title: Total and out-of-pocket expenditures for prescription drugs among older persons.
abstract: OBJECTIVE
  The burden of prescription drug costs on Medicare beneficiaries has become a critical policy issue in improving the Medicare program, yet few studies have provided detailed and current information on that burden. The present study estimates total and out-of-pocket expenditures for prescription drugs and the burden of these costs in relation to income among the elderly population. We also compare spending and burden across major subgroups of the elderly population, as defined by socioeconomic and health characteristics, and we distinguish the impact of these factors by using multivariate models.
  
  
  METHODS
  The study uses nationally representative data on Medicare beneficiaries from the 1997 Medicare Current Beneficiary Survey Cost and Use files. The study estimates out-of-pocket prescription drug spending and burden through ordinary least square, median, and logistic regression models with corrections for the complex survey design.
  
  
  RESULTS
  Our results show that in 1997, nearly 8% of the older population, more than 2.3 million people, spent greater than 10% of their income on prescription drugs. Despite pharmacy coverage, out-of-pocket cost burden fell most heavily on women and those with chronic health conditions. Burden was also higher among those with self-purchased supplemental coverage.
  
  
  CONCLUSIONS
  The impact of Medicare reform proposals on these subgroups has to be carefully evaluated.
authors.affiliation: Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, NJ 08901, USA. sambamoo@rci.rutgers.edu
authors.forename: Usha
authors.initials: U
authors.lastname: Sambamoorthi
authors.forename: Dennis
authors.initials: D
authors.lastname: Shea
authors.forename: Stephen
authors.initials: S
authors.lastname: Crystal
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D017281:Cost of Illness; D005260:Female; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D011306:Prescription Fees / Q000706:statistics & numerical data*; D017678:Sex Distribution; D012959:Socioeconomic Factors; D014481:United States