Case Studies

Improving Red Cross Blood Drives Through Simulation

Brennan, J. E., Bruce L. Golden, and Harold K. Rappoport. "Go with the Flow: Improving Red Cross Bloodmobiles Using Simulation Analysis." Interfaces, 22: 1 (1992), 1-13.

The American Red Cross was concerned with the excessive time spent waiting in lines while donating blood. Since all blood collected by the Red Cross is from voluntary donors, the organization was concerned that long waits might affect a donor's willingness to make subsequent blood donations. In addition many blood drives are at work places, and employers are interested in reducing the time off the job while donating blood.

A computer simulation model was used to develop and test several strategies for alleviating this wait-time. They included combining some or all of the donor screening steps, adopting a six-bed to eight-bed donor room with two phlebotomists (instead of the usual three-bed donor room with one phlebotomist), and developing formal work rules for floating staff.

The strategies that resulted from the simulation analysis were tested at three sites in North Carolina. In one study donor time in the system was reduced from an average of sixty minutes to approximately forty minutes. Surveys were conducted of blood donors and staff of the local American Red Cross. More than 60% of the repeat donors felt they spent less time under the new procedures for donating. In addition, nurses reported they were able to more closely observe the donors in a six- to eight-bed donor room. The staff was able to spend more time inspecting the donor registration form for errors and utilize the space more efficiently. This simulation modeling worked best for closed, business-sponsored blood drives.

There are restrictions to the implementation of this model. Budget limitations, including the shortage of nurses and the funding for training non-nursing staff, are implementation factors for this model. The incidence of impromptu donors, which is difficult to simulate, is another factor affecting the accuracy of the model.

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