BACKGROUND: Concerns have been raised that aging of the general population will increase the demand for blood products. Modeling can be applied to assess trends in blood demand and supply and predict how these will develop over time. STUDY DESIGN AND METHODS: We developed mathematical models to describe and predict the national demand of red blood cell (RBC) products. The first demand model assumes that the mean numbers of transfusions per inhabitant per age and sex are constant. A second demand model incorporates observed changes in clinical blood use over time. Further, a donation model is developed to predict future RBC supply. To estimate the supply of whole blood donations, we used annual donor retention rates, donor recruitment rates, and mean numbers of donations per donor year. RESULTS: The model based on demography only predicts an increase of 23% in RBC demand over 2008 to 2015. The second model, incorporating both demographic changes and trends in clinical RBC use, predicts a decrease of RBC demand by 8% over the same period. The predicted RBC supply closely follows the demand as predicted by the second model. CONCLUSIONS: Despite an aging population, RBC demand may not increase as much as predicted in other studies. This depends on the extent to which other effects, like that of optimal blood use, will neutralize the effects of aging of the transfusion recipient population. Still, the observed downward trend in donor recruitment in the Netherlands must be stopped to maintain a sufficient RBC supply.
BACKGROUND: Concerns have been raised that aging of the general population will increase the demand for blood products. Modeling can be applied to assess trends in blood demand and supply and predict how these will develop over time. STUDY DESIGN AND METHODS: We developed mathematical models to describe and predict the national demand of red blood cell (RBC) products. The first demand model assumes that the mean numbers of transfusions per inhabitant per age and sex are constant. A second demand model incorporates observed changes in clinical blood use over time. Further, a donation model is developed to predict future RBC supply. To estimate the supply of whole blood donations, we used annual donor retention rates, donor recruitment rates, and mean numbers of donations per donor year. RESULTS: The model based on demography only predicts an increase of 23% in RBC demand over 2008 to 2015. The second model, incorporating both demographic changes and trends in clinical RBC use, predicts a decrease of RBC demand by 8% over the same period. The predicted RBC supply closely follows the demand as predicted by the second model. CONCLUSIONS: Despite an aging population, RBC demand may not increase as much as predicted in other studies. This depends on the extent to which other effects, like that of optimal blood use, will neutralize the effects of aging of the transfusion recipient population. Still, the observed downward trend in donor recruitment in the Netherlands must be stopped to maintain a sufficient RBC supply.
Authors: Katherine D Ellingson; Mathew R P Sapiano; Kathryn A Haass; Alexandra A Savinkina; Misha L Baker; Koo-Whang Chung; Richard A Henry; James J Berger; Matthew J Kuehnert; Sridhar V Basavaraju Journal: Transfusion Date: 2017-06 Impact factor: 3.157
Authors: Koo-Whang Chung; Sridhar V Basavaraju; Yi Mu; Katharina L van Santen; Kathryn A Haass; Richard Henry; James Berger; Matthew J Kuehnert Journal: Transfusion Date: 2016-05-12 Impact factor: 3.157
Authors: Hermann Eichler; Anna Katharina Feyer; Kerstin Weitmann; Wolfgang Hoffmann; Olaf Henseler; Andreas Opitz; Alexander Patek; Detlef Nikolaus Hans; Linda Schönborn; Andreas Greinacher Journal: Transfus Med Hemother Date: 2020-12-23 Impact factor: 3.747