Opioid and SUD Data Enclave (O-SUDDEn): Bringing real-time data to the opioid crisis

摘要 合成阿片类药物(芬太尼)的广泛使用推动了意外死亡人数的迅速上升。 剂量(OD)死亡。政策制定者、州和地方机构以及调查人员一直在关注俄亥俄州 由于俄亥俄州的代表性，作为其他州经验的领头羊 人口统计数据。缺乏及时的与地理空间相关联的纵向数据源阻碍了 社区和国家机构将资源分配转移到最需要它们的地区。有限 整合环境风险因素，如社会人口特征，不能支持确定 干预的新目标或应对当地毒品供应变化带来的新威胁的新方法。我们 相信敏捷的数据系统和信息学工具可以用来演示预测的效用 有关如何实现数据驱动决策的分析和机器智能方法最终将 证明是可以在全国和不同地区翻译的。我们提出的阿片类药物使用障碍 数据飞地(O-突发性)将提供一种新的、变革性的方法来支持严谨和 关于阿片类药物和药物使用危机的可重复研究。O-猝发将填补数据中的几个现有空白 基础设施和预测模型，包括机器学习、地理空间分析和社区环境。 O-突发事件的具体目标如下：目标1：数据链接与O-突发事件的建立。我们 将开发一个地理空间敏感、个体级别安全的数据湖，该数据湖集成了多种不同的数据 符合HIPAA规定的编码限制集要求的来源。新数据源包括实时 来自尿液药物测试(UDT)的个人层面的纵向数据和基于 俄亥俄州机会指数，这是我们团队开发和使用的地区层面的健康社会决定因素。我们会 为数据协调和集成开发查询和使用工具，准备和发布数据集 传播和辅助数据分析；并促进相关行政数据的辅助使用，以 产生证据，为有针对性的阿片类药物干预提供信息。目标2：开发预测模型和 监控算法。地理空间和机器学习将被用来模拟阿片类药物的作用， 可卡因、兴奋剂使用过量、过量死亡和阿片类药物使用障碍/物质使用障碍(OUD/SUD)； 实时数据的时间关系，包括UDT和人口统计和上下文变量，以识别高 风险人群和亚人群或地理位置。我们将验证模型性能和预测 然后通过面向最终用户的O-Aurant门户网站传播监控和预测算法 进入。目标3：部署以人为中心的平台和行为信息学。应用协同设计原则 由最终用户利益相关者(社区、研究人员和州政府)组成的以人为中心的工作组 政策制定者/机构)，我们将开发和部署一个最终用户定制的门户和有效的用户友好工具 提供可操作的见解，为阿片类药物治疗和有针对性的减少伤害战略提供信息。

ABSTRACT The widespread availability of synthetic opioids (fentanyl) has fueled the rapidly rising rates of unintentional over dose (OD) fatalities. Policy makers, state and local agencies, and investigators have focused on the Ohio experience as a bellwether for the experiences of other states because of the representativeness of Ohio’s demographics. The lack of timely geospatially-linked longitudinal data sources has impeded the ability of communities and state agencies to pivot allocation of resources to regions where they are needed most. Limited integration of environmental risk factors such as sociodemographic characteristics fail to support identification of new targets for intervention or new approaches to emerging threats from changes in local drug supply. We believe that agile data systems and informatics tools that can be used to demonstrate the utility of predictive analytics and machine intelligence approaches on how to enable data-driven decision making will ultimately prove translatable across the country and diverse localities. Our proposed Opioid and Substance Use Disorder Data Enclave (O-SUDDEn) will provide a novel and transformative approach to support rigorous and reproducible research on the opioid and substance use crises. O-SUDDEn will fill several existing gaps in data infrastructure and prediction models that include machine learning, geospatial analyses, and community context. The specific aims for O-SUDDEn are as follows: Aim 1: Data linkage with establishment of O-SUDDEn. We will develop a geospatially-sensitive, individual-level secure data lake that integrates multiple disparate data sources that meets the requirement of a coded-limited set under HIPAA. New data sources include real-time individual-level longitudinal data from urine drug testing (UDT) and community contextual data based on the Ohio Opportunity Index, an area-level social determinants of health developed and used by our team. We will develop query and use tools for data harmonization and integration, prepare and release data sets for dissemination and secondary data analyses; and facilitate secondary use of related administrative data to generate evidence that informs targeted opioid interventions. Aim 2: Develop Predictive Models and Surveillance algorithms. Geospatial and machine learning will be used to model the contribution of opioid, cocaine, and stimulant use on OD, OD death and opioid use disorder/substance use disorder (OUD/SUD); temporal relationship of real time data including UDT and demographic and contextual variables to identify high- risk populations and subpopulations or geographic locales. We will validate model performances and predictive power and then disseminate surveillance and forecasting algorithms through the O-SUDDEn portal for end-user access. Aim 3: Deploy a human-centered platform and actional informatics. Applying co-design principles with a human-centered work group consisting of end-user stakeholders (community, researchers, and state policy makers/agencies), we will develop and deploy an end-user tailored portal and effective user-friendly tools to provide actionable insights to inform opioid treatment and targeted harm reduction strategies.