Varying pharmacy benefits with clinical status: the case of cholesterol-lowering therapy.
OBJECTIVE
To determine whether a pharmacy benefit that varies copayments for cholesterol-lowering (CL) therapy according to expected therapeutic benefit would improve compliance and reduce use of other services.


METHODS
Using claims data from 88 health plans, we studied 62 274 patients aged 20 years and older who initiated CL therapy between 1997 and 2001. We examined the association between copayments and compliance in the year after initiation of therapy, and the association between compliance and subsequent hospital and emergency department (ED) use for up to 4 years after initiation.


RESULTS
The fraction of fully compliant patients fell by 6 to 10 percentage points when copayments increased from 10 dollars to 20 dollars, depending on patient risk (P < .05). Full compliance was associated with 357 fewer hospitalizations annually per 1000 high-risk patients (P < .01) and 168 fewer ED visits (P < .01) compared with patients not in full compliance. For patients at low risk, full compliance was associated with 42 fewer hospitalizations (P = .02) and 21 fewer ED visits (P = .22). Using these results, we simulated a policy that eliminated copayments for high- and medium-risk patients but raised them (from 10 dollars to 22 dollars) for low-risk patients. Based on a national sample of 6.3 million adults on CL therapy, this policy would avert 79,837 hospitalizations and 31,411 ED admissions annually.


CONCLUSIONS
Although many obstacles exist, varying copayments for CL therapy by therapeutic need would reduce hospitalizations and ED use--with total savings of more than 1 billion dollars annually.
Goldman
Dana P
DP
RAND Corporation, Santa Monica, CA 90407-2138, USA. dgoldman@rand.org
Joyce
Geoffrey F
GF
Karaca-Mandic
Pinar
P
D000328:Adult; D000368:Aged; D000924:Anticholesteremic Agents / Q000191:economics / Q000627:therapeutic use; D003362:Cost-Benefit Analysis; D003669:Deductibles and Coinsurance / Q000191:economics; D016527:Drug Costs / Q000706:statistics & numerical data; D011307:Drug Prescriptions / Q000191:economics; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006264:Health Benefit Plans, Employee / Q000191:economics; D006302:Health Services Research; D006304:Health Status; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data; D007356:Insurance, Pharmaceutical Services / Q000191:economics* / Q000592:standards; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D017063:Outcome Assessment, Health Care; D010349:Patient Compliance / Q000706:statistics & numerical data*; D020379:Risk Adjustment; D014481:United States
D000924:Anticholesteremic Agents