Reducing the age of transfused red blood cells in hospitals: ordering and allocation policies.

BACKGROUND: Although recent randomized controlled trials have not found increased risk of morbidity/mortality with older red blood cells (RBCs), several large trials will be completed soon providing power to detect smaller risks if indeed they exist. Hence, there may still be a need for inventory management policies that could reduce the age of transfused RBCs without compromising availability or resulting in excessive outdates. MATERIALS AND METHODS: We developed a computer simulation model based on data from an acute care hospital in Hamilton, Ontario. We evaluated and compared the performance of certain practical ordering and allocation policies in terms of outdate rate, shortage rate and the distribution of the age of issued RBCs. RESULTS: During the 1-year period for which we analysed the data, 10349 RBC units were transfused with an average issue age of 20·7 days and six units were outdated (outdate rate: 0·06%). Adopting a strict first in, first out (FIFO) allocation policy and an order-up-to ordering policy with target levels set to five times the estimated daily demand for each blood type, reduced the average issue age by 29·4% (to 14·6 days), without an increase in the outdate rate (0·05%) or resulting in any unmet demand. Further reduction of issue age without a significant increase in outdate rate was observed when adopting non-FIFO threshold-based allocation policies and appropriately adjusting the order-up-to levels. CONCLUSION: A significant reduction of issue age could be possible, without compromising availability or resulting in excessive outdates, by properly adjusting the ordering and allocation policies at the hospital level.

The influence of partial implant-supported restorations on chewing side preference.

This study aimed at determining whether the individual's chewing side preference is affected by local effects, produced by the presence of implant-supported restorations. The test group included 81 patients with partial implant-supported prosthesis. The control group included 108 subjects with no implants. All subjects went through a series of laterality tests for chewing and tasks (hand, foot, eye and ear) side preference. The preferred chewing side (PCS) was determined by observing the first stroke of the chewing cycle during chewing a gum. A positive and significant correlation between the chewing side preference and the subject's sidedness during the different tasks was examined, by performing four Phi correlation tests for: chewing and handedness(r = 0·54; P < 0·001); chewing and footedness (r = 0·49; P < 0·001); chewing and eyedness (r = 0·65; P < 0·001) and chewing and earedness (r = 0·66, P < 0·001). Of the subjects, 78·3% preferred the right side for chewing, 19·1% preferred the left and 2·1% had no clear side preference. There was no statistical difference in chewing side preference distribution between genders. The distribution of chewing side preference was not significantly affected by the location of missing teeth or implants. In conclusion, implant placement will not affect PCS. Therefore, information on chewing side preference should be part of the routine preoperative examination for implant-supported restorations to provide a better treatment plan in those cases that the implant-supported restoration will be on the PCS.

Devising a cooperation policy for emergency networks.

A mathematical programming model is proposed to select an optimal cooperation policy between autonomous service networks for dispatching purposes. In addition to traditional characteristics such as network topology and station location, this model takes into account 'political' constraints on minimum response-time in certain subzones. Such constraints are translated into performance requirements, which are imposed on the cooperation policy. Testing the model under different assumptions can be useful for analysing various cooperation policies. The paper formulates a mathematical programming model, derives example policies for various circumstances, and tests the sensitivity of the resultant policies to some parameters, such as the penalty for not providing service, and distances between adjacent networks. The paper suggests also a less constrained approach, which entails a linear programming model. A comparison between the two approaches is presented.