ZM is the recipient of an Australian National Health and Medical Research Council (NHMRC) Postgraduate scholarship (APP1017942). This project was partly funded by the Australian Red Cross Blood Service. The Australian government fully funds the Australian Red Cross Blood Service for the provision of blood products and services to the Australian community.
A dynamic mathematical model of red blood cell clinical demand to assess the impact of prolonged blood shortages and transfusion restriction policies
Article first published online: 3 JAN 2014
© 2014 AABB
Special Issue: The evolving paradigm of patient blood management
Volume 54, Issue 10pt2, pages 2705–2715, October 2014
How to Cite
McQuilten, Z. K., Mercer, G., Phillips, L., Luangwilai, T., Brown, R., Ozolins, I., Cheng, A. C. and Wood, E. M. (2014), A dynamic mathematical model of red blood cell clinical demand to assess the impact of prolonged blood shortages and transfusion restriction policies. Transfusion, 54: 2705–2715. doi: 10.1111/trf.12525
- Issue published online: 10 OCT 2014
- Article first published online: 3 JAN 2014
- Manuscript Accepted: 29 OCT 2013
- Manuscript Revised: 10 OCT 2013
- Manuscript Received: 5 JUL 2013
- Australian Red Cross Blood Service
Estimating change in clinical demand for red blood cells (RBCs) from a disaster, as well as triaging introduced in response, is essential to plan effectively for a major blood shortage. We aimed to develop a RBC demand model to assess the impact of restriction policies on RBC use and patient outcomes.
Study Design and Methods
A compartmental dynamic model was developed in which patients require RBCs acutely (within 1 hr), urgently (24 hr), semiurgently (1-7 days), or nonurgently; outcomes included death or remaining at or transitioning to more or less urgent categories. A mathematical model was developed with transitions governed by differential equations and calibrated to a baseline scenario of adequate blood supply (using population-based hospital data sets, registries, and RBC issues). Distribution into urgency categories was based on a prospective study of 5132 randomly selected RBC units. Scenarios when the blood supply is limited compared to baseline were investigated. Transition rates between urgency categories under these scenarios were established by clinician survey.
In the baseline 21-day scenario, patients requiring the most RBCs were other surgery (2162, 22%), medical anemia (1916, 12%), malignant hematology (1092, 16%), and gastrointestinal hemorrhage (1115, 8%). A policy of withholding RBCs for all nonurgent indications results in an estimated reduction of only 1007 (11.2%) RBC units and, if extended to semiurgent, a reduction of 2567 (28.5%) RBC units.
Based on this model, restrictions that withhold transfusion from nonurgent patients have minimal impact on RBC demand and may not be sufficient to address changed demand and/or decreased supply during a prolonged disaster.