Solving Deficit Funding Issues in Indonesian Health Insurance Systems Indonesian National Health Insurance System (INHIS) is a government program that aims to provide health insurance to citizens by guaranteeing their health services. However, INHIS finances continued to experience a deficit since 2014. The purpose of this study was to find a solution so that the stock of funds remained stable. This is done by changing the patientu0027s referral mechanism in INHIS. This is one solution so that the total health care costs do not increase. In this case the dynamic system simulation model is needed to find the relationship pattern between variables so that it can estimate the condition of INHIS funds. The decision variables in this study are the total health care costs and the stock of funds. From the simulation process, the results show that the proposed model can reduce the total health care costs by 44% and be able to maintain a stable supply of funds up to 40% of the sudden increase.

Inventory Replenishment Policy for Medicines with NonStationary Stochastic Demand: The Case of a Newly Opened Hospital in Thailand Inventory and replenishment planning of medicines play a vital role in hospital management. A large replenishment quantity can lower the percentage of medicine shortage, which might be critical for a patientu0027s life, but somehow needed to be traded off with high inventory cost from excessive stock. Especially for a vital medicine with nonstationary stochastic demand e.g., antivenom serum or adrenaline, demand for these medicines found to be intermittent since itu0027s an unpredictable event, but a shortage of these medicines when needed will result in a serious loss. Adequate recorded data allow the pharmacist a better decide on its replenishment policy. However, this case study is not yet existed since a hospital has just opened for four months. Hence, the objective of this paper is to propose a replenishment policy (Rn,Sn) for this type of medicine including optimal orderupto level and period with lowest expected total cost using Tarim and Kingsmanu0027s MILP. A newly opened hospital in Thailand was selected as a case study. The results were compared with current policy and now being cited as its reference orderupto level.