This exceptional reference book provides comprehensive insights into the conditions and requirements necessary to establish an optimal and supportive transfusion practice. It focuses on enhancing the procurement process and manufacturing of blood products (components) in an evidence-based and cost-effective manner, specifically targeting the vital advancements needed in low and middle-income countries (LMICs), which are home to 84% of the global population.
While this book does not delve into practical disciplinary guidelines, its emphasis lies on crucial topics. It explores the balance between restricted and liberal use of blood and blood components, the implementation and utilization of artificial intelligence (including machine learning and deep learning), and the integration of a digital footprint within clinical transfusion prescription and practice. Additionally, it addresses the significance of educating clinicians in transfusion medicine, considering the educational environment and curricular outcomes. By contributing to the development of appropriate clinical utilization of blood and blood components, the book highlights the importance of patient blood management, evidence-based decision-making, prescription practices, and bedside care delivered by well-informed professionals, including clinicians, nurses, and technologists. Furthermore, it underscores the significance of fostering a conducive climate and environment, nurturing knowledge economy, and implementing quality management practices.
In its essence, this book serves as an invaluable source of knowledge to enhance transfusion medicine practices, refine clinical indication setting, and facilitate informed decision-making. By emphasizing patient comfort, welfare, and the reduction of unnecessary harm and risks, it aims to make a significant contribution to the field. Hematologists and professionals involved in transfusion medicine will find this book to be an indispensable reference that enhances their understanding and expertise.
While this book does not delve into practical disciplinary guidelines, its emphasis lies on crucial topics. It explores the balance between restricted and liberal use of blood and blood components, the implementation and utilization of artificial intelligence (including machine learning and deep learning), and the integration of a digital footprint within clinical transfusion prescription and practice. Additionally, it addresses the significance of educating clinicians in transfusion medicine, considering the educational environment and curricular outcomes. By contributing to the development of appropriate clinical utilization of blood and blood components, the book highlights the importance of patient blood management, evidence-based decision-making, prescription practices, and bedside care delivered by well-informed professionals, including clinicians, nurses, and technologists. Furthermore, it underscores the significance of fostering a conducive climate and environment, nurturing knowledge economy, and implementing quality management practices.
In its essence, this book serves as an invaluable source of knowledge to enhance transfusion medicine practices, refine clinical indication setting, and facilitate informed decision-making. By emphasizing patient comfort, welfare, and the reduction of unnecessary harm and risks, it aims to make a significant contribution to the field. Hematologists and professionals involved in transfusion medicine will find this book to be an indispensable reference that enhances their understanding and expertise.
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