A study of inventory classification in healthcare logistics using system dynamics modelling.

One of the key challenges for a modern day health care provider is to dispense high quality of medical care while limiting or even reducing the health care expenditures. This research work endeavours to meet this challenge through effective management of hospitals logistics systems. The aim of this research work is to provide a structured mechanism for modelling and analysing health care logistics to be able to understand its dynamic behaviour and effectively manage its logistical activities on the basis of the model. In order to achieve the research objectives, this research uses system dynamics as the main medium of analysis, and in particular, employs an integrated system dynamics framework which has been used previously for manufacturing industry supply chain designs and tests the feasibility of the framework for analysing and modelling health care logistics. This is ascertained by developing and incorporating a decision making metrics in the system dynamics model based on item criticality, usage, and value to optimise overall logistics costs. System Dynamics methodology is employed at first to develop a model for existing inventory control decisions, and subsequently to produce two alternative approaches based on traditional (R, s, S) inventory control approach and Continuous Replenishment Inventory and Order Based Production Control CR(IOBPCS) approach. These approaches are tested for two case hospitals, namely: Children's National Medical Center (CNMC) USA, and Derbyshire Royal Infirmary (DRI) UK. The dynamic analysis for each case revealed problems in terms of multistage inventories and order batching, which could lead to demand amplification causing a detrimental effect on the inventory management throughout the supply chain. Accordingly, the simulations results produced for the two cases are benchmarked using alternative strategies in terms of lower inventory cost, and robustness to meet the unpredictable demand arising from a large number of items. Overall, this research work has enhanced the understanding of hospitals logistics systems by building qualitative and quantitative models. More specifically, this research work has illustrated the applicability of the integrated system dynamics framework in analysing and modelling hospitals logistics systems and inventory control decisions. One particular contribution of this study is introducing inventory classification based on the criticality of items for patient needs which is more suited for health care situations rather purely cost based policies prevalent in other manufacturing and service chains. Therefore, this work has rigorously tested a multi-criteria based inventory classification method that takes into account the criticality of use, cost, and usage value of items for optimising overall inventory cost while maintaining the required patient care/service level. Future studies may be conducted to further evaluate the trade-offs in between different logistics decision making (such as, inventory control, service level, purchasing, transportation and warehousing) in order to design a set of "best practice" simulation models to optimise the overall dynamic behaviour for health care supply chains.