CAN DO IT (COVID-19 in Ambulatory Settings: Using NLP to Drive Outcomes and Improve Treatment)

Abstract: Primary, acute, and emergency department care settings fill essential assessment and treatment roles in the COVID-19 pandemic, yet providers in these settings lack guidance based on emerging data trends to inform care management needs for patients presenting with suspected COVID-19 illness and patients with chronic conditions or other vulnerable risk factors. We will use electronic health record data to help providers improve testing, treatment, and patient outcomes related to COVID-19, as well as management of critical patient care disrupted by the pandemic. This research will help healthcare systems administer equitable patient care by creating rapid discovery from data entered into structured fields and clinical notes, using data science methods to create actionable data driven dashboards for ambulatory care settings, that address the direct and indirect health effects of COVID-19.

Status: in progress

Led by: Drs. Kari Stephens and Matthew Thompson