286. Simulating extended blood type matching in a hierarchical supply chain
Contributed abstract in session HB-4: Modeling and Simulation /2, stream Regular talks.
Thursday, 11:00-12:30Room: Room S3
Authors (first author is the speaker)
| 1. | Folarin Oyebolu
|
| MRC Biostatistics Unit, University of Cambridge | |
| 2. | William J. Astle
|
| MRC Biostatistics Unit, University of Cambridge |
Abstract
Blood transfusions are a life-saving treatment in people with sickle cell disorder (SCD). Currently, blood group matching for transfusion is manual and uses incomplete red cell blood type information to determine the allocation of units to patients. We have been investigating alternative approaches to blood allocation that exploit extended blood type information measured by a new genetic test shortly to be introduced by the National Health Service in England to minimise the immunological incompatibility between donors and patients.
We previously presented a blood inventory problem and formulated sequential allocation decisions as a Markov decision process. Using a simplified model of a blood supply chain which assumed a single central inventory, we studied penalty-based policies for matching which considered up to 17 blood group antigens. Our analysis demonstrated an 81% reduction in alloimmunisation risk to SCD patients compared to current guidelines.
Here, we improve this model by incorporating the hierarchical structure of the supply chain and the transportation of blood units between stock holding units (SHUs), allowing units at one SHU to be reserved and transported for future appointments at another SHU. We carried out simulation experiments in a range of scenarios with varying restrictions on the transport of blood units between SHUs. We assess the impact on patient care, in terms of alloimmunisation risk and shortages.
Keywords
- Modelling and simulation
- Healthcare policy modelling
- Healthcare management
Status: accepted
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