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

Transfusion. 2013 Dec;53(12):3052-9. doi: 10.1111/trf.12227. Epub 2013 Apr 29.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Transfusion
  • Bloodless Medical and Surgical Procedures / methods
  • Erythrocyte Transfusion*
  • Humans
  • Outcome Assessment, Health Care / methods*
  • Software