Ryan A. Metcalf1,2, Jin Ye Yeo3
1Department of Pathology, University of Utah, Salt Lake City, Utah, USA; 2ARUP Laboratories, Salt Lake City, Utah, USA; 3AOB Editorial Office, AME Publishing Company
Correspondence to: Jin Ye Yeo. AOB Editorial Office, AME Publishing Company. Email: aob@amegroups.com
This interview can be cited as: Metcalf RA, Yeo JY. Meeting the Editorial Board Member of AOB: Dr. Ryan A. Metcalf. Ann Blood. 2024. Available from: https://aob.amegroups.org/post/view/meeting-the-editorial-board-member-of-aob-dr-ryan-a-metcalf.
Expert introduction
Dr. Ryan A. Metcalf (Figure 1) 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 clinical transfusion medicine, decision support interventions, the use of machine learning to predict patient blood management outcomes, data visualization to identify root causes from complex clinical data, and data-driven approaches to improve our understanding of risks associated with blood transfusion.
Dr. Metcalf is Chair of the 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 received the Department's Outstanding Teaching Award for Clinical Pathology faculty in 2020 and the William Roberts Award for Excellence in Laboratory Medicine in 2023.
Figure 1 Dr. Ryan A. Metcalf
Interview
AOB: What inspired you to pursue transfusion medicine?
Dr. Metcalf: I have been driven by a desire for a deeper understanding of medical science to try to help as many patients as best I can. My favorite subject during my undergraduate education was organic chemistry, because it was very mechanistic, and I felt a connection to the underpinnings of how biology works at a molecular level. I chose to pursue a pathology residency because it seemed like it lent itself to a mechanistic understanding of disease. As I gained more exposure to transfusion medicine during my residency training, I realized it was a field that combined many of the things I enjoyed about different specialties: biology, medicine, epidemiology, administration, and both testing and treatment.
AOB: Could you provide a brief overview of the new and important advances in data-driven transfusion practice?
Dr. Metcalf: There are many exciting developments in the field related to data. Certainly, there has been a great deal of attention on artificial intelligence (AI) and machine learning (ML), whether for clinical prediction, knowledge-based use cases, and much more. Advances in data visualization have paved the way for effective audit and feedback to improve clinical transfusion practices. Other exciting use cases are in silico clinical trials, blood inventory forecasting, immunohematology database curation, donor identification and engagement, and more.
AOB: How have informatics-based approaches and AI solutions for patient blood management (PBM) evolved over the years? Are there any examples that hold significant promise or have impacted your practice?
Dr. Metcalf: I view these as a spectrum ranging from simpler to more complex methods. Electronic clinical decision support to improve transfusion guideline adherence has been implemented at many institutions and can be quite effective at reducing some unnecessary transfusions. We have implemented such alerts with success and have turned our attention toward advanced data visualization to more comprehensively evaluate PBM practice. AI solutions, such as those for clinical prediction, are very much of interest, but the field (and medicine as a whole) has much work to do in order to realize potential, and to do so safely. Developing an AI model with good performance characteristics is much easier than implementing the model and demonstrating effectiveness in the real world.
AOB: You highlighted some gaps and challenges of using AI and ML in transfusion medicine in your presentation on “Data-Driven Transfusion Medicine: Looking to the Future”. In your opinion, what should be the next steps in research to overcome these gaps and challenges?
Dr. Metcalf: I think we need to take a quality management approach to developing and implementing AI responsibly in medicine in general. We are well suited to take such an approach in our field because quality management is something we understand and practice every day.
AOB: As a proponent of data-driven and evidence-based practice, as well as a co-inventor of the Sanguine, a sophisticated data visualization tool for patient blood management, what hopes do you have for the future of using data to power personalized medicine?
Dr.Metcalf: I think health systems have a lot of clinical data available that are underutilized. Because medicine is complex, it made sense to develop a data visualization tool that allows us to better understand practice performance at a deeper level. Data visualization helps with understanding and insights from available data. The first step to improvement is truly understanding the current state. We can do this by evaluating numerous patient blood management modalities, in clinical context, all tied to patient outcomes. For example, we can evaluate preoperative anemia, transfusion appropriateness, use of antifibrinolytic agents, use of cell salvage, costs, and more. These can be evaluated by department/surgeon, by procedure, adjusted for risk/complexity or clinical context, connected to key patient outcomes – and this can all be done at once with custom charts that are visually appealing. This can be used for audit and feedback to optimize practice and for easy follow up of the outcomes of interventions.
AOB: As the award recipient of the William Roberts Award for Excellence in Laboratory Medicine in 2023, what tips do you have for aspiring researchers who wish to pursue laboratory medicine?
Dr. Metcalf: From a research standpoint, my suggestion would be to lean into thinking creatively and take time to critically think about your vision if all barriers were removed. This can help with finding a passion and the next challenge is figuring out how to effectively pursue the passion. Of course, be open to learning always and seek out collaboration with others. It can take time to build momentum, so do not give up!
AOB: How has your experience been as an Editorial Board Member of AOB?
Dr. Metcalf: AOB has been a great source of meaningful publications from my perspective. I have enjoyed reviewing well-written manuscripts on a broad array of topics relevant to transfusion medicine.
AOB: As an Editorial Board Member, what are your expectations for AOB?
Dr. Metcalf: I can see AOB continuing to publish articles that are useful for readers in our community. I would expect AOB to continue to receive manuscripts from a variety of countries internationally and continue to increase its readership to educate and advance practice in transfusion medicine.