Common Data Model-based Analysis of Selective Leukoreduction Protocol Compliance at Three Hospitals

Area of Science:

• Hematology
• Transfusion Medicine
• Health Services Research

Background:

• Selective leukoreduction protocol (SLP) is critical for specific patient populations but can be challenging to implement consistently.
• Patient oversight can be a limitation in identifying individuals who require SLP.
• Utilizing the Observational Medical Outcomes Partnership common data model (CDM) allows for estimation of SLP compliance (SLPC).

Purpose of the Study:

• To estimate selective leukoreduction protocol compliance (SLPC) across diverse patient groups.
• To analyze trends in SLPC over time using a large-scale dataset.
• To identify patient cohorts with suboptimal SLPC requiring targeted interventions.

Main Methods:

• A retrospective analysis of red blood cell (RBC) transfusion history was conducted using three hospital datasets.
• Data from approximately three million patients over 20 years were analyzed using the CDM.
• SLPC was calculated as the proportion of patients receiving only leukoreduced RBCs among all patients transfused with RBCs.

Main Results:

• A total of 166,641 patients were included in the study from 2001 to 2021.
• SLPC generally increased across most patient groups, with variations observed between hospitals.
• High SLPC (≥75%) was sustained for extended periods in hematology disease and solid organ transplantation groups, while cancer, immunodeficiency, and cardiovascular surgery groups showed <50% SLPC shortly after diagnosis/treatment.

Conclusions:

• CDM-based analysis is effective for evaluating large-scale SLPC.
• While overall SLPC shows improvement, specific patient groups demonstrate persistent low compliance.
• Targeted educational initiatives and enhanced monitoring are recommended for patient groups with low SLPC to improve transfusion safety.