@Article{info:doi/10.2196/29279,
author="Suraj, Varun
and Del Vecchio Fitz, Catherine
and Kleiman, Laura B
and Bhavnani, Suresh K
and Jani, Chinmay
and Shah, Surbhi
and McKay, Rana R
and Warner, Jeremy
and Alterovitz, Gil",
title="SMART COVID Navigator, a Clinical Decision Support Tool for COVID-19 Treatment: Design and Development Study",
journal="J Med Internet Res",
year="2022",
month="Feb",
day="18",
volume="24",
number="2",
pages="e29279",
keywords="COVID-19; clinical decision support; precision medicine; web application; FHIR",
abstract="Background: COVID-19 caused by SARS-CoV-2 has infected 219 million individuals at the time of writing of this paper. A large volume of research findings from observational studies about disease interactions with COVID-19 is 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 patients with COVID-19. Our application allows clinicians to access a patient's electronic health records and identify disease interactions from a large set of observational research studies that affect the severity and fatality due to COVID-19. Methods: The SMART COVID Navigator takes a 2-pronged approach to clinical decision support. The first part is a connection to electronic health record servers, allowing the application to access a patient's medical conditions. The second is accessing data sets with information from various observational studies to determine the latest research findings about COVID-19 outcomes for patients with certain medical conditions. By connecting these 2 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 2 data sets of over 1100 research studies to provide information on the fatality and severity of COVID-19 for several pre-existing conditions. We also analyzed the results of the collected studies to determine which medical conditions result in an increased chance of severity and fatality of COVID-19 progression. We found 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 the 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 considering their prior medical conditions. ",
issn="1438-8871",
doi="10.2196/29279",
url="https://www.jmir.org/2022/2/e29279",
url="https://doi.org/10.2196/29279",
url="http://www.ncbi.nlm.nih.gov/pubmed/34932493"
}