@文章{info:doi/10.2196/35973，作者="Hota, Bala和Casey, Paul和McIntyre, Anne F和Khan, Jawad和Rab, Shafiq和Chopra, Aneesh和Lateef, Omar和Layden, Jennifer E"，标题="应对COVID-19的基于标准的城市公共卫生信息交换:发展研究"，期刊="JMIR公共卫生监测"，年="2022"，月="9"，日="27"，卷="8"，数="9"，页="e35973"，关键词="公共卫生;信息学;监测;疾病监测;流行病学;健康数据;电子病历;数据中心;急诊医院;COVID-19; pandemic; data governance", abstract="Background: Disease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards. Objective: We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources. Methods: Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems---a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds. Results: Data from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1{\%}) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5{\%} of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. Conclusions: We described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance. ", issn="2369-2960", doi="10.2196/35973", url="https://publichealth.www.mybigtv.com/2022/9/e35973", url="https://doi.org/10.2196/35973", url="http://www.ncbi.nlm.nih.gov/pubmed/35544440" }