title: Controlling costs without compromising quality: paying hospitals for total knee replacement.
abstract: BACKGROUND
  Unit costs of health services are substantially higher in the United States than in any other developed country in the world, without a correspondingly healthier population. An alternative payment structure, especially for high volume, high cost episodes of care (eg, total knee replacement), is needed to reward high quality care and reduce costs.
  
  
  METHODS
  The National Inpatient Sample of administrative claims data was used to measure risk-adjusted mortality, postoperative length-of-stay, costs of routine care, adverse outcome rates, and excess costs of adverse outcomes for total knee replacements performed between 2002 and 2005. Empirically identified inefficient and ineffective hospitals were then removed to create a reference group of high-performance hospitals. Predictive models for outcomes and costs were recalibrated to the reference hospitals and used to compute risk-adjusted outcomes and costs for all hospitals. Per case predicted costs were computed and compared with observed costs.
  
  
  RESULTS
  Of the 688 hospitals with acceptable data, 62 failed to meet effectiveness criteria and 210 were identified as inefficient. The remaining 416 high-performance hospitals had 13.4% fewer risk-adjusted adverse outcomes (4.56%-3.95%; P < 0.001; χ) and 9.9% lower risk-adjusted total costs ($12,773-$11,512; P < 0.001; t test) than all study hospitals. Inefficiency accounted for 96% of excess costs.
  
  
  CONCLUSIONS
  A payment system based on the demonstrated performance of effective, efficient hospitals can produce sizable cost savings without jeopardizing quality. In this study, 96% of total excess hospital costs resulted from higher routine costs at inefficient hospitals, whereas only 4% was associated with ineffective care.
authors.affiliation: Michael Pine and Associates, Chicago, IL 60615, USA. michaelorjoan@yahoo.com
authors.forename: Michael
authors.initials: M
authors.lastname: Pine
authors.forename: Donald E
authors.initials: DE
authors.lastname: Fry
authors.forename: Barbara L
authors.initials: BL
authors.lastname: Jones
authors.forename: Roger J
authors.initials: RJ
authors.lastname: Meimban
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Pine
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019645:Arthroplasty, Replacement, Knee / Q000191:economics* / Q000706:statistics & numerical data; D003363:Cost Control / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis; D017598:Efficiency, Organizational; D018588:Fee-for-Service Plans / Q000191:economics; D005260:Female; D017722:Hospital Charges / Q000706:statistics & numerical data*; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000191:economics; D012051:Reimbursement Mechanisms / Q000191:economics*; D014481:United States; D055815:Young Adult