title: Sources of hospital variation in short-term readmission rates after percutaneous coronary intervention.
abstract: BACKGROUND
  Risk-standardized all-cause 30-day readmission rates (RSRRs) after percutaneous coronary intervention (PCI) have been endorsed as a national measure of hospital quality. Little is known about variation in the performance of hospitals on this measure, and whether high hospital rates of readmission after PCI are due to modifiable deficiencies in quality of care has not been assessed.
  
  
  RESULTS
  We estimated 30-day, all-cause RSRRs for all nonfederal PCI-performing hospitals in Massachusetts, adjusted for clinical and angiographic variables, between 2005 and 2008. We assessed if differences in race, insurance type, and PCI and post-PCI characteristics, including procedural complications and discharge characteristics, could explain variation between hospitals using nested hierarchical logistic regression models. Of 36 060 patients undergoing PCI at 24 hospitals and surviving to discharge, 4469 (12.4%) were readmitted within 30 days of discharge. Hospital RSRRs ranged from 9.5% to 17.9%, with 8 of 24 hospitals being identified as outliers (4 lower than expected and 4 higher than expected). Differences in race, insurance, PCI, and post-PCI factors accounted for 10.4% of the between-hospital variance in RSRRs.
  
  
  CONCLUSIONS
  We observed wide variation in hospital 30-day all-cause RSRRs after PCI, most of which could not be explained by identifiable differences in procedural and postprocedural factors. A better understanding of etiologies of hospital variation is necessary to determine whether this measure is an actionable assessment of hospital quality, and, if so, how hospitals might improve their performance.
authors.affiliation: Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. ryeh@partners.org
authors.forename: Robert W
authors.initials: RW
authors.lastname: Yeh
authors.forename: Kenneth
authors.initials: K
authors.lastname: Rosenfield
authors.forename: Katya
authors.initials: K
authors.lastname: Zelevinsky
authors.forename: Laura
authors.initials: L
authors.lastname: Mauri
authors.forename: Rahul
authors.initials: R
authors.lastname: Sakhuja
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Shivapour
authors.forename: Ann
authors.initials: A
authors.lastname: Lovett
authors.forename: Bonnie H
authors.initials: BH
authors.lastname: Weiner
authors.forename: Alice K
authors.initials: AK
authors.lastname: Jacobs
authors.forename: Sharon-Lise T
authors.initials: SL
authors.lastname: Normand
mesh_terms: D000368:Aged; D017130:Angioplasty; D003324:Coronary Artery Disease / Q000453:epidemiology* / Q000601:surgery; D003331:Coronary Vessels / Q000473:pathology / Q000601:surgery*; D005260:Female; D006801:Humans; D007348:Insurance, Health; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011183:Postoperative Complications / Q000453:epidemiology* / Q000601:surgery; D010818:Practice Patterns, Physicians'; D011787:Quality of Health Care; D044469:Racial Groups; D012306:Risk; D013997:Time Factors; D014481:United States