JMIR Publications

ABSTRACT

Background:

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected 219 million individuals at the time of writing. A large volume of research findings from observational studies about disease interactions with COVID-19 are being produced almost daily, making it difficult for physicians to keep track of the latest information on COVID-19’s effect on patients with certain pre-existing conditions.

Objective:

In this paper, we describe the creation of a clinical decision support tool, the SMART COVID Navigator, a web application to assist clinicians in treating COVID-19 patients. Our app allows clinicians to access a patient’s electronic health records and identify disease interactions from a large set of observational research studies that affect severity and fatality due to COVID-19.

Methods:

The SMART COVID Navigator takes a two-pronged approach to clinical decision support. The first part is a connection to electronic health record servers, allowing the app to access a patient’s medical conditions. The second is accessing datasets with information on various observational studies to determine the latest research findings about COVID-19 outcomes for patients with certain medical conditions. By connecting these two data sources, users can see how a patient’s medical history will affect their COVID-19 outcomes.

Results:

The SMART COVID Navigator aggregates patient health information from multiple Fast Healthcare Interoperability Resources-enabled electronic health record systems. This allows physicians to see a comprehensive view of patient health records. The application accesses two datasets of over 1,100 research studies to provide information on fatality and severity of COVID-19 for several pre-existing conditions. We also analyze the results of the collected studies to determine which medical conditions result in an increased chance of severity and/or fatality of COVID-19 progression. We find that certain conditions result in a higher likelihood of severity and fatality probabilities. We also analyze various cancer tissues and find that the probabilities for fatality vary greatly depending on the tissue being examined.

Conclusions:

The SMART COVID Navigator allows physicians to predict fatality and severity of COVID-19 progression given a particular patient’s medical conditions. This can allow physicians to determine how aggressively to treat patients infected with COVID-19 and to prioritize different patients for treatment taking into account their prior medical conditions.