From the Department of Biostatistics, School of Public Health, Boston University, Boston, MA.
Ohio Colleges of Medicine Government Resource Center, The Ohio State University Wexner Medical Center, OH.
Epidemiology. 2023 Nov 1;34(6):841-849. doi: 10.1097/EDE.0000000000001653. Epub 2023 Sep 26.
The National Survey on Drug Use and Health (NSDUH) estimated the prevalence of opioid use disorder (OUD) among the civilian, noninstitutionalized people aged 12 years or older in Massachusetts as 1.2% between 2015 and 2017. Accurate estimation of the prevalence of OUD is critical to the success of treatment and resource planning. Various indirect estimation approaches have been used but are subject to data availability and infrastructure-related issues.
We used 2015 data from the Massachusetts Public Health Data Warehouse (PHD) to compare the results of two approaches to estimating OUD prevalence in the Massachusetts population. First, we used a seven-dataset capture-recapture analysis under log-linear model parameterization, controlling for the source dependence and effects of age, sex, and county through stratification. Second, we applied a benchmark-multiplier method in a Bayesian framework by linking health care claims data to death certificate data assuming an extrapolation of death rates from observed untreated OUD to unobserved OUD.
Our estimates for OUD prevalence among Massachusetts residents (aged 18-64 years) were 4.62% (95% CI = 4.59%, 4.64%) in the capture-recapture approach and 4.29% (95% CrI = 3.49%, 5.32%) in the Bayesian model. Both estimates were approximately four times higher than NSDUH estimates.
The synthesis of our findings suggests that the disease surveillance system misses a large portion of the population with OUD. Our study also suggests that concurrent use of multiple methods improves the justification and facilitates the triangulation and interpretation of the resulting estimates.
ClinicalTrials.gov Identifier: NCT04111939.
国家药物使用与健康调查（NSDUH）估计，2015 年至 2017 年，马萨诸塞州年龄在 12 岁及以上的平民非住院人群中阿片类药物使用障碍（OUD）的患病率为 1.2%。准确估计 OUD 的患病率对于治疗和资源规划的成功至关重要。已经使用了各种间接估计方法，但这些方法受到数据可用性和基础设施相关问题的限制。
我们使用了 2015 年马萨诸塞州公共卫生数据仓库（PHD）的数据，比较了两种方法估计马萨诸塞州人群 OUD 患病率的结果。首先，我们使用了对数线性模型参数化的七个数据集捕获-再捕获分析，通过分层控制来源依赖性和年龄、性别和县的影响。其次，我们通过将医疗保健索赔数据与死亡证明数据联系起来，在贝叶斯框架中应用基准乘数方法，假设从观察到的未治疗 OUD 推断到未观察到的 OUD 的死亡率外推，假设从观察到的未治疗 OUD 推断到未观察到的 OUD 的死亡率外推。
我们在捕获-再捕获方法中估计马萨诸塞州居民（年龄在 18-64 岁之间）的 OUD 患病率为 4.62%（95%置信区间=4.59%，4.64%），贝叶斯模型中为 4.29%（95%CrI=3.49%，5.32%）。这两个估计值都大约是 NSDUH 估计值的四倍。
我们的综合研究结果表明，疾病监测系统漏掉了很大一部分患有 OUD 的人群。我们的研究还表明，同时使用多种方法可以提高合理性，并有助于对得出的估计值进行三角测量和解释。
ClinicalTrials.gov 标识符：NCT04111939。
