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A real-time dashboard for optimizing blood product utilization through a FHIR-based data integration pipeline
Cynthia Sabrina Schmidt1, Johannes Wutzkowsky2, Henning Schäfer3
1Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany; Institute for Transfusion Medicine, University Hospital Essen, Essen, Germany.
Background:
Efficient blood product utilization remains a critical operational challenge in transfusion medicine. One key aspect is the timely identification of products eligible for release and the monitoring of discharged patients with reserved blood products that may no longer be needed, as manual review processes for unused or misallocated units often delay their reintroduction into circulation.
Objective:
To develop a real-time dashboard that integrates heterogeneous hospital data to identify blood products allocated to patients after discharge, transfer, or death.
Methods:
Clinical and laboratory data from the Hospital Information System (HIS) and Laboratory Information System (LIS) were harmonized via an Extract-Transform-Load (ETL) pipeline into Fast Healthcare Interoperability Resources (FHIR) and stored in a structured database using a relational FHIR engine. A Grafana dashboard visualizes the information retrieved through SQL queries, consolidating patient data, blood product information and crossmatch status into a unified interface.
Results:
The dashboard provides an overview of all blood products that could potentially be released back into stock and lists associated patients and departments. It is reviewed daily by blood depot staff as part of the clinical workflow, enabling faster verification and release of unused units. The integration of FHIR-based analytics ensures interoperability and real-time updates.
Conclusion:
The dashboard demonstrates that structured FHIR data can be leveraged for operational decision support in transfusion medicine, enabling proactive stock management and improved resource utilization through seamless integration with existing clinical systems.
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