A framework for at-home blood collection considering donor preferences

In all health care systems, Blood Donation Supply Chains (BDSCs) play a fundamental role in several sectors, including hematology, trauma management and surgery. According to recent statistics (2019), the pro- duction of blood units for transfusion still falls short of satisfying the ever-increasing demand. This is due to a combination of factors, the main one being that blood can only be produced from human donors. Meeting demand has always been the main objective of the system, and several decision tools have been developed during the years to help reach it. However, during the COVID-19 pandemic, new and unexpected issues emerged. As blood drives were cancelled because of lockdowns and donors feared going to donations centers, shortages of units have increased dra- matically. This is due to the lack of a direct channel between donors and blood banks. According to the Italian National Blood Center, in April 2020 the production of red blood cells was 36.4% less than the one of the previous year. At the same time, healthcare services are now mov- ing towards a more decentralized paradigm. Considering these factors, in this work we consider an integrated framework to collect blood directly at the donors homes. To do so, we link the Blood Donation Appoint- ment Scheduling (BDAS) and the Multi-Trip Vehicle Routing Problem with Time Windows (MTVRP-TW) problems in an organic way. Our approach consists of three planning phases: in the first one, we create possible time slots for donor appointments, with the aim of balancing the production of the different blood types, to ensure better manageable stock levels. Then, we turn these slots into real appointments, according to the received booking requests. Here, we compromise between the preferences expressed by calling donors and the requirements of the center, including scheduling and routing constraints. Lastly, a fleet of bloodmobiles is dis- patched to perform the collection. The second and third phases are linked in such a way that the outcome of the former serves the purpose of helping the computation of the latter, providing an improved starting point. The proposed integrated framework is then tested and validated against data obtained from the most prominent Italian blood provider. We also prove the cost-effectiveness of the implementation of the proposed solution.