A resilient donor arrival policy for blood

Fortsch, Sima M.; Perera, Sandun

doi:10.1016/j.orhc.2018.04.003

Cited by 10 publications

(6 citation statements)

References 59 publications

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“…Aside from blood availability, blood centers face challenges like demand uncertainty (Nagurney & Dutta, 2019; Fortsch & Khapalova, 2016), inventory management, limited available resources (Privett & Gonsalvez, 2014) and random distribution of the donor arrivals (Fortsch & Perera, 2018). To make blood operations easier to comprehend, we created a simplified process flow diagram depicting a series of activities required for this industry.…”

Section: Literature and Blood Supply Chainmentioning

confidence: 99%

Mitigating the risk of blood shortage

Fortsch

Khapalova

Carden³

et al. 2023

JBSE

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PurposeThe objective of this study is to mitigate the risks of a blood shortage. The authors designed two simulation studies to identify the superior methodology that can decrease the impact of a massive national donor shortage.Design/methodology/approachThe simulation designs are triggered by the COVID-19 pandemic. The first simulation examines the company’s choice of strategic partners (regionally and nationally), and the second inspects creating a national coordinated effort to organize a pooled blood inventory that would require blood centers to contribute a small percentage of their monthly donations to become a member.FindingsThe results indicate that both methods can significantly manage the risk of stockouts regardless of the availability of safety inventory in a blood center; however, although more effective in reducing the number of shortages per month, creating a national blood pool causes the shortages to be recognized earlier than desired.Originality/valueThe authors contribute to the literature by focusing on the potential risk of blood shortage because it directly impacts healthcare, hospitals’ costs and their ability to provide care. Though a handful of researchers have targeted the study of the blood supply chain, there is not any article that is similar to this study.

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Section: Literature and Blood Supply Chainmentioning

confidence: 99%

Mitigating the risk of blood shortage

Fortsch

Khapalova

Carden³

et al. 2023

JBSE

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“…A noticeable part of single-stage studies deals with the collection stage. Among the 32 single-stage collection focused studies, the most frequent topics are perceiving donors' behavior [85][86][87][88][89]; prediction of donations [90][91][92]; determination of donor arrival policy [93][94][95][96]; location allocation [6,49], and vehicle routing [97][98][99][100][101][102][103]. The most utilized solution methods for this stage are stochastic/robust programming, deterministic mixed-integer programming, and statistical analysis techniques, with 25, 24, and 5 implementations, respectively.…”

Section: Collectionmentioning

confidence: 99%

A Systematic Literature Review of the Blood Supply Chain through Bibliometric Analysis and Taxonomy

Imamoglu

Topçu

Aydın

2023

Systems

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The blood supply chain is an inseparable part of health systems. The importance of blood and the difficulties of managing the blood supply chain have led to numerous publications on this topic over the last two decades. This study seeks to reveal the state of the art of the blood supply chain and provide research gaps and future research directions. For this purpose, a mixed review methodology is conducted that includes bibliometric analysis, network analysis, and a six-dimension taxonomy. Bibliometric analysis identifies the most contributing journals, authors, and countries as well as provides popular keywords, while network analysis reveals interactions between these components. Taxonomy clarifies decision models and research gaps with a deeper examination. The electronic database Web of Science is examined to uncover relevant articles. In total, 265 articles are analyzed in detail. The findings reveal that the blood supply chain gathers more interest from researchers, and despite the continuing dominance of the inventory stage, there is an upward trend in the literature for the research of the blood supply chain as a whole. Optimization techniques come forward in the blood supply chain topic as solution methodology. In accordance with the results of bibliometric analysis, network analysis, and taxonomy, six prospective directions for future research are emphasized.

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“…Researchers also note on multiple occasions that there are no particular methods that are guaranteed to give accurate forecasts and that the best method may change over time 3,12,14 . To avoid laborious periodic method reselection, others have suggested using method selection systems and specific automatic procedures (most often the Box‐Jenkins procedure 15 ) to help evaluate and select Autoregressive Integrated Moving Average (ARIMA) models without human intervention 4–6,13,14 …”

Section: Introductionmentioning

confidence: 99%

“…According to a recent survey, 1 most research on supply chain planning assumes demand as stochastic, deterministic, or otherwise intractably uncertain, using constant estimates or distribution sampling. However, demand forecasting has been deemed necessary and superior to expert planning in several studies, [1][2][3][4][5][6][7][8][9][10][11] suggesting that supply chain management approaches can be improved by a significant margin by adopting methods for demand forecasting. Almost all reviewed research on demand forecasting attempts to determine the single best method for reducing shortages or costs, revealing that the best method varies between blood banks and blood products.…”

Section: Introductionmentioning

confidence: 99%

“…3,12,14 To avoid laborious periodic method reselection, others have suggested using method selection systems and specific automatic procedures (most often the Box-Jenkins procedure 15 ) to help evaluate and select Autoregressive Integrated Moving Average (ARIMA) models without human intervention. [4][5][6]13,14 In this study, we use a marked but relatively brief change in the behavior of the weekly red blood cell demand in Finland to examine how the continuation of this behavior would affect method performance and selection. We then devise heuristics for method selection that could allow an autonomous system to produce robust forecasts without supervision during changes in the demand behavior and compare the performance of such a system with individual method performance using altered demand data.…”

Section: Introductionmentioning

confidence: 99%

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A robust autonomous method for blood demand forecasting

et al. 2022

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Background Blood supply chain management requires estimates about the demand of blood products. The more accurate these estimates are, the less wastage and fewer shortages occur. While the current literature demonstrates tangible benefits from statistical forecasting approaches, it highlights issues that discourage their use in blood supply chain optimization: there is no single approach that works everywhere, and there are no guarantees that any favorable method performance continues into the future. Study Design and Methods We design a novel autonomous forecasting system to solve the aforementioned issues. We show how possible changes in blood demand could affect prediction performance using partly synthetic demand data. We use these data then to investigate the performances of different method selection heuristics. Finally, the performances of the heuristics and single method approaches were compared using historical demand data from Finland and the Netherlands. The development code is publicly accessible. Results We find that a shift in the demand signal behavior from stochastic to seasonal would affect the relative performances of the methods. Our autonomous system outperforms all examined individual methods when forecasting the synthetic demand series, exhibiting meaningful robustness. When forecasting with real data, the most accurate methods in Finland and in the Netherlands are the autonomous system and the method average, respectively. Discussion Optimal use of method selection heuristics, as with our autonomous system, may overcome the need to constantly supervise forecasts in anticipation of changes in demand while being sufficiently accurate in the absence of such changes.

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A resilient donor arrival policy for blood

Cited by 10 publications

References 59 publications

Mitigating the risk of blood shortage

Mitigating the risk of blood shortage

A Systematic Literature Review of the Blood Supply Chain through Bibliometric Analysis and Taxonomy

A robust autonomous method for blood demand forecasting

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