Effect of an expenditure cap on low-income seniors' drug use and spending in a state pharmacy assistance program

Health Serv Res. 2009 Jun;44(3):1010-28. doi: 10.1111/j.1475-6773.2009.00951.x. Epub 2009 Mar 2.

Abstract

Objective: To estimate the impact of a soft cap (a ceiling on utilization beyond which insured enrollees pay a higher copayment) on low-income elders' use of prescription drugs.

Data sources and setting: Claims and enrollment files for the first year ( June 2002 through May 2003) of the Illinois SeniorCare program, a state pharmacy assistance program, and Medicare claims and enrollment files, 2001 through 2003. SeniorCare enrolled non-Medicaid-eligible elders with income less than 200 percent of Federal Poverty Level. Minimal copays increased by 20 percent of prescription cost when enrollee expenditures reached $1,750.

Research design: Models were estimated for three dependent variables: enrollees' average monthly utilization (number of prescriptions), spending, and the proportion of drugs that were generic rather than brand. Observations included all program enrollees who exceeded the cap and covered two periods, before and after the cap was exceeded.

Principle findings: On average, enrollees exceeding the cap reduced the number of drugs they purchased by 14 percent, monthly expenditures decreased by 19 percent, and the proportion generic increased by 4 percent, all significant at p<.01. Impacts were greater for enrollees with greater initial spending, for enrollees without one of five chronic illness diagnoses in the previous calendar year, and for enrollees with lower income.

Conclusions: Near-poor elders enrolled in plans with caps or coverage gaps, including Part D plans, may face sharp declines in utilization when they exceed these thresholds.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cost Control
  • Cost Sharing / economics*
  • Drug Utilization / economics
  • Drugs, Generic / economics
  • Drugs, Generic / therapeutic use
  • Female
  • Health Care Surveys
  • Health Expenditures / statistics & numerical data*
  • Humans
  • Illinois
  • Insurance Claim Reporting / economics
  • Insurance Coverage / economics
  • Insurance, Pharmaceutical Services / economics*
  • Linear Models
  • Logistic Models
  • Male
  • Medical Assistance / economics*
  • Medicare Part D / economics
  • Models, Econometric
  • Poverty / economics
  • Prescription Drugs / economics*
  • Prescription Drugs / therapeutic use
  • Socioeconomic Factors
  • State Health Plans / economics*
  • United States

Substances

  • Drugs, Generic
  • Prescription Drugs