Blood product demand forecast modeling using clinical predictors

Blood transfusion is one of the most crucial and commonly-administrated therapeutics worldwide. The need for more accurate and efficient ways to manage blood demand and supply is an increasing concern in many countries. Building a technology-based robust blood demand and supply system that can achieve the goal of reducing the costs of wastage and shortage, while maintaining the safety of blood usage, is essential in modern healthcare organizations. Many countries have recognized the importance of applying technology and mathematical models into blood inventory planning and management. There are a number of studies addressing blood inventory, blood allocation policies and simulation studies for blood supply networks, but to-date few forecasting models incorporating patient clinically-related indicators have been developed. In collaboration with Canadian Blood Services (CBS) and McMaster, we will use patient clinical data and inventory data to develop a comprehensive demand forecasting model for blood products and plasma derivatives in Canada.

Faculty Supervisor:

Douglas Down

Student:

Na Li

Partner:

Canadian Blood Services

Discipline:

Computer science

Sector:

Medical devices

University:

Program: