Noelle M. Cocoros, Aileen Ochoa, John T. Menchaca, and Michael Klompas are with the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA. Chaim Kirby, Bob Zambarano, Karen Eberhardt, and Catherine Rocchio are with Commonwealth Informatics, Waltham, MA. W. Sanouri Ursprung, Victoria M. Nielsen, and Natalie Nguyen Durham are with Massachusetts Department of Public Health, Boston. Mark Josephson, Diana Erani, and Ellen Hafer are with Massachusetts League of Community Health Centers, Boston. Michelle Weiss and Brian Herrick are with Cambridge Health Alliance, Cambridge, MA. Myfanwy Callahan and Thomas Isaac are with Atrius Health, Boston.
Am J Public Health. 2021 Feb;111(2):269-276. doi: 10.2105/AJPH.2020.305963. Epub 2020 Dec 22.
Automated analysis of electronic health record (EHR) data is a complementary tool for public health surveillance. Analyzing and presenting these data, however, demands new methods of data communication optimized to the detail, flexibility, and timeliness of EHR data.RiskScape is an open-source, interactive, Web-based, user-friendly data aggregation and visualization platform for public health surveillance using EHR data. RiskScape displays near-real-time surveillance data and enables clinical practices and health departments to review, analyze, map, and trend aggregate data on chronic conditions and infectious diseases. Data presentations include heat maps of prevalence by zip code, time series with statistics for trends, and care cascades for conditions such as HIV and HCV. The platform's flexibility enables it to be modified to incorporate new conditions quickly-such as COVID-19.The Massachusetts Department of Public Health (MDPH) uses RiskScape to monitor conditions of interest using data that are updated monthly from clinical practice groups that cover approximately 20% of the state population. RiskScape serves an essential role in demonstrating need and burden for MDPH's applications for funding, particularly through the identification of inequitably burdened populations.
电子健康记录 (EHR) 数据的自动化分析是公共卫生监测的一种补充工具。然而，分析和呈现这些数据需要新的数据通信方法，这些方法要针对 EHR 数据的详细程度、灵活性和及时性进行优化。RiskScape 是一个开源的、交互式的、基于 Web 的、用户友好的 EHR 数据公共卫生监测数据聚合和可视化平台。RiskScape 显示近实时监测数据，并使临床实践和卫生部门能够审查、分析、映射和分析慢性病和传染病的聚合数据趋势。数据展示包括按邮政编码划分的流行率热图、用于趋势分析的时间序列以及 HIV 和 HCV 等疾病的护理级联。该平台的灵活性使其能够快速修改以纳入新的条件，例如 COVID-19。马萨诸塞州公共卫生部 (MDPH) 使用 RiskScape 使用从覆盖该州约 20%人口的临床实践小组每月更新的数据来监测感兴趣的条件。RiskScape 通过确定负担不均的人群，在为 MDPH 的资金申请提供需求和负担方面发挥了重要作用。
