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AI Supply Chain Optimisation for Platelets to Reduce Costs

  • Improve productivity and performance
  • Cutting-edge AI solution to optimise a complex, short-life blood product supply chain.
  • 54% reduction in expired platelets.
  • 100% elimination of costly ad hoc transport.
  • Significant reduction in expiries while maintaining a high “In Full” delivery rate.

Background

Platelets are critical blood products with a shelf life of only 7 days. Hospitals must manage diverse blood types and antigens to meet patient needs while minimizing overstocking and wastage. This involves complex coordination of supply, manufacturing, distribution, stock holding, and logistics.

Objectives

  • Cut ad hoc transport costs by 50%.
  • Reduce expiries by 50%.

Approach

  • Data Management:   Ensured accuracy from three Wellness Network trusts.
  • Forecasting:   Predicted demand for 40 blood products across 15 hubs.
  • Advanced Modelling:   Built a model with 700,000 variables to cut costs; validated with a simulator.
  • Data Science Methodology:   Used time series analysis and Kortical's AutoML to identify XGBoost.
  • Deployment:     Streamlined with Kortical Cloud API; created a team dashboard.

Results

  • 54% reduction in expired platelets.
  • 100% reduction in costly ad hoc transport.
  • Maintained high “In Full” delivery rates while reducing expiries.
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