In a project funded by the National Institutes of Health, Xiaoming Li and Bankole Olatosi, co-directors of the UofSC Big Data Health Science Center, are acquiring de-identified electronic health records for all COVID-19 patients in South Carolina to develop a statewide data-driven system to respond to the pandemic. The first iteration of data came from more than 280,000 adult patients who were diagnosed from March through December 2020, with the number growing to more than 440,000 in early February.
The patient information, which includes underlying conditions, diagnoses, symptoms, disease progression, clinical outcomes and health utilization data, comes from the South Carolina Department of Health and Environmental Control, hospitals and other state agencies and stakeholders. Any information that identifies a patient is removed before the data is processed.
By applying big data science to the dataset, researchers will be able to use data clustering and data visualization to examine trajectories of the disease’s severity, treatment and progression. They also will develop models to help identify, prevent, predict and treat long term physical and mental complications or disabilities due to COVID-19.
“South Carolina is hit hard by COVID-19. This pandemic adds additional complication to health problems in a largely rural state with large disparities in terms of both health care access and health outcomes among our residents,” Li says. “However, there are many unknowns with this novel virus and the biggest challenge presently with COVID-19 is the lack of large data related to this disease. Our work is significant as we will be in a unique position to answer many questions regarding the transmission dynamics, natural history, virology and clinical outcomes of COVID-19, and the answers to these questions will inform better treatment and care for COVID-19 patients over time.”
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