Challenge and opportunity research in blood supply chain management: a literature review

Abstract

An interconnected series of the blood management is called blood supply chain management (BSCM). The stages of BSCM consisted of blood collecting, production, inventory, and distribution. The main challenges in BSCM are related to shortage, outdate, and supply chain cost which needed to minimize. Naturally, problems in BSCM are complex, it is not an easy task to find the solution. This complexity brought by several factors as follows: its inflicted risk, the uncertainty of supply and demand, blood nature as perishable commodity, demand uniqueness, and cost occurred. This research purposes was to review of various research related to BSCM and highlight opportunities to develop further research in blood supply chain (BSC). The result of this research is a suggestion on various possible future research to be explored in BSC, for example, developing an adaptive inventory model to support blood supply chain management that could be responsive toward demand fluctuation and developing collecting strategy to minimize shortage, outdate and incurred cost in supply chain level.

From demand forecasting to inventory ordering decisions for red blood cells through integrating machine learning, statistical modeling, and inventory optimization

“…The study identified 227,944 RBC transfusions for 40 At the participating hospital blood banks, the mean (SD) of daily RBC demand was 92.43 (28.27) units. The mean (SD) of the daily ordering quantity was 103.71 (69.49) units, which was significantly higher than the actual daily demand (difference in means: 11.27; 95% CI: 9.09, 13.46; p-value <0.001).…”

“…A significant cost saving was achieved, mainly through leaner inventory, contrasting with actual hospital blood bank inventory levels that are excessive, highly variable, and associated with an increasing trend over time. 26 Although there have been many studies in the field of blood demand and supply management, [40][41][42][43][44] these typically assume independent and identically distributed demands, which is rarely the case, as the demand of blood has temporal dependence and is affected by clinical indicators. To our knowledge, our study team was the first to consider integrating demand forecasting models into blood inventory management strategies using electronic medical records.…”

Optimisation and control of the supply of blood bags in hemotherapic centres via Markov decision process with discounted arrival rate

“…Recent literature reviews on blood supply chains can be found in (Pirabán et al, 2019), (Mansur et al, 2018), (Osorio et al, 2015) and (Beliën and Forcé, 2012). And a substantial number of articles study inventory management of blood components and perishable commodities.…”

A structured approach to analyse logistics risks in the blood transfusion process

“…Blood transfusion is an excellent example of complex health care process 2,3 being constituted by a set of interdependent sub‐processes involving different professionals where any error happening at any stage may cause serious consequences on the downstream phases and ultimately on patients 4,5 . The most common errors encompass patient misidentification, incorrect sample collection and labelling, incomplete or incorrect data entry, prescription and transcription errors, laboratory errors, inappropriate management of storage devices, inappropriate order of blood products, inaccurate handling, delivery and administration 6,7 .…”