University of Illinois at Chicago, Chicago, IL.
AMIA Annu Symp Proc. 2023 Apr 29;2022:580-586. eCollection 2022.
With an increasing number of overdose cases yearly, the city of Chicago is facing an opioid epidemic. Many of these overdose cases lead to 911 calls that necessitate timely response from our limited emergency medicine services. This paper demonstrates how data from these calls along with synthetic and geospatial data can help create a syndromic surveillance system to combat this opioid crisis. Chicago EMS data is obtained from the Illinois Department of Public Health with a database structure using the NEMSIS standard. This information is combined with information from the RTI U.S. Household Population database, before being transferred to an Azure Data Lake. Afterwards, the data is integrated with Azure Synapse before being refined in another data lake and filtered with ICD-10 codes. Afterwards, we moved the data to ArcGIS Enterprise to apply spatial statistics and geospatial analytics to create our surveillance system.
随着每年过量用药案例的增加,芝加哥市正面临阿片类药物泛滥的问题。这些过量用药案例中有许多导致了 911 报警电话,这需要我们有限的紧急医疗服务部门及时做出响应。本文展示了这些报警电话中的数据,以及综合和地理空间数据,如何帮助创建一个综合征监测系统,以应对这场阿片类药物危机。芝加哥紧急医疗服务数据是从伊利诺伊州公共卫生部获得的,数据库结构采用 NEMSIS 标准。这些信息与 RTI 美国家庭人口数据库的信息结合,然后转移到 Azure 数据湖中。之后,数据与 Azure Synapse 集成,然后在另一个数据湖中进行细化,并使用 ICD-10 代码进行筛选。之后,我们将数据移动到 ArcGIS Enterprise 中,应用空间统计和地理空间分析来创建我们的监测系统。