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


METHODS
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.


METHODS
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.


RESULTS
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.
Bishop
Christine E
CE
Schneider Institutes for Health Policy, The Heller School for Social Policy and Management, Brandeis University, Waltham, MA 02454-9110, USA. : bishop@brandeis.edu
Ryan
Andrew M
AM
Gilden
Daniel M
DM
Kubisiak
Joanna
J
Thomas
Cindy Parks
CP
D000368:Aged; D000369:Aged, 80 and over; D003363:Cost Control; D017047:Cost Sharing / Q000191:economics*; D004363:Drug Utilization / Q000191:economics; D016568:Drugs, Generic / Q000191:economics / Q000627:therapeutic use; D005260:Female; D019538:Health Care Surveys; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D007087:Illinois; D007344:Insurance Claim Reporting / Q000191:economics; D019458:Insurance Coverage / Q000191:economics; D007356:Insurance, Pharmaceutical Services / Q000191:economics*; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D008483:Medical Assistance / Q000191:economics*; D054524:Medicare Part D / Q000191:economics; D017059:Models, Econometric; D011203:Poverty / Q000191:economics; D055553:Prescription Drugs / Q000191:economics* / Q000627:therapeutic use; D012959:Socioeconomic Factors; D013221:State Health Plans / Q000191:economics*; D014481:United States
D016568:Drugs, Generic; D055553:Prescription Drugs