Impact of State Policies on Smoking among Individuals with Substance Use Disorder

项目摘要/摘要 越来越多的证据表明，有必要将吸烟者的物质使用障碍(SUD)识别为关键 在评估与烟草有关的使用和疾病方面，评估不平等群体，并确定解决这一不平等问题的战略。 吸烟经常与其他非法药物和酒精的使用并存，并协同作用地恶化健康。许多 随着年龄的增长，他们从SUD中恢复过来，仍然依赖烟草，患癌症和其他疾病的风险更高 与吸烟相关的并发症和死亡率(患有SUD的吸烟者的死亡率是非吸烟者的4倍 吸烟者患有SUD)。尽管吸烟者对尼古丁的依赖更大，戒烟难度更大，但 SUD，患有SUD的吸烟者经常报告强烈的戒烟愿望，烟草依赖治疗(TDT)是 在这群人中很有效。此外，戒烟已反复被证明可以改善sud。 治疗结果，抵消了通常将尼古丁依赖作为SUD较低优先事项的情况 治疗。然而，这一人群中TDT的发生率仍然很低。最近，许多州都扩大了 TDT的医疗补助覆盖范围，但尚不清楚这是否增加了治疗服务的使用 弱势群体。烟草税和其他烟草控制政策也成功地减少了吸烟。 费率一般，但对患有SUD的吸烟者的有效性尚不清楚。 我们建议评估扩大烟草税覆盖范围和烟草消费税对烟草税使用的影响。 使用2004-16年医疗补助分析摘录对患有SUD的吸烟者的服务、吸烟强度和戒烟率 (MAX)所有50个州的索赔数据，以及2004-2018年全国药物使用与健康调查(NSDUH)， 合并到州医疗补助福利和州、市和县级烟草政策的数据集。拿走 随着时间的推移，州内和州之间的差异的优势，我们应用严格的方法(差异-在- 差异分析和个人固定效应模型)，以评估戒烟政策的因果影响。 在目标1中，我们测试了医疗补助TDT覆盖范围对TDT的启动和维持以及对退出的影响 患有SUD的医疗补助受益人中的吸烟情况。在目标2中，我们测试了增加香烟消费额的效果 对吸烟强度和戒烟的税收，在更广泛的全国范围内抽样调查患有自闭症的个人。 在目标3中，我们评估了TDT和税收政策对医疗补助中烟草使用的综合影响 获益者为SUD患者。 我们假设TDT的保险范围会激励TDT寻求治疗，而增税会产生 强烈的戒烟动机，这两项政策结合在一起将放大离职率。我们一直与 利益相关者提出分析建议，为复杂现实世界政策环境中的决策者提供信息 难以接触到的人群，我们纳入了一个传播计划，为可采取行动奠定基础 针对州烟草控制经理、州SUD服务机构、SUD治疗的政策变化 不愿纳入TDT的提供者，以及集成的行为健康提供者。

Project Summary/ Abstract Growing evidence supports the need to both recognize smokers with substance use disorder (SUD) as a key disparity group in evaluating tobacco-related use and disease, and identify strategies to address this disparity. Smoking frequently co-occurs with other illicit drug and alcohol use and synergistically worsens health. Many who recover from SUD as they age remain dependent on tobacco and are at higher risk for cancer and other smoking-related complications, and mortality (smokers with SUD have mortality rates 4 times higher than non- smokers with SUD). Despite greater nicotine dependence and more difficulty quitting among smokers with SUD, smokers with SUD often report a strong desire to quit, and tobacco dependence treatment (TDT) is effective in this population. Moreover, smoking cessation has repeatedly been shown to improve SUD treatment outcomes, countering the common dismissal of nicotine dependence as a lower priority in SUD treatment. However, rates of TDT in this population remain low. Recently, many states have expanded Medicaid coverage of TDT, but it is unclear whether this has increased use of treatment services in this vulnerable group. Tobacco tax and other tobacco control policies have also successfully reduced smoking rates generally, but effectiveness for smokers with SUD is unknown. We propose to assess the impact of expanded TDT coverage and tobacco excise taxes on use of TDT services, smoking intensity and quit rates for smokers with SUD using the 2004-16 Medicaid Analytic Extract (MAX) claims data from all 50 states, and the 2004-2018 National Survey of Drug Use and Health (NSDUH), merged to datasets of state Medicaid benefits and state-, city-, and county-level tobacco policies. Taking advantage of variation within and between states over time, we apply rigorous methods (difference-in- difference analyses and individual fixed-effects models) to assess causal effects of tobacco cessation policies. In Aim 1, we test the effect of Medicaid TDT coverage on initiation and maintenance of TDT and on quitting smoking among Medicaid beneficiaries with SUD. In Aim 2, we test the effect of increasing cigarette excise taxes on the intensity of smoking and smoking cessation in a broader national sample of individuals with SUD. In Aim 3, we assess the combined effects of TDT and tax policies on tobacco use among Medicaid beneficiaries with SUD. We hypothesize that insurance coverage of TDT incentivizes TDT treatment-seeking, that rising taxes create strong incentives to quit, and that both policies together will amplify quitting rates. We have worked closely with stakeholders to propose analyses that inform decision-makers in complex real-world policy environments with hard-to-reach populations, and we incorporate a dissemination plan that lays the groundwork for actionable policy changes by targeting state tobacco control managers, state SUD services agencies, SUD treatment providers reluctant to incorporate TDT, and integrated behavioral health providers.