“…One way to conceptualize the application of big data to transfusion medicine is to combine various types of health data, including electronic health records [5, 6], electronic medical records [7], personal health records [8], laboratory information systems [9], medical practice management [10] software, and hemovigilance data [11]. This combination creates a large database that healthcare professionals can use to identify patterns and trends, leading to improved practices in blood product usage, inventory management, and more, ultimately, improving patient outcomes [4, 12]. By including hemovigilance data in the discussion of big data in transfusion medicine, it highlights the importance of monitoring and ensuring the safety and quality of blood products, which is a critical aspect of transfusion medicine.…”