Simulation-optimization model for production planning in the blood supply chain

Impact of Implementing a Standard Operating Procedure to Reduce Blood Wastage in Blood Centers of Iran

BACKGROUND

Blood wastage leads to additional costs and reduced blood availability to patients. Above all is the moral issue of wasting donor gifts. This study aimed to determine the rate of blood wastage before and after implementing a new standard operating procedure (SOP) in Iran.

METHODS

In this interventional study, a SOP for wastage management was prepared and implemented in all blood centers throughout the country. Data were extracted from the integrated software of the Iranian Blood Transfusion Organization (IBTO). The wastage rate of blood components in the post-intervention years (2016-2017) was then compared with that in the pre-intervention years (2013-2015) using the Z test.

RESULTS

The overall wastage rate decreased by 36.86% (P<0.001, 95% CI [36.84-36.88]) after the intervention. Red blood cell (RBC) wastage decreased from 2.6% to 2.5%, platelet wastage from 19.5% to 10.6% and plasma wastage from 15.5% to 7.3% (P<0.001). The highest percentage of waste reduction pertained to plasma components, which decreased by 52.90% (P<0.001, 95% CI [52.86-52.94]). Expiration was the most common cause of RBC and platelet wastage. The most common causes of plasma wastage were RBC contamination and rupture or leakage of the bags. The intervention resulted in a drop of over 250000 discarded components each year, equal to approximately thirty-six million dollars in savings.

CONCLUSION

This intervention effectively reduced waste and increased efficiency. Ongoing blood wastage reviews, auditing, and receiving feedback from the central headquarters were powerful tools in following the compliance of blood centers. Further studies are recommended, especially concerning blood wastage in hospital blood banks and various wards.

Blood supply chain network design: a systematic review of literature and implications for future research

Purpose

The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.

Design/methodology/approach

The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.

Findings

The results of the study present the researchers’ tendencies and preferences when designing their BSC network models.

Research limitations/implications

The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.

Originality/value

The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.

A multi-product multi-period stochastic model for a blood supply chain considering blood substitution and demand uncertainty

This paper presents a multi-product multi-period stochastic program for an integrated blood supply chain that considers red blood cells and platelets while accounting for multi-product interactions, demand uncertainty, blood age information, blood type substitution, and three types of patients. The aim is to minimize the total cost incurred during the collection, production, inventory, and distribution echelons under centralized control. The supply chains for red blood cells and platelets intertwine at the collection and production echelons as collected whole blood can be separated into red blood cells and platelets at the same time. By adapting to a real-world blood supply chain with one blood center, three collection facilities, and five hospitals, we found a cost advantage of the multi-product model over an uncoordinated model where the red blood cell and platelet supply chains are considered separately. Further sensitivity analyses indicated that the cost savings of the multi-product model mainly come from variations in the number of whole blood donors. These findings suggest that healthcare managers are able to see tremendous improvement in cost efficiency by considering red blood cell and platelet supply chains as a whole, especially with more whole blood donations and a higher percentage of whole blood derived platelets pooled for transfusion.

A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model

In this paper, we develop a multiclass, multiproduct equilibrium model for convalescent plasma donations in the Covid-19 pandemic. The potential donors are situated at different locations and the donor population at each location can be separated into different classes based on their motivation and the product for which they provide donations at a collection site. The model captures the competition between nonprofit and for-profit organizations seeking convalescent plasma donations, which is a characteristic of this new market. A variational inequality formulation of the equilibrium conditions and qualitative properties of the model are provided. We also present a capacitated version of the model. Numerical examples of increasing complexity are presented and solved using the modified projection method. The results reveal multiclass, multiproduct donor behavior under different scenarios which can inform policy makers during this pandemic and beyond.

A novel capacity sharing mechanism to collaborative activities in the blood collection process during the COVID-19 outbreak

Because of government intervention, such as quarantine and cancellation of public events at the peak of the COVID-19 outbreak and donors’ health scare of exposure to the virus in medical centers, the number of blood donors has considerably decreased. In some countries, the rate of blood donation has reached lower than 30%. Accordingly, in this study, to fill the lack of blood product during COVID-19, especially at the outbreak’s peak, we propose a novel mechanism by providing a two-stage optimization tool for coordinating activities to mitigate the shortage in this urgent situation. In the first stage, a blood collection plan considering disruption risk in supply to minimize the unmet demand will be solved. Afterward, in the second stage, the collected units will be shared between regions by applying the capacity sharing concept to avoid the blood shortage in health centers. Moreover, to tackle the uncertainty and disruption risk, a novel stochastic model combining the mixed uncertainty approach is tailored. A rolling horizon planning method is implemented under an iterative procedure to provide and share the limited blood resources to solve the proposed model. A real-world case study of Iran is investigated to examine the applicability and performance of the proposed model; it should be noted that the designed mechanism is not confined just to this case. Obtained computational results indicate the applicability of the model, the superior performance of the capacity sharing concept, and the effectiveness of the designed mechanism for mitigating the shortage and wastage during the COVID-19 outbreak.

Inventory management in blood supply chain considering fuzzy supply/demand uncertainties and lateral transshipment

Supply and demand uncertainties combined with very short lifetime of blood platelets has led to significant wastage of the total blood collected from the donors. Conversely, great shortage of platelets may be obtained due to the limited number of donors and emergency demands. Therefore, it is of utmost importance to develop appropriate inventory management model to simultaneously minimize both shortage and wastage along the blood supply chain. To achieve this purpose, this paper presents an Inventory Management model for Age-differentiated platelets under supply/demand Uncertainties (IMAU) for Blood Supply Chains with Lateral Transshipment (BSCLT), resulting a new model named IMAU-BSCLT. The proposed model is solved using whale optimization algorithm considering the costs of ordering from blood centers and lateral transshipment, transportation, inventory holding, shortage, and wastage. In order to validate the proposed methodology, a case study of blood supply chain is used to show the usability of the proposed model and claim its benefits over existing models. Simulation results demonstrate that lateral transshipment between different demand nodes has a major impact on load balancing leads to simultaneously reduce both shortage and wastage costs. According to the obtained results, shortage rate (total shortage per total demands) and wastage rate (total wastage per total supply) of the proposed method are 3.4 % and 4.8 %, respectively.

Re-design of a blood supply chain organization with mobile units

This research analyses the re-organization of a blood supply chain organization. Blood supply chain network design is a hard problem. Uncertainties of the blood supply and demand, perishability of blood over time and compatibility of blood types are some factors that make the problem difficult. This paper presents a novel multi-objective mixed-integer location-allocation model for a blood supply chain design problem. Unlike many studies on blood supply chain design in the literature, supply chain network consisting of mobile and permanent units is planned together effectively with our mixed-integer programming model. Multi-objective structure of the model minimizes distances between the blood supply chain elements and the length of the mobile unit routes. The objectives are prioritized by experts using the Analytical Hierarchical Process. Finally, the model is implemented on a real life case study using real data from the Eastern Anatolia region of Turkey for various supply demand scenarios. The solutions offered by the model are compared with the current situation in the region. It is shown that the proposed model gives at least %25 more effective solutions. Moreover, sensitivity analysis on the budget constraint is conducted, and robustness of the model is empirically illustrated.

A two-stage stochastic model for daily reserve in inventory management of Rh-negative red blood cells

Rh-negative rare blood inventory protection plays an important role in emergency blood protection. Normally, hospitals typically hold a fixed amount of daily reserve in response to emergency needs, but the measure can increase the unnecessary cost of repeated freezing and thawing. In order to save manpower, protect blood resources and reduce costs, a two-stage stochastic model is proposed to determine the optimal daily reserve of Rh-negative red blood cells, taking into account the uncertainty of demand. First, the model focuses on minimizing operational cost, shortage cost and damage caused by blood substitution. Then, the proposed model generates a series of discrete scenarios to solve the uncertainty of demand and predict the demand. In addition, a case study is presented to prove the validity of the proposed model with real data. Sensitivity analysis is also established to observe the effect of parameter changes on the results. Finally, the results show that the proposed model can effectively reduce the cost and current waste.

Inventory Management at a Chilean Hospital Pharmacy: Case Study of a Dynamic Decision-Aid Tool

Pharmacy inventory management is a critical process in healthcare centers. On the one hand, effective drug procurement is fundamental for fulfilling the therapeutic requirements of patients. On the other hand, as hospital pharmacies’ purchasing and storage costs comprise an important share in the hospital budgets, efficient inventory management may play a central role in operational cost containment. Therefore, healthcare centers should design and implement decision-aid strategies for planning the purchase of drugs with the aim of avoiding excessive purchasing volumes and optimizing warehouse capacity, while also meeting forecast demand and ensuring critical stock levels. In this study, we present the methodological features of a decision-aid tool for planning the purchases and inventory levels for the controlled medication pharmacy of the Regional Hospital of Talca, Chile. We report the results obtained after 1 year of operation; these results show that our strategy produced more than 7% savings compared to the regular inventory planning strategy and was more effective in preserving critical stock levels. Furthermore, from a computational point of view, our strategy outperforms a recently published approach for a similar application.

A reactive phase against disruptions for designing a proactive platelet supply network

Previous studies in blood supply chain network design often follow a commonly used approach in protecting the chain against disruptions, considering the effects of disruptions on the designing phase. However, in many real-world situations, disruptions cannot be adequately measured in advance. Moreover, using disruptions in the designing phase through the common two-stage stochastic programming models impose high costs on the network, since they cannot be updated based on unpredicted disruptions. This paper proposes an updatable two-phase approach which deals with disruptions in the operational phase, not in the strategic design phase. In the first step, called the proactive phase, a nominal platelet supply chain network is designed under operational uncertainty, using the whole-blood collection method. In the event of disruptions, the second step, called the reactive phase, is applied, and the tailored network is updated based on the realized data, using apheresis as the collection mechanism. The operational risks are captured using a fuzzy programming approach in the model. Based on the real data from Fars province of Iran, we compare the performance of the two-phase approach with the commonly used approaches in the literature, resulting in more flexible decisions, and consequently, less conservatism degree rather than the existing approaches.

A cross-sectional study of prevalence, distribution, cause, and impact of blood product recalls in the United States

Defective blood products that are recalled because of safety or potency deviations can trigger adverse health events and constrict the nation's blood supply chain. However, the underlying characteristics and impact of blood product recalls are not fully understood. In this study, we identified 4700 recall events, 7 reasons for recall, and 144 346 units affected by recalls. Using geospatial mapping of the newly defined county-level recall event density, we discovered hot spots with high prevalence and likelihood of blood product recall events. Distribution patterns and distribution distances of recalled blood products vary significantly between product types. Blood plasma is the most recalled product (87 980 units), and leukocyte-reduced products (34 230 units) are recalled in larger numbers than non-leukocyte-reduced products (8076 units). Donor-related reasons (92 382 units) and sterility deviations (22 408 units) are the major cause of blood product recalls. Monetary loss resulting from blood product recalls is estimated to be $17.9 million, and economic sensitivity tests show that donor-related reasons and sterility deviations contribute most to the overall monetary burden. A total of 2.8 million days was required to resolve recall events, and probabilistic survival time analysis shows that sterility deviations and contamination took longer to resolve because of their systemic effect on blood collection and processing. Our studies demonstrate that better donor screening procedures, rigorous sterility requirements, improved containment methods, and mitigation of recall events in high-prevalence regions will enable a more robust blood supply chain.

Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption

The perishability of blood platelets complicates the management of their supply chain. This paper studies the impact of energy consumption and carbon emissions of transportation activities in a blood platelet supply chain. Energy consumption and carbon emissions vary significantly, and the effective location-allocation of blood facilities is a key strategy for the optimal use of energy. The total cost of the supply chain for perishable products is minimized when energy consumption is optimized. The proposed model is too complex to be solved with existing methodologies; therefore, mathematical tools are used to solve it. A numerical experiment is carried out to validate the proposed model, and graphical representations are presented for better visualization of the study’s outcomes. The results of the numerical studies confirm that the selected locations of blood facilities are optimal for the maximization of energy efficiency and minimization of the total cost.

Designing the blood supply chain: how much, how and where?

BACKGROUND

The topology of the blood supply chain network can take different forms in different settings, depending on geography, politics, costs, etc. Many developed countries are moving towards centralized networks. The goal for all blood distribution networks, regardless of topology, remains the same: to satisfy demand at minimal cost and minimal wastage.

STUDY DESIGN AND METHODS

Mathematically, the blood supply system design can be viewed as a location-allocation problem, where the aim is to find the optimal location of collection and production facilities and to assign hospitals to them to minimize total system cost. However, most location-allocation models in the blood supply chain literature omit several important aspects of the problem, such as selecting amongst differing methods of collection and production. In this paper, we present a location-allocation model that takes these factors into account to support strategic decision-making at different levels of centralization.

RESULTS

Our approach is illustrated by a case study (Colombia) to redesign the national blood supply chain under a range of realistic travel time limitations. For each scenario, an optimal supply chain configuration is obtained, together with optimal collection and production strategies. We show that the total costs for the most centralized scenario are around 40% of the costs for the least centralized scenario.

CONCLUSION

Centralized systems are more efficient than decentralized systems. However, the latter may be preferred for political or geographical reasons. Our model allows decision-makers to redesign the supply network per local circumstances and determine optimal collection and production strategies that minimize total costs.