Monitoring and feedback using data in transfusion medicine: A study of practices from the
BEST
Collaborative
Ryan A. Metcalf, Allison Mo, Sandra K. White, Gustavo C. Duarte, Nancy M. Dunbar, Katie Hands, Anil K. Panigrahi, Jessica L. Poisson, Nabiha H. Saifee, Hua Shan, Erica M. Wood, Michael F. Murphy, Simon J. Stanworth Abstract
Background
It is imperative that health systems monitor transfusion practice quality and implement improvements when evidence‐based practice gaps are identified. Despite the importance of data‐driven quality activities, little is known about approaches employed by hospitals. This study aimed to describe strategies used by hospitals to acquire, analyze, and apply transfusion‐related quality data.
Study Design and Methods
A pre‐piloted survey was developed by the core team, and Biomedical Excellence for Safer Transfusion (BEST) Collaborative attendees of meetings were invited to participate. Topics spanned five domains: hospital characteristics, data acquisition, quality metric prioritization, data analysis/visualization, and feedback processes. Responses were summarized to identify patterns and variation across institutions.
Results
Nine hospitals of varying size, specialty mix, and transfusion volumes from three continents participated. Most transfusion services acquired transfusion data from both the electronic health record and the laboratory information system (6/9, 67%). Although all sites tracked the number of transfusions, there was wide variation in other metrics prioritized. Transfusion appropriateness was prioritized by 7 of 9 centers, but few reported monitoring antifibrinolytic agent use (2/9, 22%), anemia management (4/9, 44%), and consent (2/9, 22%). All hospitals performed some form of data analysis, but chart/table types and functionalities differed. Feedback was typically provided by transfusion medicine specialists or hematology, but frequency and means differed between sites.
Discussion
This descriptive study highlights significant variation in how selected hospitals use data to monitor transfusion practices and provide feedback. There are many opportunities to enhance optimal uses of data to deliver effective quality improvement.