RiskScape: A Data Visualization and Aggregation Platform for Public Health Surveillance Using Routine Electronic Health Record Data

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.

Real-world data for precision public health of noncommunicable diseases: a scoping review

“…An advanced global example is the Electronic Medical Record Support for Public Health (ESPNet) surveillance platform [17] that is the digital infrastructure for Risk-Scape -a data aggregation and visualisation platform that updates monthly to heat map disease prevalence and perform descriptive and time series statistics for various communicable (e.g. chlamydia, influenza) and noncommunicable (e.g., type 1 and type 2 diabetes, obesity, hypertension, asthma) diseases across approximately 20% of the Massachusetts (USA) population [12]. The real-world application of this platform in the Massachusetts Department of Public Health has identified NCD hot spots and risk factor targeting to inform prevention program design [12].…”

“…This capability creates a responsive and agile 'learning public health system' , where continuous, near real-time streams of data relevant for disease prevention and public health is used to improve decision accuracy and preventive care for future populations [7,11]. One example in the USA, RiskScape, aggregates electronic health record (EHR) data in near real-time (~ 1 month) to review, analyse, map and trend data on chronic conditions and infectious diseases in 20% of the Massachusetts population [12]. These analytics are used by relevant state public health departments to monitor conditions of interest and plan interventions according to population risk.…”

A narrative review on the validity of electronic health record-based research in epidemiology

“…Importantly, the epidemiologist must ascertain whether the population captured within the EHR or EHR-derived data is representative of the population targeted for inference. This is particularly true under the paradigm of population health and inferring the health status of a community from EHR-based records [ 13 ]. For example, a study of Clostridium difficile infection at an urban safety net hospital in Philadelphia, Pennsylvania demonstrated notable differences in risk factors in the hospital’s EHR compared to national surveillance data, suggesting how catchment can influence epidemiologic measures [ 14 ].…”

“…Comparing the weighted estimates to the original, non-weighted estimates provides insight into differences in the study participants. In the population health paradigm whereby the EHR is used as a surveillance tool to identify community health disparities [ 13 ], one also needs to be concerned about representativeness. There are emerging approaches for producing such small area community estimates from large observational datasets [ 22 , 23 ].…”

Precision Public Health for Non-communicable Diseases: An Emerging Strategic Roadmap and Multinational Use Cases

“…RiskScape is ESP's interactive, web-based data visualization platform. It provides timely, high-level summaries of specific conditions of interest to public health officials including NCDs like asthma, hypertension, smoking, obesity, and diabetes (39). RiskScape utilizes data from clinical partners that participate in ESP, but is built on a centralized, individual-level, deidentified dataset that is updated monthly.…”