Supply chain management of blood products: a literature review.

This paper presents a review of the literature on inventory and supply chain management of blood products. First, we identify different perspectives on approaches to classifying the existing material. Each perspective is presented as a table in which the classification is displayed. The classification choices are exemplified through the citation of key references or by expounding the features of the perspective. The main contribution of this review is to facilitate the tracing of published work in relevant fields of interest, as well as identifying trends and indicating which areas should be subject to future research.OR in health services; Supply chain management; Inventory; Blood products; Literature review;

Optimal allocation of blood products

The high cost of collection and the short shelf life of apheresis platelets demand efficient inventory management to reduce outdates and shortages. Apheresis platelets are licensed for seven days, and blood centers are keen on knowing the consequences of various product collection and distribution strategies. To reduce outdates, inventory managers typically distribute the older units first, thereby following first-in first-out (FIFO) policy; however, hospital blood banks would prefer that the blood center issues out the freshest units first, equivalent to a last-in first-out (LIFO) policy. This study addresses the optimal distribution policy to achieve a desired outdate, shortage and average age of apheresis platelets. A comprehensive literature review was conducted on previous models studied to efficiently distribute blood products. However, most of the research on blood inventory management has been restricted to the hospital blood bank level in terms of ordering policies and inventory levels. This study takes the approach from the perspective of the inventory manager at the regional blood center. The inventory manager needs a reliable forecast of the quantity and timing of future blood supply (collection from donors) and blood demand from hospital blood banks to make an effective decision on blood inventory control. A forecasting method is used in this study to predict collection and demand for Single Donor Platelets (SDPs), and solves the blood inventory problem using a heuristic method and a Linear Programming (LP) with a rolling horizon method to find the near optimal issuing policy, the expected average age, outdate rate, and shortage rate of a blood product from the perspective of the blood center. It is concluded that regional blood centers can distribute with a ‘mixed’ FIFO/LIFO strategy and not significantly affect outdates or ability to cover shortages. For the LP model with a rolling horizon schedule, the inventory manager at the blood center would have to use forecast windows of five to achieve good issuing policies. A simulation study comparing the heuristic method and an LP-based with a rolling horizon method indicated that LP models with forecast windows of five and heuristics methods with a ‘mixed’ FIFO/LIFO strategy can be used to optimize this inventory problem

A Metaheuristic-Based Simulation Optimization Framework For Supply Chain Inventory Management Under Uncertainty

The need for inventory control models for practical real-world applications is growing with the global expansion of supply chains. The widely used traditional optimization procedures usually require an explicit mathematical model formulated based on some assumptions. The validity of such models and approaches for real world applications depend greatly upon whether the assumptions made match closely with the reality. The use of meta-heuristics, as opposed to a traditional method, does not require such assumptions and has allowed more realistic modeling of the inventory control system and its solution. In this dissertation, a metaheuristic-based simulation optimization framework is developed for supply chain inventory management under uncertainty. In the proposed framework, any effective metaheuristic can be employed to serve as the optimizer to intelligently search the solution space, using an appropriate simulation inventory model as the evaluation module. To be realistic and practical, the proposed framework supports inventory decision-making under supply-side and demand-side uncertainty in a supply chain. The supply-side uncertainty specifically considered includes quality imperfection. As far as demand-side uncertainty is concerned, the new framework does not make any assumption on demand distribution and can process any demand time series. This salient feature enables users to have the flexibility to evaluate data of practical relevance. In addition, other realistic factors, such as capacity constraints, limited shelf life of products and type-compatible substitutions are also considered and studied by the new framework. The proposed framework has been applied to single-vendor multi-buyer supply chains with the single vendor facing the direct impact of quality deviation and capacity constraint from its supplier and the buyers facing demand uncertainty. In addition, it has been extended to the supply chain inventory management of highly perishable products. Blood products with limited shelf life and ABO compatibility have been examined in detail. It is expected that the proposed framework can be easily adapted to different supply chain systems, including healthcare organizations. Computational results have shown that the proposed framework can effectively assess the impacts of different realistic factors on the performance of a supply chain from different angles, and to determine the optimal inventory policies accordingly

Platelet inventory management in blood supply chain under demand and supply uncertainty

Supply chain management of blood and its products are of paramount importance in medical treatment due to its perishable nature, uncertain demand, and lack of auxiliary substitutes. For example, the Red Blood Cells (RBC's) have a life span of approximately 40 days, whereas platelets have a shelf life of up to five days after extraction from the human body. According to the World Health Organization, approximately 112 million blood units are collected worldwide annually. However, nearly 20 percent of units are discarded in developed nations due to being expired before the final use. A similar trend is noticed in developing countries as well. On the other hand, blood shortage could lead to elective surgeries cancellations. Therefore, managing blood distribution and developing an efficient blood inventory management is considered a critical issue in the supply chain domain. A standard blood supply chain (BSC) achieves the movement of blood products (red blood cells, white blood cells, and platelets) from initial collection to final patients in several echelons. The first step comprises of donation of blood by donors at the donation or mobile centers. The donation sites transport the blood units to blood centers where several tests for infections are carried out. The blood centers then store either the whole blood units or segregate them into their individual products. Finally, they are distributed to the healthcare facilities when required. In this dissertation, an efficient forecasting model is developed to forecast the supply of blood. We leverage five years' worth of historical blood supply data from the Taiwan Blood Services Foundation (TBSF) to conduct our forecasting study. With the generated supply and demand distributioins from historial supply and demand data as inputs, a single objective stochastic model is developed to determine the number of platelet units to order and the time between orders at the hospitals. To reduce platelet shortage and outdating, a collaborative network between the blood centers and hospitals is proposed; the model is extended to determine the optimal ordering policy for a divergent network consisting of multiple blood centers and hospitals. It has been shown that a collaborative system of blood centers and hospitals is better than a decentralized system in which each hospital is supplied with blood only by its corresponding blood center. Furthermore, a mathematical model is proposed based on multi-criteria decision-making (MCDM) techniques, in which different conflicting objective functions are satisfied to generate an efficient and satisfactory solution for a blood supply chain comprising of two hospitals and one blood center. This study also conducted a sensitivity analysis to examine the impacts of the coefficient of demand and supply variation and the settings of cost parameters on the average total cost and the performance measures (units of shortage, outdated units, inventory holding units, and purchased units) for both the blood center and hospitals. The proposed models can also be applied to determine ordering policies for other supply chain of perishable products, such as perishable food or drug supply chains.Includes bibliographical references

A game-based approach towards facilitating decision making for perishable products: an example of blood supply chain

NOTICE: this is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, Volume 41, Issue 9, July 2014, Pages 4043–4059 doi:10.1016/j.eswa.2013.12.038Supply chains for perishable items consist of products with a fixed shelf life and limited production/collection; managing them requires competent decision-making. With the objective of placing the learners in the position of decision-makers, we propose the Blood Supply Chain Game which simulates the supply chain of blood units from donors to patients based on a real case study modeling the UK blood supply chain. The Excel-based game is an abstraction of the technical complex simulation model providing a more appropriate learning environment. This paper presents the game’s background, its mathematical formulations, example teaching scenarios and the learners’ evaluation. The game aims to translate qualitative aspects of a sensitive supply chain into quantitative economic consequences by presenting a process analysis and suggesting solutions for the patient’s benefit in a cost effective manner, trying to synchronize blood demand and supply and maximize the value of the whole supply chain. This innovative approach will be instructive for students and healthcare service professionals

Optimising Blood Donation Session Scheduling in South East England

It is essential that all countries operate a form of blood banking service, where blood is collected at donation sessions, stored and then distributed to local healthcare providers. It is imperative that these services are efficiently managed to ensure a safe supply of blood and that costs and wastages are kept minimal. Previous works in the area of blood management have focussed primarily on the perishable inventory problem and on routing blood deliveries to hospitals; there has been relatively little work focusing on scheduling blood donation sessions. The primary aim of this research is to provide a tool that allows the National Blood Service (the English and Welsh blood service) to schedule donation sessions so that collection targets are met in such a way that costs are minimised (the Blood Scheduling Problem). As secondary aims, the research identifies the key types of data that blood services should be collecting for this type of problem. Finally, various what-if scenarios are considered, specifically improv- ing donor attendance through paying donors and the proposed changes to the inter-donation times for male and female donors. The Blood Scheduling Problem is formulated as a Mixed Integer Linear Programming (MILP) problem and solved using a variable bound heuristic. Data from the South East of England is used to create a collection schedule, with all further analysis also being carried out on this data set. It was possible to make improvements to the number of units under collected in the current schedule, moreover the number of venues and panels operated could be reduced. Further- more, it was found that paying donors to donate was uneconomical. Finally, changing the inter-donation times could lead to a reduction in the number of shortfalls, even when demand was increased by as much as 20%. Though the model is specific to England and Wales, it can easily be adapted to other countries’ blood services. It is hoped that this model will provide blood services with a model to help them better schedule donation sessions and allow them to identify the data necessary to better understand their performance

An Inventory and Safety Stock Analysis of Air Force Medical Service Pharmaceuticals

A significant challenge facing the Air Force Medical Service (AFMS) Military Treatment Facilities (MTFs) is the perishability costs associated with its pharmaceutical stock. During a two year time period, the AFMS returned expired or nearly expired pharmaceuticals valued at over $23,000,000. In response to the waste represented by pharmaceutical perishability cost, this thesis analyzes the historical inventory management decisions of 173 MTF/pharmaceutical combinations and proposes an alternative inventory control policy to reduce perishability costs. Based on the critical nature of pharmaceuticals and importance of generating high patient satisfaction, the proposed alternative inventory control system was required to be cognizant of the cost savings/service level trade-off. After applying a fundamental inventory management equation to historical patient demands, the calculated inventory control policy is evaluated against a recent nine month time period of patient demand in terms of potential cost savings and fill rates. At the conclusion of the study, it is determined that the use of the proposed inventory control policy would generate an effective perishability cost savings of approximately$250,000 annually, as well as a one-time inventory reduction cost savings that exceeds $1,700,000. In spite of this stock reduction, the studied MTF/pharmaceutical combinations would maintain a strong fill rate that exceeds 99.82%

Performance measures of nonstationary inventory models for perishable products under the EWA policy

Accurately estimating key performance indicators in inventory models for perishable items is essential in order to assess and improve the management strategy of these systems. We analyse the production of platelet concentrates at blood banks under the EWA replenishment policy. We give analytical approximations of the most important performance measures, such as the size of orders, the size of stocks, the percentage of outdating, the age distribution of stocks and the freshness of units issued, among others. The production of platelet concentrates is a prototypical example of inventory models for short life items with random demand and a weekly pattern, where a high service level is required. The methodology and the approximations presented here can be easily adapted to other inventory systems with similar characteristics. Most of the formulae in this article are new for nonstationary models under the EWA policy; indeed, formulae for the age distribution of units in stock and of units issued have not appeared in the literature even for the simpler base-stock replenishment policy. We apply our results to a real blood bank and find very close agreement between the formulae and the results of Monte Carlo simulations. The accuracy of our approximations is also tested in several scenarios, depending on the lifetime of units, safety stock levels and the probabilistic distribution of demand.Carlos Gorria and Mikel Lezaun have received funding from the Department of Education of the Basque Government through the Consolidated Research Group MATHMODE (IT1294-19) and the Spanish Ministry of Science and Inovation Ref. PID2019-108111RB-I00 (FEDER/AEI). F. Javier López has received funding from Grant PID2020-116873GB-I00 funded by MCIN/AEI/ 10.13039/501100011033. He is a member of the research group Modelos Estocásticos (DGA). The authors thank CVTTH for providing the data on platelet demand in 2012