Funding for this project was provided by the Natural Sciences and Engineering Research Council of Canada Discovery Grant program and by Canadian Blood Services.
DONOR RECRUITMENT AND MOTIVATION
Determining staffing requirements for blood donor clinics: the Canadian Blood Services experience
Article first published online: 28 JUL 2013
© 2013 American Association of Blood Banks
Special Issue: Donating Blood: Who? Why? What of It?
Volume 54, Issue 3pt2, pages 814–820, March 2014
How to Cite
Blake, J. T. and Shimla, S. (2014), Determining staffing requirements for blood donor clinics: the Canadian Blood Services experience. Transfusion, 54: 814–820. doi: 10.1111/trf.12353
- Issue published online: 11 MAR 2014
- Article first published online: 28 JUL 2013
- Manuscript Revised: 13 JUN 2013
- Manuscript Accepted: 13 JUN 2013
- Manuscript Received: 26 APR 2013
- Natural Sciences and Engineering Research Council of Canada Discovery Grant
- Canadian Blood Services
Canadian Blood Services runs approximately 16,000 donor clinics annually. While there were more than 220 different clinic configurations used in 2011 and 2012, 67% of all clinic configurations followed one of 51 standard models. As part of operational planning for current and future configurations it was necessary for Canadian Blood Services to calculate staffing requirements for standard clinic models.
Study Design and Methods
In this article we present a method that incorporates both cost control and impact on donor experience. We calculate staffing requirements to minimize costs, but adjust using queuing theory to ensure donor wait time metrics are met. The method can be applied in a wide variety of situations.
Although developed for a particular study, the methods described in this article can be applied in a wide variety of situations. A case study in which the model is used to review existing staffing arrangements at Canadian Blood Services is presented.
The staffing model can be used to balance the requirements of minimizing staffing costs with that of ensuring that donors do not suffer unnecessary delays. Moreover, in an example application, savings of 3.4% were identified through the modeling process.