2013
DOI: 10.1016/j.jsat.2013.01.011
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An updated algorithm for choosing among smoking cessation treatments

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Cited by 30 publications
(19 citation statements)
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“…Given the benefits of cessation, such caveats should rarely prevent use of nicotine replacement therapy. 9,10 A 2013 meta-analysis of treatment-specific reviews in the Cochrane Database reported an odds ratio (OR) of 1.84 (95% confidence interval [CI] 1.71-1.99) for nicotine replacement therapy versus placebo.…”
Section: What Medications Can Help Patients To Quit Smoking?mentioning
confidence: 99%
“…Given the benefits of cessation, such caveats should rarely prevent use of nicotine replacement therapy. 9,10 A 2013 meta-analysis of treatment-specific reviews in the Cochrane Database reported an odds ratio (OR) of 1.84 (95% confidence interval [CI] 1.71-1.99) for nicotine replacement therapy versus placebo.…”
Section: What Medications Can Help Patients To Quit Smoking?mentioning
confidence: 99%
“…5,23-27 However, we detected no effect of the AQC on measures of duration of use, including receipt of 90 or more days of pharmacotherapy among users or receipt of more than one counseling visit among users, despite evidence that higher-intensity treatments are often more effective than lower-intensity treatments. 5,28 Our findings that the AQC increased the probability of cessation treatment use relative to a comparison group of BCBSMA enrollees suggest that the incentives inherent in a multi-year global payment contract for providers to prioritize use of services with the potential to lower the future disease burden within a population such as tobacco cessation therapies led to greater provision of these services. These incentives drove changes in utilization patterns even in the absence of specific outpatient cessation performance metrics.…”
Section: Discussionmentioning
confidence: 86%
“…Therefore, it is of considerable public health importance that such populations benefit from smoking cessation treatments. Further, it is important to determine whether person factors (e.g., gender, race) or smoking-related factors (e.g., tobacco dependence) might effectively guide treatment selection or allocation (Hughes, 2013; Loh et al, 2012). …”
Section: Introductionmentioning
confidence: 99%