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RiskScape: A Data Visualization and Aggregation Platform for Public Health Surveillance Using Routine Electronic
Noelle M Cocoros1, Chaim Kirby1, Bob Zambarano1
1Noelle 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.
Abstract:
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.
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