Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019

Jose, Thulasee; Warner, David O.; O’Horo, John C.; Peters, Steve G.; Chaudhry, Rajeev; Binnicker, Matthew J.; Burger, Charles D.

Objective To describe the design, implementation and utilization of Electronic Health Record (EHR) based digital health surveillance strategies used to manage the coronavirus disease (COVID-19) pandemic and ensure delivery of high quality clinical care such as case identification, remote monitoring, telemedicine services, and recruitment to clinical trials at Mayo Clinic. Setting Mayo Clinic, a large multistate integrated health care system with over 1.5 million annual patient visits that utilizes the Epic© electronic health record (EHR) system. Methods and Results Rule-based live registries were designed in EHR system to classify patients who 1) are currently tested positive for COVID-19; 2) were tested positive but has recovered from COVID-19; 3) are suspected of COVID-19 but did not yet meet clinical diagnostic criteria,; 4) had tested negative for COVID-19; and 5) exceeded a risk score for serious complications from COVID-19. Using registries, custom dashboards and operational reports were developed to provide daily high-level summary for clinical practice use and provide up to date information used to manage individual patients impacted by COVID-19, including support of case identification, contact isolation and other care management tasks. Conclusion we developed and implemented a systematic approach for using EHR patient registries to manage the COVID-19 pandemic that proved feasible and useful for managing a large multistate group clinical practice. The key to harnessing the potential of digital surveillance tools to promote patient-centered care during COVID-19 pandemic was to use the registry data, reports and dashboards as informatics tools to inform decision-making.