Stevens Andrew, Karki Saugat, Shivers Elizabeth, Pérez Alejandro, Choi Myung, Berro Andre, Riley Michael, Yang Jane, Tassev Plamen, Jackson David Alexander, Kim Inho, Duke Jon D
Georgia Tech Research Institute, Atlanta, GA 30308, United States.
Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA 30333, United States.
JAMIA Open. 2024 Dec 28;8(1):ooae145. doi: 10.1093/jamiaopen/ooae145. eCollection 2025 Feb.
The resurgence of syphilis in the United States presents a significant public health challenge. Much of the information needed for syphilis surveillance resides in electronic health records (EHRs). In this manuscript, we describe a surveillance platform for automating the extraction of EHR data, known as SmartChart Suite, and the results from a pilot.
The SmartChart Suite framework has been developed in compliance with the HHS Health IT Alignment Policy. The platform's major functionalities are (1) data retrieval; (2) logical evaluation; (3) standardized data storage; and (4) results display. The SmartChart Suite was deployed in September 2023 at the Grady Health System in Atlanta, Georgia. We established a cohort of likely syphilis patients, randomly selected 50 medical records for manual and automated chart review, and analyzed the results.
The SmartChart Suite was successfully deployed and integrated with the Epic EHR system at Grady. The overall performance results were precision of 97.6%, recall of 100.0%, and F-Score of 98.8.
Automated abstraction of EHR data has significant potential to improve public health surveillance and case investigation processes while reducing the resource burden on health departments and reporters. The SmartChart Suite comprises a flexible open-source solution for registry development and maintenance across a wide spectrum of conditions and use cases.
SmartChart Suite demonstrates the potential of automated chart abstraction to support disease surveillance. HHS-compliant open-source tools such as SmartChart Suite can support more efficient human review by providing accurate and relevant data for critical public health activities.
梅毒在美国的再度流行对公共卫生构成了重大挑战。梅毒监测所需的许多信息都存在于电子健康记录(EHR)中。在本手稿中,我们描述了一个用于自动提取EHR数据的监测平台,即智能图表套件(SmartChart Suite),以及一项试点的结果。
智能图表套件框架的开发符合美国卫生与公众服务部(HHS)的健康信息技术对齐政策。该平台的主要功能包括:(1)数据检索;(2)逻辑评估;(3)标准化数据存储;(4)结果显示。智能图表套件于2023年9月在佐治亚州亚特兰大的格雷迪健康系统(Grady Health System)部署。我们建立了一个可能患有梅毒的患者队列,随机选择50份病历进行人工和自动图表审查,并分析结果。
智能图表套件已成功部署并与格雷迪的Epic EHR系统集成。总体性能结果为精确率97.6%,召回率100.0%,F值98.8。
EHR数据的自动提取在改善公共卫生监测和病例调查流程方面具有巨大潜力,同时可减轻卫生部门和报告者的资源负担。智能图表套件为跨多种疾病和用例的登记册开发和维护提供了一个灵活的开源解决方案。
智能图表套件证明了自动图表提取在支持疾病监测方面的潜力。像智能图表套件这样符合HHS标准的开源工具可以通过为关键的公共卫生活动提供准确和相关的数据来支持更高效的人工审查。