Sanguine: Visual analysis for patient blood management

Author:

Lin Haihan1ORCID,Metcalf Ryan A2,Wilburn Jack1,Lex Alexander1ORCID

Affiliation:

1. SCI Institute and School of Computing, University of Utah, Salt Lake City, UT, USA

2. ARUP Laboratories, University of Utah Hospital, Salt Lake City, UT, USA

Abstract

Blood transfusion is a frequently performed medical procedure in surgical and nonsurgical contexts. Although it is often necessary or even life-saving, it has been identified as one of the most overused procedures in hospitals. Unnecessary transfusions not only waste resources but can also be detrimental to patient outcomes. Patient blood management (PBM) is the clinical practice of optimizing transfusions and associated outcomes. In this paper, we introduce Sanguine, a visual analysis tool for transfusion data and related patient medical records. Sanguine was designed with two user groups in mind: PBM experts who oversee blood management practices across an institution and clinicians performing transfusions. PBM experts use Sanguine to explore and analyze transfusion practices and their associated medical outcomes. They can compare individual surgeons, or compare outcomes or time periods, such as before and after an intervention regarding transfusion practices. PBM experts then curate and annotate views for communication with clinicians, with the goal of improving their transfusion practices. We validate the utility and effectiveness of Sanguine through case studies.

Funder

National Institutes of Health

ARUP Laboratories

National Science Foundation

Publisher

SAGE Publications

Subject

Computer Vision and Pattern Recognition

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