title: Cost Implications of New National Allocation Policy for Deceased Donor Kidneys in the United States.
abstract: BACKGROUND
  In December 2014, a new national deceased donor kidney allocation policy was implemented, which allocates kidneys in the top 20% of the kidney donor profile index to candidates in the top 20% of expected survival. We examined the cost implications of this policy change.
  
  
  METHODS
  A Markov model was applied to estimate differences in total lifetime cost of care and quality-adjusted life years (QALY).
  
  
  RESULTS
  Under the old allocation policy, average lifetime outcomes per listed patient discounted to 2012 US dollars were US $342,799 and 5.42 QALY, yielding US $63,775 per QALY gained. Under the new policy, average lifetime cost was reduced by US $2090 and lifetime QALYs increased by 0.03. Thus, the new policy improved on the old policy by producing more QALYs at lower cost. The present value of total lifetime cost savings from the policy change is estimated to be US $271 million in the first year and US $55 million in subsequent years. The higher transplant rates and allograft survival expected for candidates in the top 20% of expected survival would decrease costs by reducing time on dialysis. Most cost savings are expected to accrue to Medicare, and most increased access to transplant is expected in private payer populations.
  
  
  CONCLUSIONS
  The new allocation policy was found to be dominant over the old policy because it increases QALYs at lower cost.
authors.affiliation: 1 Department of Pediatrics, University of Washington, Seattle, WA. 2 Scientific Registry of Transplant Recipients, Minneapolis Medical Research Foundation, Minneapolis, MN. 3 Department of Surgery, Saint Louis University School of Medicine, St. Louis, MO. 4 Department of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN. 5 Department of Medicine, Hennepin County Medical Center, University of Minnesota, Minneapolis, MN.
authors.forename: Jodi M
authors.initials: JM
authors.lastname: Smith
authors.forename: Mark A
authors.initials: MA
authors.lastname: Schnitzler
authors.forename: Sally K
authors.initials: SK
authors.lastname: Gustafson
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Salkowski
authors.forename: Jon J
authors.initials: JJ
authors.lastname: Snyder
authors.forename: Bertram L
authors.initials: BL
authors.lastname: Kasiske
authors.forename: Ajay K
authors.initials: AK
authors.lastname: Israni
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D064591:Allografts; D003198:Computer Simulation; D017046:Cost Savings; D003362:Cost-Benefit Analysis; D005260:Female; D006084:Graft Rejection / Q000191:economics / Q000276:immunology / Q000628:therapy; D006085:Graft Survival; D017048:Health Care Costs; D006801:Humans; D016030:Kidney Transplantation / Q000191:economics* / Q000379:methods; D008297:Male; D008390:Markov Chains; D006278:Medicare / Q000191:economics; D008875:Middle Aged; D018803:Models, Economic; D009313:National Health Programs / Q000191:economics*; D011050:Policy Making; D015397:Program Evaluation; D019057:Quality-Adjusted Life Years; D012042:Registries; D006435:Renal Dialysis / Q000191:economics; D013997:Time Factors; D009927:Tissue and Organ Procurement / Q000191:economics*; D016896:Treatment Outcome; D014481:United States; D055815:Young Adult