Data-Driven Transfusion Medicine: Looking to the Future



 

Blood transfusion is cited as one of the most overused healthcare interventions, making patient blood management (PBM) a prime target for informatics-based approaches and artificial intelligence (AI) solutions. During this presentation, we’ll probe PBM strategies, AI use cases, and the current state of the field of transfusion medicine, including AI limitations. An analysis of a novel data visualization tool that can provide unique insights into PBM practice performance will be presented.

Originally presented on December 18, 2023, in Salt Lake City, Utah.


Lecture Presenter

Ryan A. Metcalf, MD, CQA(ASQ)

Ryan A. Metcalf, MD, CQA(ASQ)

Associate Professor (Clinical)
University of Utah School of Medicine
Section Chief
Transfusion Medicine
Chief Value Officer
Utah Health and ARUP Laboratories
Medical Director, Transfusion Service/Blood Bank
ARUP Laboratories

Dr. Metcalf is section chief of Transfusion Medicine, medical director of the Transfusion Service, associate professor of Pathology, and inpatient chief value officer for the Department of Pathology at the University of Utah Health and ARUP Laboratories. He completed a residency in anatomic and clinical pathology and a fellowship in transfusion medicine at Stanford University and is board certified in these disciplines. He also has expertise in quality management and is a certified quality auditor.

Dr. Metcalf practices transfusion medicine and his specific interests include data-driven/informatics approaches to patient blood management, quality management, and innovation. His research interests include the use of machine learning to predict patient blood management (PBM) outcomes, advanced data visualization to improve understanding of clinical practice quality, and data-driven approaches to improve our understanding of risks associated with blood transfusion. He is coinventor of a novel advanced data visualization tool that evaluates PBM practice.

Dr. Metcalf is chair of the Association for the Advancement of Blood and Biotherapies (AABB) Clinical Transfusion Medicine Committee, a member of the AABB Patient Blood Management Standards Committee, and a member of the College of American Pathologists (CAP) Transfusion, Apheresis, and Cellular Therapy Committee. He is also active in transfusion medicine education and received the department's Outstanding Teaching Award for Clinical Pathology faculty in 2020.


Objectives

After this presentation, participants will be able to:

  • Describe common informatics-based patient blood management interventions you can implement at your hospital
  • Appraise the current state of artificial intelligence and machine learning in transfusion medicine
  • Analyze how a novel data visualization tool can provide unique insights into PBM practice performance

Sponsored by:

University of Utah School of Medicine, Department of Pathology, and ARUP Laboratories