Modeling the impact of smoking-cessation treatment policies on quit rates.
BACKGROUND
Smoking-cessation treatment policies could yield substantial increases in adult quit rates in the U.S.


OBJECTIVE
The goals of this paper are to model the effects of individual cessation treatment policies on population quit rates, and to illustrate the potential benefits of combining policies to leverage their synergistic effects.


METHODS
A mathematical model is updated to examine the impact of five cessation treatment policies on quit attempts, treatment use, and treatment effectiveness. Policies include: (1) expand cessation treatment coverage and provider reimbursement; (2) mandate adequate funding for the use and promotion of evidence-based, state-sponsored telephone quitlines; (3) support healthcare system changes to prompt, guide, and incentivize tobacco treatment; (4) support and promote evidence-based treatment via the Internet; and (5) improve individually tailored, stepped-care approaches and the long-term effectiveness of evidence-based treatments.


RESULTS
The annual baseline population quit rate is 4.3% of all current smokers. Implementing any policy in isolation is projected to increase the quit rate to between 4.5% and 6%. By implementing all five policies in combination, the quit rate is projected to increase to 10.9%, or 2.5 times the baseline rate.


CONCLUSIONS
If fully implemented in a coordinated fashion, cessation treatment policies could reduce smoking prevalence from its current rate of 20.5% to 17.2% within 1 year. By modeling the policy impacts on the components of the population quit rate (quit attempts, treatment use, treatment effectiveness), key indicators are identified that need to be analyzed in attempts to improve the effect of cessation treatment policies.
Levy
David T
DT
Pacific Institute for Research and Evaluation, University of Baltimore, Calverton, Maryland 20705, USA. Levy@pire.org
Graham
Amanda L
AL
Mabry
Patricia L
PL
Abrams
David B
DB
Orleans
C Tracy
CT
D000328:Adult; D003695:Delivery of Health Care; D037001:Directive Counseling / Q000191:economics; D055317:Evidence-Based Practice; D006293:Health Promotion / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D020407:Internet; D015233:Models, Statistical; D009042:Motivation; D011050:Policy Making; D015397:Program Evaluation / Q000706:statistics & numerical data*; D012907:Smoking / Q000453:epidemiology*; D016540:Smoking Cessation / Q000706:statistics & numerical data; D013689:Telephone; D014481:United States / Q000453:epidemiology