Panel: The Latest Predictive Tools in Sepsis Care: Insights and Learnings from Real World Case Studies
It's a common understanding that solving sepsis requires a multidisciplinary approach, and that early detection remains the most promising opportunity for improving outcomes. As health systems launch new initiatives and technologies to target the disease, it's critical to understand why sepsis is so hard to solve in the first place, and why and where current technology fails. At this panel, Dr. Suchi Saria will lead a conversation with physician, informaticist, and a patient, on why sepsis is so hard to solve, highlight progress to date including Artificial Intelligence/machine learning-based approaches to early detection, map out what an effective Artificial Intelligence/machine learning solution looks like for sepsis, and outline what steps health systems can take now to effectively impact their sepsis outcomes.
This course was originally recorded in June 2021 as part of Sepsis Tech & Innovation.
Industry leaders, Public Policy Experts, Health and hospital Leadership (C-Suite, physicians, nurses, pharmacists, CIOs), Health quality and decision support leaders, Health Investors and VCs, Health and Technology Media, Health Advocates, Health Advisors, Health Educators, Health Marketers.
Suchi Saria, PhD, MSc
Founder and CEO, John C. Malone Associate Professor, Bayesian Health and Johns Hopkins University
Suchi Saria is the Founder and CEO of Bayesian Health, the John C. Malone Associate Professor of computer science, statistics and health policy and the Director of the Machine Learning and Healthcare Lab at Johns Hopkins University. She has published over 50 peer-reviewed articles with over 3000 citations, and was recently described as “the future of 21st century medicine” by The Sloan Foundation. Her research has pioneered the development of next generation diagnostic and treatment planning tools that use statistical machine learning methods to individualize care. At Bayesian Health, Dr. Saria is leading the charge to unleash the full power of data to improve healthcare, unburdening caregivers and empowering them to save lives. Backed by 21 patents and peer reviewed publications in leading technical and clinical journals, Bayesian leverages best-in-class machine learning and behavior change management expertise to help health organizations unlock improved patient care outcomes at scale by providing real-time precise, patient-specific, and actionable insights in the EMR.
Joshua Clark, MHA, RN
Senior Vice President Quality and Safety Operations, Jefferson Health
Josh Clark is the Senior Vice President of Quality and Safety Operations for Jefferson Health, a 14-hospital system covering the greater Philadelphia region and southern New Jersey. Josh led the implementation of the OnPoint Program for advancing care excellence which included launching an industry leading serious safety event review program, enterprise escalating huddles, an organizational learning and triage platform and a state-of-the-art enterprise analytics platform. Josh obtained his RN and Master of Healthcare Administration degrees from Jefferson College of Health Sciences. After ten years of critical care nursing in Virginia and NYC, Josh transitioned his focus to the science of healthcare delivery. He helped lead a quality and safety transformation at Virginia’s second largest health system which included one of the only Applied Human Factors departments in the country. His work to integrate translational Human Factors within clinical operations was recognized by the National Quality Forum, Next Generation Innovator Award. Josh has led sepsis improvement efforts since 2008 and has served on expert panels with Dr. Emmanuel Rivers and presented to the Society of Critical Care Medicine on establishing a comprehensive sepsis program. Josh holds certifications for quality and safety from the National Association of Healthcare Quality and the Institute for Healthcare Improvement.
Roy Adams, PhD
Assistant Professor, Johns Hopkins School of Medicine
Roy Adams is an Assistant Professor of Psychiatry and Behavioral Sciences in the Johns Hopkins School of Medicine where he works on machine learning and statistical methods for understanding electronic medical data. He uses these methods to provide insight into complex medical conditions and to improve the safety, efficiency, and efficacy of patient care, with particular focus on sepsis, addiction, and Alzheimer’s disease. He received his PhD in computer science from the University of Massachusetts, Amherst in 2018 and completed a postdoctoral fellowship in computer science and biostatistics at Johns Hopkins University in 2021.
Karandeep Singh, MD, MMSc
Assistant Professor of Learning Health Sciences, Internal Medicine, Urology, and Information, University of Michigan
Dr. Singh is an Assistant Professor of Learning Health Sciences, Internal Medicine, Urology, and Information at the University of Michigan. He is a nephrologist with a background in biomedical informatics who uses machine learning methods to model electronic health record and registry data in support of a learning health system. He directs the Machine Learning for Learning Health Systems lab which focuses on using machine learning and biomedical informatics methods to understand and improve health at scale. His research spans multiple clinical domains including nephrology, urology, emergency medicine, obstetrics, and ophthalmology. He chairs the Michigan Medicine Clinical Intelligence Committee, which focuses on implementation of machine learning models across the health system. He teaches a graduate-level health data science course. He completed his internal medicine residency at UCLA Medical Center, where he served as chief resident, and a nephrology fellowship in the combined Brigham and Women’s Hospital/Massachusetts General Hospital program in Boston, MA. He completed his medical education at the University of Michigan Medical School and holds a master’s degree in medical sciences in Biomedical Informatics from Harvard Medical School. He is board certified in internal medicine, nephrology, and clinical informatics.
Head Of Corporate Communications, AKASA
Catherine Afarian spent 40 days in the hospital and an additional 3 months at home fighting a septic liver infection in 2018. Now fully recovered, Catherine serves as the Head of Corporate Communications for AKASA. Catherine is a communications and media relations executive with 20+ years of experience in Silicon Valley working for disruptive and innovative internet companies, including Netflix, eBay and 23andMe. Catherine holds a BA in journalism from California State University, Chico.
No continuing education credits are offered for this session.
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