Model for blood collections management

Abstract

The results obtained from the simulation model for a real-life situation show that the cutoff level policies are better than the unrestricted collection policy in controlling total costs. They also result in less wastage in the system for a given level of shortages.

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

“…Other researchers have studied collection policies and collection methods and their impact on the performance indicators of the blood supply chain. Lowalekar and Ravichandran [6] develop a simulation model to evaluate different collection policies. One of the main conclusions of this work is that it is not necessarily beneficial to collect as much blood as possible.…”

A combined age‐and‐stock‐based policy for ordering blood units in hospital blood banks

“…() showed that variations of simple order‐up‐to‐level policies were quite effective in managing the inventory of platelets. Lowalekar and Ravichandran () showed that a cutoff‐level policy, which is a modification of the classic ( R , T ) policy, was effective in controlling total costs in blood banks when the supply quantity was not deterministic. Zhou et al.…”

“…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.…”

“…Thus, collecting a large number of units of rare blood types can actually be disastrous for a blood bank since it can experience both wastage and shortage due to the erratic demand pattern of such products. Moreover, the traditional approach of aggregating the demand information for all the blood types in order to determine the order (production) quantities (Lowalekar and Ravichandran, , ) can have serious implications for rare blood types. In this research, we analyze all the blood types separately and identify suitable ordering policy (and its parameters) for each of them using our simulation model.…”

“…Haijema et al (2007Haijema et al ( , 2009) and showed that variations of simple order-up-to-level policies were quite effective in managing the inventory of platelets. Lowalekar and Ravichandran (2010) showed that a cutoff-level policy, which is a modification of the classic (R, T) policy, was effective in controlling total costs in blood banks when the supply quantity was not deterministic. Zhou et al (2011) studied an order-up-to-level policy for platelets under two replenishment modes: (a) regular replenishment at the start of the ordering cycle and (b) optional expedited replenishment in the middle of an ordering cycle.…”