Big Data Donor Health (BDDH)

Big Data Donor Health (BDDH) aims to create a decision model to personalize iron monitoring and management strategies for blood donors. This project seeks to ensure donors' health and safety by tailoring donation frequencies and iron checks to individual needs.

Project Goals:

1.  Investigating Donor Health Dynamics:
   a.    Explore how iron levels and red blood cell (RBC) parameters change over repeated donations.
   b.    Study the impact of donor characteristics like age, sex, iron and vitamin status, and lifestyle on these changes.
2. Optimizing Donation Practices:
   a.    Determine the best donation frequencies and iron monitoring methods for different donor groups using diverse data sources.
   b.    Employ computational modeling and machine learning to enhance prediction accuracy.

In the project, we use data from the donor database which contains a large number of donations from the past decade. However, in the project we also seek to improve data collection methods at the blood bank for better research and operational efficiency. 

By Partnering with international blood establishments inside and outside the EU, we can validate approaches and improve policy outcomes. Moreover, these collaborations allow us to examine the effects of different policies (e.g., iron supplementation and deferral strategies) on donor health and prediction model performance.

Publications:
https://doi.org/10.1111/vox.13643
https://doi.org/10.1016/S0140-6736(24)01085-7