Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.