Modeling and detecting potentially ruinous streaks in health expenditures

Int J Health Care Finance Econ. 2007 Mar;7(1):23-42. doi: 10.1007/s10754-007-9010-2. Epub 2007 Mar 10.

Abstract

The mean of a distribution of medical expenditures in an insured population can be affected significantly by the occurrence of a few high cost cases. This fact leads some organizations that hold the primary risk for the population (e.g., health plans or self-insured employers) to seek reinsurance arrangements that spread the risk of high cost cases across a broader pool. Recently, the private reinsurance market has experienced some difficulties, attributable to information asymmetries between primary risk holders and reinsurers. The disproportionate effect of a few high cost cases also has generated interest in the development of "risk-adjustment" systems that attempt to reduce the difference in health plans' unreimbursed costs either to endogenous management decisions or random chance. We discuss these issues in light of a well-known statistical result regarding the probability of "streaks" in random data. We illustrate problems that can arise and suggest methods to distinguish random streaks from systematic trends.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Bayes Theorem
  • Health Expenditures / statistics & numerical data*
  • Humans
  • Insurance Pools / trends*
  • Insurance, Health / economics*
  • Insurance, Health / statistics & numerical data
  • Models, Econometric
  • Risk Sharing, Financial / methods*