Early retirement and the influence on healthcare budgets and insurance premiums in a diabetes population.
OBJECTIVE
To contribute to current discussions about budget impact modeling, two different approaches for the impact of a new pharmaceutical product were analyzed: firstly considering the impact on annual healthcare expenditures only, and secondly additional inclusion of lost insurance premiums due to possible early retirement in patients with chronic diseases.


METHODS
The dynamic model calculates the budget impact from two different perspectives: (a) the impact on healthcare expenditures and (b) on expenditures as well as on health insurance revenues due to premiums. The latter approach could especially be useful for patients with chronic diseases who have higher probabilities of early retirement. Early retirement rates and indirect costs were derived from published data. Healthcare premiums were calculated based on an average premium and a mean income. Epidemiological input data were obtained from the literature. Time horizon was 10 years.


RESULTS
Results in terms of reimbursement decisions of the budget impact analysis varied depending on the assumptions made for the insurance premiums, costs, and early retirement rate. Sensitivity analyses revealed that in extreme cases the decision for accepting a new pharmaceutical product would probably be negative using approach (a), but positive using approach (b).


CONCLUSIONS
Depending on the disease and population of interest in a budget impact analysis, not only the healthcare expenditures for a health insurance have to be considered but also the revenue side for an insurance due to retirement should be included.
Walzer
Stefan
S
Analytica International, Untere Herrenstrasse 25, 79539 Loerrach, Germany. stefan.walzer@access.unizh.ch
D002017:Budgets; D017281:Cost of Illness; D003661:Decision Support Techniques; D003920:Diabetes Mellitus / Q000188:drug therapy / Q000191:economics*; D005249:Fees and Charges; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D007004:Hypoglycemic Agents / Q000191:economics / Q000627:therapeutic use; D007328:Insulin / Q000191:economics / Q000627:therapeutic use; D007348:Insurance, Health / Q000191:economics*; D008875:Middle Aged; D017059:Models, Econometric; D012179:Retirement / Q000191:economics*
D007004:Hypoglycemic Agents; D007328:Insulin
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