TY - JOUR
T1 - The impact of implementing a demand forecasting system into a low-income country's supply chain
AU - Mueller, Leslie E.
AU - Haidari, Leila A.
AU - Wateska, Angela R.
AU - Phillips, Roslyn J.
AU - Schmitz, Michelle M.
AU - Connor, Diana L.
AU - Norman, Bryan A.
AU - Brown, Shawn T.
AU - Welling, Joel S.
AU - Lee, Bruce Y.
N1 - Funding Information:
This work was supported by the Bill and Melinda Gates Foundation , the Agency for Healthcare Research and Quality (AHRQ) via grant R01HS023317 , the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Office of Behavioral and Social Sciences Research (OBSSR) and the Global Obesity Prevention Center (GOPC) via grant U54HD070725 , NICHD via grant U01 HD086861 , the National Institute for General Medical Sciences via grant U24GM110707 and USAID via grant AID-OAA-A-15-00064 . The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/7/12
Y1 - 2016/7/12
N2 - Objective To evaluate the potential impact and value of applications (e.g. adjusting ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country's vaccine supply chain with different levels of population change to urban areas. Materials and Methods Using our software, HERMES, we generated a detailed discrete event simulation model of Niger's entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. Results Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. Discussion The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. Conclusion Demand forecasting systems have the potential to greatly improve vaccine demand fulfilment, and decrease logistics cost/dose when implemented with storage and transportation increases. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements.
AB - Objective To evaluate the potential impact and value of applications (e.g. adjusting ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country's vaccine supply chain with different levels of population change to urban areas. Materials and Methods Using our software, HERMES, we generated a detailed discrete event simulation model of Niger's entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. Results Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. Discussion The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. Conclusion Demand forecasting systems have the potential to greatly improve vaccine demand fulfilment, and decrease logistics cost/dose when implemented with storage and transportation increases. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements.
KW - Health information systems
KW - Immunization
KW - International health
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U2 - 10.1016/j.vaccine.2016.05.027
DO - 10.1016/j.vaccine.2016.05.027
M3 - Article
C2 - 27219341
AN - SCOPUS:84991275193
SN - 0264-410X
VL - 34
SP - 3663
EP - 3669
JO - Vaccine
JF - Vaccine
IS - 32
ER -