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Monitoring Adherence to PBM Guidelines from Clinical Data Warehouse: A Case Study

Paul-Antoine Beaudoin1, Alexandre Godon2, Sebastien Marquet2

  • 1Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, Grenoble Alpes University Hospital, TIMC, Grenoble, France.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed

Insights

Implementing Patient Blood Management (PBM) is difficult. This study details a method using a graph-based clinical data warehouse (CDW) to generate quality reports for PBM implementation at Grenoble Alpes University Hospital.

Area of Science:

  • Clinical Informatics
  • Healthcare Quality Improvement
  • Health Services Research

Background:

  • Patient Blood Management (PBM) is evidence-based but challenging to implement in clinical practice.
  • Hospitals face difficulties in integrating PBM protocols into routine care.
  • Effective data utilization is crucial for monitoring and improving PBM implementation.

Purpose of the Study:

  • To describe a novel method for generating quality reports to support Patient Blood Management (PBM).
  • To leverage a graph-based clinical data warehouse (CDW) for PBM data analysis.
  • To facilitate the routine implementation of PBM at Grenoble Alpes University Hospital.

Main Methods:

  • Utilized a graph-based clinical data warehouse (CDW) for data extraction and analysis.
  • Developed a methodology for producing quality reports specifically for PBM.
  • Applied the method at Grenoble Alpes University Hospital.

Main Results:

  • Successfully generated quality reports using data from the CDW.
  • The described method provides a framework for monitoring PBM implementation.
  • Data-driven reporting can aid in overcoming PBM implementation challenges.

Conclusions:

  • A graph-based CDW can be effectively used to produce quality reports for PBM.
  • This methodology offers a practical solution for hospitals aiming to implement PBM.
  • Quality reporting is essential for the successful integration of PBM into standard clinical practice.

Keywords:
Patient Blood Managementclinical data warehousegraph database

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