Chicago Data-driven OUD Screening, Engagement, Treatment and Planning (C-DOSETaP) System

项目摘要/摘要 与HHS过量预防战略相一致，这项Hear Data2action创新项目 建议书解决了初级预防、减少危害、治疗OUD和使用 最先进的数据驱动方法，将把伊利诺伊大学的元素整合在一起 医院和诊所(UI Health)和伊利诺伊大学芝加哥分校整合为单一、统一的方法，即 能够降低芝加哥西区乌德的死亡率和发病率。我们将部署一支 结合机器学习(电子健康记录数据的自然语言处理)、状态 报告的处方监测数据，以及患者报告的措施，以确定个人和群体- 将各种UI医疗保健站点的风险分级(优先级2，创新项目)。然后我们将使用 这些数据在个人层面(以促进临床护理)和在社区/系统层面(以 支持资源分配和规划)。

Project Summary/Abstract In alignment with the HHS Overdose Prevention Strategy, this HEAL Data2Action Innovation Project proposal addresses primary prevention, harm reduction, treatment of OUD, and recovery support using a state-of-the-art data driven approach that will bring together elements of the University of Illinois Hospital and Clinics (UI Health) and University of Illinois Chicago into a single, unified approach that is capable of reducing mortality and morbidity from OUD on the westside of Chicago. We will deploy a combination of machine learning (natural language processing of electronic health records data), state reported prescription monitoring data, and patient reported measures to determine individual and group- level OUD risk across the various UI Health care sites (Priority 2, Innovation Project). We will then use this data at both the individual level (to facilitate clinical care) and at the community/system level (to support resource allocation and planning).