Quality and Patient Safety
William Miles, MD, FCCM (he/him/his)
Carolinas Medical Center
Despite improvement in the care of critically ill patients, limitations remain in the areas of patient health complexities, predicting deterioration, and providing timely treatment. Advanced monitoring systems and treatments have improved care, but it has yet to be determined whether these advances are the next step in critical care. AI and machine learning algorithms aim to identify patterns in complex data. The recent growth in computing power means that AI can now be applied to complex critical care medicine data. Many clinicians lack understanding of AI and are unaware of how it can help in ICU management as long as we are aware of its limitations. This session will focus on AI basics, how it can help improve clinician efficiencies, patients' ICU experiences, and predictive modeling. AI improvements in medication reconciliation and drug interactions will also be addressed. Speakers will highlight problems with AI in critical care and how AI can adapt to prevent biases and inaccuracies that develop in machine learning.
Teresa Rincon, BSN, PhD, FCCM (N/A)
Carrie Griffiths, PharmD, BCCCP (she/her/hers) – W. G. (Bill) Hefner Salisbury Department of Veterans Affairs Medical Center
Leo Anthony Celi, MD, MPH, MS (he/him/his) – Beth Israel Deaconess Medical Center BIDMC