Forecasting blood donation session capacity


30 Second Summary

Blood donation sessions face issues with cancellations, non-attendance, and medical rejections, leading to missed donations. This project aims to develop a Machine Learning tool to predict actual attendance and assess additional capacity. It will also build a web app for users to review current session capacity and manage bookings effectively.

Machine Learning
Streamlit
Blood & Transplant
Non-attendance Prediction
Author
Affiliation

Sam Plimmer

NHS Blood and Transplant

Blood donation sessions have limits of how many people will be able to attend a session. Bookings for sessions often don’t convert into actual donations due to cancellations, non-attendance and medical rejections. These missed collections represent a lost opportunity to successfully bring someone in to donate.

The aim of this project is to:

  1. Develop a Machine Learning-based predictive tool to assess, of the current bookings made for a session, what proportion of these are likely to take place, and if there is room for additional capacity
  2. Build a web based app that demonstrates the above and allows users to review current available capacity at each session