Résumé
80% defined as category A,B,and C,respectively.Category A drugs were regarded as the focus of management,category B as the second focus of management,category C underwent general management,category D drugs were regarded as the focus in purchase.RESULTS:Hospital first-order drug storeroom and secondary drug storerooms classified their drugs into their own A,B,and C categories (category D was consistent).The consumption sum of category A drugs(about 20% of drugs) accounted for 60%;the consumption sum of category B drugs(about 20% of drugs) accounted for 20%;and the consumption sum of category C drugs(about 60% of drugs) plus that of small quantity of category D drugs accounted for 20%.CONCLUSION:This method can ensure drug supply and help maximize ec-onomical benefits with least human,material and financial resources.
Résumé
OBJECTIVE:To explore the new drug purchasing mode using autoregressive integrated moving-average (ARIMA) prediction model for improvement of the working quality and efficiency in hospital drug storeroom.METHODS:Drug consumption data from week 1 to week 47 in 2008 were collected.According to ABC method,category A drugs were defined among which 10 kinds of drugs were sampled randomly.Based on the data of from week 1 to week 44 in 2008,software SPSS13 was applied for the modeling and fitting of ARIMA model.The established model was applied to predict the data of from week 45 to 47,with the predicated data compared with the actual consumption data.RESULTS:The predicted purchasing amount using ARIMA model were consistent with the actual consumption data,with prediction accuracy for quantity at 89.19% and prediction accuracy for whole unit of purchased drugs at 97.56%,respectively.CONCLUSIONS:Good fitting and high short-medium term predication accuracy were obtained in the prediction using ARIMA model,and which could provide scientific support for drug purchasing and help manage the drug stock reasonably without appearance of out of stock or overstock.
Résumé
OBJECTIVE: To standardize and simplify the drug receving and preparing model. METHODS: Reasonable pharamcy inventory parameters were set up based on our experience; second order drug storeroom dynamic inventory system was designed and applied, and the indexes of drug storeroom inventory and workload of the new and the old models were reported and analyzed. RESULTS: The new warning system provided an optimal inventory, and in which the incidences of overstock or stock shortage, the frequency of daily drug receving, drug kinds and the time used with checking stock and filling receipt were all significantly less than in the traditional model. CONCLUSION: Due to the second order drug storeroom dynamic inventory warning system, the drug receiving was more scientific, the drug stock amount was reduced and the drug receiving time was saved, and the mangament level of hospital drug storeroom inventory was enhanced.