With limited resources and rapidly growing COVID-19 patient volumes, accurate and rapid identification of individuals at the highest risk of hospitalization is a top priority. To identify and target interventions towards high-risk patients, ChristianaCare leveraged a cloud-based data platform and analytics applications, including data science tools and predictive analytics, to generate a risk score for each patient testing positive for COVID-19. Join this session to learn how up-to-date risk identification helped the organization make data-informed resource allocation decisions and enroll patients in the appropriate care management program, avoiding 61 hospital admissions and 7 intensive care unit admissions and avoiding $1.8 million in cost.
Participants will learn:
- What risk prediction tools were used.
- How up-to-date risk identification helped the organization make timely, data-informed decisions.
- What interventions were used to avoid hospital and ICU admissions.