A novel method of data analysis for utilization of red blood cell transfusion

Authors

  • Steven M. Frank,

    Corresponding author
    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
    • Address correspondence to: Steven M. Frank, MD, Department of Anesthesiology, Zayed 6208, The Johns Hopkins Medical Institutions, 1800 Orleans Street, Baltimore, MD 21287; e-mail: sfrank3@jhmi.edu.

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  • Linda M.S. Resar,

    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
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  • James A. Rothschild,

    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
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  • Elizabeth A. Dackiw,

    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
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  • Will J. Savage,

    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
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  • Paul M. Ness

    1. Department of Anesthesiology/Critical Care Medicine, Department of Medicine (Hematology), Oncology & Pediatrics, The Johns Hopkins Medical Institutions, Baltimore, Maryland
    2. Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland
    3. Department of Pathology (Transfusion Medicine), Brigham and Women's Hospital, Boston, Massachusetts
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  • Support was provided from institutional and/or departmental sources and from The New York Community Trust (New York, NY).

Abstract

Background

A necessary component of an effective blood management program is the accurate and comprehensive collection and analysis of blood utilization data. This study describes innovative methods for analyzing and presenting data for red blood cell (RBC) utilization that compare hemoglobin (Hb) transfusion triggers and targets to those representing the restrictive transfusion strategy advocated by previous large outcome studies.

Study Design and Methods

From one institution, blood utilization data for 134,456 patients, 23,559 of whom were transfused with RBCs, were analyzed. Hb triggers and targets for transfused patients were plotted and graphically compared to the trigger and target ranges from previously published randomized clinical trials.

Results

Nine hospital services with the highest transfusion rates were selected for analysis. The service with the highest Hb trigger and target was further analyzed by comparing transfusion thresholds for individual providers. Differences among services and among individual providers for mean Hb transfusion triggers and targets were significant (up to 1.5 g/dL, p < 0.0001). The variation between the 10th and 90th percentiles for both trigger and target was also significant (up to 3 g/dL, p < 0.0001). If a restrictive transfusion strategy were implemented, the need for transfusion would be reduced or eliminated in 10% to 50% of patients, depending on the service and the individual provider.

Conclusion

By using these methods for analyzing and presenting RBC utilization data, opportunities can be identified for blood conservation, and educational efforts can be directed toward the appropriate individual hospital services and providers.

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