Innovation in Action: Easing the Burden on Clinicians and Patients with Machine Learning
11AM PST / 12PM MST
The end of January saw the first U.S. case of COVID-19. A little more than a week later, the first person-to-person case appeared in the U.S. and the Trump Administration declared the coronavirus a public health emergency the next day. As the world watched the disease spread, healthcare organizations had to quickly figure out how to treat, examine, and calm anxious and possibly highly-infectious patients without overwhelming their emergency rooms and ICUs.
With a call from the leadership team at Providence St. Joseph, Maryam Gholami, head of digital products, was tasked with figuring out the problem. As she’ll explain in this special HIMSS webinar, Providence, one of the largest healthcare organizations in the northwest, recognized that a huge volume of worried people would ask for tests, and Gholami turned to Chatbots and machine learning to help triage the population.
This is a familiar story in the early stages of the pandemic. Necessity required healthcare to innovate to alleviate the burden on healthcare providers and also to better serve an anxious and reeling public.
Join HIMSS for this webinar to hear Gholami and Jawad Khan, Rush University Medical Center’s director of data sciences and knowledge management, discuss how COVID-19 put machine learning and AI projects on the fast track throughout healthcare and if this accelerated path will continue when COVID-19 is in the rearview mirror.
Key discussion points:
- Scaling technology quickly to address demand
- How machine learning can improve patient pathways to ease provider burden
- Navigating symptoms and results to steer patients
- Talking to executive leadership about critical technology
- Working under pressure with clinical and non-clinical staff
- Lessons learned, pitfalls and hurdles and their solutions