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Simulating the blood transfusion system in Kenya: Modelling methods and exploratory analyses.

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This study uses discrete event simulation to model Kenya's blood system, identifying bottlenecks from donation to transfusion. The findings help improve blood supply and meet patient demand effectively.

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Area of Science:

  • Health Systems Research
  • Operations Research
  • Public Health

Background:

  • Ensuring adequate and safe blood for transfusion is a critical challenge in low- and middle-income countries.
  • Existing approaches rarely address the blood supply chain from a holistic system perspective.

Purpose of the Study:

  • To present the first discrete event simulation model of the Kenyan blood system.
  • To explore the impact of system variations on meeting patient-level blood demand.

Main Methods:

  • Developed a process map of the Kenyan blood system through interviews with healthcare personnel.
  • Simulated the blood system from collection to transfusion, incorporating supply and demand parameters.
  • Utilized expert opinion for supply-side data and hospital records for demand-side data.

Main Results:

  • The model demonstrates how changes in blood collection, demand, and distribution affect patient blood availability.
  • Identified potential process impediments within the blood supply chain.
  • Provided a tool to evaluate alternative strategies for improving blood collection, testing, distribution, and use.

Conclusions:

  • A systems approach is crucial for understanding and optimizing the blood supply chain.
  • Discrete event simulation can effectively identify interventions to enhance blood availability and meet patient needs.
  • This model aids in policy decisions for a more robust national blood system.