1976
DOI: 10.1016/0038-0121(76)90039-2
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Simulation of a blood-inventory-bank system in a hospital

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Cited by 21 publications
(8 citation statements)
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“…Studies that targeted the individual hospital level generally examined hospital blood blanks. Various problems were solved in this regard such as evaluating the factors affecting stock level and reducing the blood wastage in hospital blood banks (Dumas & Rabinowitz, ; Pink, Thomson, & Wylie, ; Perera, Hyam, Taylor, & Chapman, ; Yates, Stanger, Wilding, & Cotton, ); developing benchmarking targets for RBC outdates at hospital blood banks (Heddle et al., ); simulating the blood inventory system to reconsider the blood ordering strategy or improve the inventory policy (Rabinowitz, ; Vrat & Khan, ; Lowalekar & Ravichandran, ); and examining how alternative hospital policies might impact the blood inventory policy (Pegels, Seagle, Cumming, Kendall, & Shubsda, ).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Studies that targeted the individual hospital level generally examined hospital blood blanks. Various problems were solved in this regard such as evaluating the factors affecting stock level and reducing the blood wastage in hospital blood banks (Dumas & Rabinowitz, ; Pink, Thomson, & Wylie, ; Perera, Hyam, Taylor, & Chapman, ; Yates, Stanger, Wilding, & Cotton, ); developing benchmarking targets for RBC outdates at hospital blood banks (Heddle et al., ); simulating the blood inventory system to reconsider the blood ordering strategy or improve the inventory policy (Rabinowitz, ; Vrat & Khan, ; Lowalekar & Ravichandran, ); and examining how alternative hospital policies might impact the blood inventory policy (Pegels, Seagle, Cumming, Kendall, & Shubsda, ).…”
Section: Literature Reviewmentioning
confidence: 99%
“…In addition to the works cited above, which use integer and linear programming methods to solve the problems they address, the blood supply chain literature includes several studies that use simulation tools to identify means of improving overall operational efficiency (Vrat and Khan, ; Rytila and Spens, ; Katsaliaki and Brailsford, ; Özgen, ; Mustafee et al., ). In turn, Catassi and Peterson () and Frankfurter et al.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Since the assumption of actual aging makes analytical models intractable (see Ravichandran, 1995), we use simulation as a tool for an analysis. Simulation models (Rabinowitz, ; Vrat and Khan, ; Cohen and Pierskalla, ; Haijema et al., , ; van Dijk et al., ; Katsaliaki et al., ; Mustafee et al., ; Lowalekar and Ravichandran, , ; Katsaliaki and Mustafee, ) have been immensely used in blood banking to test the effects of various system variables and policies on the overall performance of a blood bank. Even though simulation studies suffer from the problem of lack of generalizability of results (Cohen and Pierskalla, 1979), they can incorporate complexities of a real‐life situation such as blood banks (e.g., multiple blood groups, intergroup substitutability, componentizing, cross‐matching, inter‐blood bank transfers, etc.…”
Section: Literature Reviewmentioning
confidence: 99%