizes readmission to any hospital, many institutions can only track readmissions to their own hospitals. We sought to determine the extent to which same-hospital readmission rates can be used to estimate all-hospital readmission rates after major surgery.
  
  
  METHODS
  We evaluated 3,940 hospitals treating 741,656 Medicare fee-for-service beneficiaries undergoing CABG, hip fracture repair, or colectomy between 2006 and 2008. We used hierarchical logistic regression to calculate risk- and reliability-adjusted rates of 30-day readmission to the same hospital and to any hospital. We next evaluated the correlation between same-hospital and all-hospital rates. To analyze the impact on hospital profiling, we compared rankings based on same-hospital rates with those based on all-hospital rates.
  
  
  RESULTS
  The mean risk- and reliability-adjusted all-hospital readmission rate was 13.2% (SD 1.5%) and mean same-hospital readmission rate was 8.4% (SD 1.1%). Depending on the operation, between 57% (colectomy) and 63% (CABG) of hospitals were reclassified when profiling was based on same-hospital readmission rates instead of on all-hospital readmission rates. This was particularly pronounced in the middle 3 quintiles, where 66% to 73% of hospitals were reclassified.
  
  
  CONCLUSIONS
  In evaluating hospital profiling under Medicare's Hospital Readmissions Reduction Program, same-hospital rates provide unstable estimates of all-hospital readmission rates. To better anticipate penalties, hospitals require novel approaches for accurately tracking the totality of their postoperative readmissions.
authors.affiliation: Center for Healthcare Outcomes and Policy (CHOP), University of Michigan, Ann Arbor, MI; Department of Surgery, University of Illinois Hospital & Health Sciences System, Chicago, IL. Electronic address: aagonzal@umich.edu.
authors.forename: Andrew A
authors.initials: AA
authors.lastname: Gonzalez
authors.affiliation: Center for Healthcare Outcomes and Policy (CHOP), University of Michigan, Ann Arbor, MI.
authors.forename: Terry
authors.initials: T
authors.lastname: Shih
authors.affiliation: Center for Healthcare Outcomes and Policy (CHOP), University of Michigan, Ann Arbor, MI.
authors.forename: Justin B
authors.initials: JB
authors.lastname: Dimick
authors.affiliation: Center for Healthcare Outcomes and Policy (CHOP), University of Michigan, Ann Arbor, MI.
authors.forename: Amir A
authors.initials: AA
authors.lastname: Ghaferi
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005500:Follow-Up Studies; D054624:Health Status Disparities; D054625:Healthcare Disparities / Q000191:economics / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data*; D015397:Program Evaluation; D012189:Retrospective Studies; D013514:Surgical Procedures, Operative / Q000191:economics / Q000706:statistics & numerical data*; D013997:Time Factors; D014481:United States