A simulation model that estimates individual health care spending as a function of the structure of indemnity-type insurance plans is presented. The behavioral models that form the basis for this work were developed as part of RAND's Health Insurance Experiment, (HIE), a randomized clinical trial. The randomized design and statistical methods provided estimates of the effects of insurance on use, uncontaminated by sickness or selection effects. The demand for medical care was modeled using episodes of treatment. Within the simulation, episodes occur independently and randomly through time according to a Poisson process with rates depending on individual characteristics and insurance. Empirical results from the HIE indicated that insurance primarily affects individual decisions to seek treatment (episode frequency), but has only minimal effects on episode costs. The response to changes in price (insurance) is modeled as a Bernoulli censoring process on episode frequency. The model is used to address issues on the effective design of insurance plans.