A simulation model of policies directed at treating tobacco use and dependence.

OBJECTIVES: The authors develop a simulation model to predict the effects on quit rates and cost-effectiveness of different smoking treatment policies.
METHODS: A decision theoretic model of quit behavior is first developed that incorporates the decision to quit and the choice of treatment. A policy model then examines the effect on quit attempts and quit rates of policies to cover the costs of different combinations of treatments and to require health care providers to conduct brief interventions. The model incorporates substitution between treatments and effects of policies on treatment effectiveness. The cost per quit is also calculated for each policy.
RESULTS: The model of quit behavior predicts a 1-year quit rate of 4.5% for the population of smokers. The policy model predicts a 37% increase in quit rates from a policy that combines mandated brief interventions with coverage of all proven tobacco treatments. Smaller effects are predicted from policies that provide more restricted coverage of treatments, especially those limited to behavioral treatment. Payments for brief interventions alone increase quit rates by about 7%. Brief intervention and behavioral therapy policies had lower costs per quit but yield substantially fewer additional quits than policies that cover pharmacotherapy. There is, however, considerable variation around these estimates depending on assumptions about the effects of policy on treatment use, substitution between treatments, and treatment effectiveness.
CONCLUSION: Tobacco treatment policies, especially those with broad and flexible coverage, have the potential to substantially increase smoking quit rates. However, further research is needed on the effect of payment policies on the use and effectiveness of tobacco treatments.