title: Statistical uncertainty in the Medicare shared savings program.
abstract: OBJECTIVE
  Analyze statistical risks facing CMS and Accountable Care Organizations (ACOs) under the Medicare Shared Savings Program (MSSP).
  
  
  METHODS
  We calculate the probability that shared savings formulas lead to inappropriate payment, payment denial, and/or financial penalties, assuming that ACOs generate real savings in Medicare spending ranging from 0-10%. We also calculate expected payments from CMS to ACOs under these scenarios.
  
  
  RESULTS
  The probability of an incorrect outcome is heavily dependent on ACO enrollment size. For example, in the MSSP two-sided model, an ACO with 5,000 enrollees that keeps spending constant faces a 0.24 probability of being inappropriately rewarded for savings and a 0.26 probability of paying an undeserved penalty for increased spending. For an ACO with 50,000 enrollees, both of these probabilities of incorrect outcomes are equal to 0.02. The probability of inappropriate payment denial declines as real ACO savings increase. Still, for ACOs with 5,000 patients, the probability of denial is at least 0.15 even when true savings are 5-7%. Depending on ACO size and the real ACO savings rate, expected ACO payments vary from $115,000 to $35.3 million.
  
  
  CONCLUSIONS
  Our analysis indicates there may be greater statistical uncertainty in the MSSP than previously recognized. CMS and ACOs will have to consider this uncertainty in their financial, administrative, and care management planning. We also suggest analytic strategies that can be used to refine ACO payment formulas in the longer term to ensure that the MSSP (and other ACO initiatives that will be influenced by it) work as efficiently as possible.
authors.affiliation: Rutgers University-Center for State Health Policy.
authors.forename: Derek
authors.initials: D
authors.lastname: DeLia
authors.affiliation: Rutgers University-Statistics/Institute for Health.
authors.forename: Donald
authors.initials: D
authors.lastname: Hoover
authors.affiliation: Rutgers University-Center for State Health Policy.
authors.forename: Joel C
authors.initials: JC
authors.lastname: Cantor
mesh_terms: D060866:Accountable Care Organizations / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D017046:Cost Savings / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D006278:Medicare / Q000191:economics / Q000458:organization & administration* / Q000706:statistics & numerical data; D018803:Models, Economic; D015233:Models, Statistical; D012051:Reimbursement Mechanisms / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D035501:Uncertainty; D014481:United States
keywords: Capitation; DRGs; Health Care Costs; Health Care Financing; Health Care Organizations and Systems; Health Economics; Health Policy; Incentives in Health Care; Insurance; Law; Medicare, Econometrics; Payment Systems: FFS; Politics; Premiums; RBRVS; Regulation; Risk Adjusted Payments etc.