Enhancing Infrastructure for Clinical and Translational Research to Address the Opioid Epidemic

加强临床和转化研究基础设施以应对阿片类药物流行病

• 批准号: 10646250
• 负责人: LESLIE A. LENERT
• 金额: $ 71.16万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-06 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10646250
• 关键词: Acceleration; Accident and Emergency department; Address; Algorithms; Automation; California; Clinical Data; Clinical Research; Clinical Trials; Clinical Trials Database; Clinical Trials Network; Code; Country; Data; Databases; Dedications; Effectiveness; Electronic Health Record; Epidemic; Evaluation; Evolution; Fentanyl; Funding; Health; Health Care Costs; Health system; Healthcare Systems; Heroin; Hospitals; Individual; Infrastructure; Institution; International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10); Intervention; Intervention Trial; Investments; Kentucky; Laboratories; Modification; Monitor; Morbidity - disease rate; National Center for Advancing Translational Sciences; National Institute of Drug Abuse; Natural Language Processing; Non-Prescription Drugs; Odds Ratio; Opiate Addiction; Opioid; Outcome Study; Overdose; Patients; Pharmaceutical Preparations; Phenotype; Policies; Predictive Value; Prevention; Prevention Research; Procedures; Process; Public Health; Research; Resources; Site; Source; System; Time; Training; Translational Research; United States; Universities; Work; clinical care; clinical infrastructure; combat; comorbidity; data dictionary; data infrastructure; data integration; data modeling; data tools; demographics; design; effective therapy; electronic health data; fitness; high risk population; innovation; inter-institutional; mortality; natural language; opioid epidemic; opioid misuse; opioid overdose; opioid use disorder; overdose prevention; point of care; prescription opioid; prescription opioid misuse; prototype; response; service delivery; social; social health determinants; synthetic opioid; therapy design; therapy development; tool; translational study; treatment research; trial planning; usability

PROJECT SUMMARY Up-to-date information about non-fatal overdose emergency department (ED) encounters can provide critical information about the evolution of the opioid epidemic and response of the healthcare system and is an essential to planning of clinical trials to address the problems underlying this epidemic. Establishing a platform that delivers high positive predictive value for opioid-related overdose (OD) using a combination of coded and natural language terms in electronic health records (EHRs) is an essential step toward the large-scale surveillance necessary to evaluate the pragmatic effectiveness of numerous systemic and policy-based efforts and to create the infrastructure for large scale trials to reduce drug-related mortality and morbidity. However, to date, localized and federal efforts have been largely based on discrete ICD-10 code data or have had time lags of one-to-three years for more detailed data. Perhaps more Importantly, they have not had the capacity for planning and feasibility assessment for clinical and translational research at specific sites. We propose foundational work to create an inter-institutional research database and network focused on patients presenting to EDs with opioid-related OD. To create this network, we will extend previous work to develop: (1) an e-phenotype for case identification in the ED based on EHR data, and (2) combine this with a data dictionary and coded data extraction tools, and natural language processing (NLP) algorithms, to obtain additional data from EHRs; tools for primary capture of data during clinical care; and tools for integration of data on social determinants of health. This will allow for a more thorough characterization of individuals presenting to EDs with opioid-related OD including: demographics, comorbidities, OD agent and source, intentionality of the OD, ED treatment and discharge disposition. Through refinement and automation, the data extraction process will be extended to a set of pilot CTSA Accrual to Clinical Trials (ACT) Network sites and then potentially to other CTSA's nation-wide. This new functionality focuses on providing a platform to accelerate research. To accomplish this work, our Specific Aims are to: 1) Demonstrate the feasibility of extending the ACT Network data model and infrastructure to monitor the opioid epidemic using ED data, 2) Create a prototype opioid overdose monitoring and response network across participating institutions and a toolkit for other CTSA sites to join the network, and 3) Demonstrate potential usefulness of the network in monitoring the opioid epidemic and in planning clinical trials. This proposal is innovative as it aims to develop a feasible and effective near real time means of monitoring opioid-related OD presentation in EDs across the country to inform point-of-care service delivery, prevention and treatment intervention development and evaluation. Downstream, the application of project deliverables include dissemination of the replication toolkit to leverage the platform of the CTSAs and NIDA Clinical Trials Network to build capacity for timely surveillance of opioid-related OD to facilitate prevention and treatment research and intervention.

项目摘要 有关非致命过量急诊科（ED）遭遇的最新信息可以提供关键 有关阿片类药物流行和医疗保健系统反应的进化的信息，这是一种 对于临床试验的计划至关重要，以解决这种流行病的基础问题。建立平台 通过编码和 电子健康记录中的自然语言术语（EHRS）是大规模迈出的重要一步 评估众多系统和政策努力的务实有效性所需的监视 并为大规模试验创建基础设施，以降低与药物有关的死亡率和发病率。但是，要 日期，本地化和联邦的努力主要基于离散的ICD-10代码数据或时间滞后 一到三年，以获取更详细的数据。也许更重要的是，他们没有能力 在特定地点进行临床和翻译研究的计划和可行性评估。我们建议 创建机构间研究数据库和网络的基础工作，重点是患者 用阿片类药物相关的OD向ED呈现。为了创建此网络，我们将扩展以前的工作以开发：（1） 基于EHR数据中的ED中的病例识别的电子表型，（2）将其与数据结合 词典和编码数据提取工具以及自然语言处理（NLP）算法，以获得 EHR的其他数据；在临床护理期间主要捕获数据的工具；和集成的工具 有关健康决定因素的数据。这将使个人更彻底地表征 与阿片类药物相关的OD介绍ED，包括：人口统计，合并症，OD代理和来源， OD，ED治疗和排出处置的意图。通过改进和自动化，数据 提取过程将扩展到一组临床试验（ACT）网站和 然后有可能转移到其他CTSA在全国范围内。这种新功能着重于提供一个平台 加速研究。为了完成这项工作，我们的具体目的是：1）证明 扩展ACT网络数据模型和基础架构以使用ED数据监测阿片类药物流行，2） 在参与机构和一个 其他CTSA站点加入网络的工具包，3）在 监测阿片类药物流行病和计划临床试验。该建议具有创新性，因为它旨在开发一个 可行且有效的近实时手段，在整个ED中监测与阿片类药物相关的OD表示 为保健服务提供点提供，预防和治疗干预开发的国家 /地区 评估。下游，项目可交付物的应用包括传播复制工具包 利用CTSA和NIDA临床试验网络的平台来建立及时监视的能力 阿片类药物相关的OD促进预防和治疗研究和干预。

项目成果

The effectiveness of a noninterruptive alert to increase prescription of take-home naloxone in emergency departments.

• DOI: 10.1093/jamia/ocac257
• 发表时间: 2023-03-16
• 期刊: JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
• 影响因子: 6.4
• 作者: Jennings, Lindsey K.;Ward, Ralph;Pekar, Ekaterina;Szwast, Elizabeth;Sox, Luke;Hying, Joseph;Mccauley, Jenna;Obeid, Jihad S.;Lenert, Leslie A.
• 通讯作者: Lenert, Leslie A.