Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10968617 | Vaccine | 2011 | 7 Pages |
Abstract
In a low or middle income country, determining the correct number of routine vaccines to order at a health clinic can be difficult, especially given the variability in the number of patients arriving, minimal vaccination days and resource (e.g., information technology and refrigerator space) constraints. We developed a spreadsheet model to determine the potential impact of different ordering policies, basing orders on the arrival rates seen in the previous 1, 3, 6, or 12 sessions, or on long-term historical averages (where these might be available) along with various buffer stock levels (range: 5-50%). Experiments varied patient arrival rates (mean range: 1-30 per session), arrival rate distributions (Poisson, Normal, and Uniform) and vaccine vial sizes (range: 1-dose to 10-dose vials). It was found that when the number of doses per vial is small and the expected number of patients is low, the ordering policy has a more significant impact on the ability to meet demand. Using data from more prior sessions to determine arrival rates generally equates to a better ability to meet demand, although the marginal benefit is relatively small after more than 6 sessions are averaged. As expected, the addition of more buffer is helpful in obtaining better performance; however, this advantage also has notable diminishing returns. In general, the long-term demand rate, the vial sizes of the vaccines used and the method of determining the patient arrival rate all have an effect on the ability of a clinic to maximize the demand that is met.
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Authors
Jayant Rajgopal, Diana L. Connor, Tina-Marie Assi, Bryan A. Norman, Sheng-I Chen, Rachel R. Bailey, Adrienne R. Long, Angela R. Wateska, Kristina M. Bacon, Shawn T. Brown, Donald S. Burke, Bruce Y. Lee,