Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019

15 Dec, 2020

Abstract

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 EpicĀ© 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.


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