Dynamic Coordination And Optimization Of Ordering And Delivery Of Medical Supplies Based On Real Time Data

The separation of medicine and drug is the key factor for the formation of a rational system of medical circulation.As an attempt to deepen the reform of the medical system,the pharmacy trusteeship reduces the pressure on the management and operation of the hospital.At the same time it also puts forward higher requirements on the purchase,distribution,storage and management of the medical supplies.How to combine the dynamic changes in hospital needs to achieve effective coordination of drug material ordering and distribution is an important issue in current practice.In this paper,we focus on the ordering and delivery of flu drugs under the pharmacy trusteeship,and propose a decision framework model(FPEA)that includes the four phases of forecasting(F),planning(P),execution(E)and adjustment(A)model.In the forecasting phase,we construct a SIRS dynamics model for the spread of influenza and design a time-varying demand forecasting model based on the SIRS model.In the planning stage,aiming at the minimum total cost of ordering and delivery as the decision-making target,we construct the coordination and optimization model of ordering and delivery of single and multiple drugs for flu drugs combined with the forecast demand of the planning cycle.Then we implement the optimization result of the planning phase in a managed pharmacy during the execution phase,and collect actual daily data on the demand for influenza drugs.At the end of this planning cycle,we adjust and update the relevant parameters of the forecasting model according to the daily actual data collected from the decision-making period so that we can make a smooth transition to the forecasting of the next decision cycle.Through the research,we can find that:1.Compared with the static optimization problem of traditional medical material ordering and delivery,the FPEA model combines the flu diffusion analysis,dynamic ordering and delivery of drugs,pharmacy hosting factors to consider together,which make the research more practical value.2.In this paper,we use the real-time data collection and management system to collect the actual observation data of each decision cycle and then dynamically adjusts the relevant parameters of the flu epidemic diffusion model.This represents a data-driven feature and achieves the goal of reducing forecast errors,establishing more accurate drug ordering and delivery planning,and saving on operational costs for pharmacy hosting.