Discussion on the Optimization Scheme for Variety and Quantity of Drugs Equipped in Emergency Medical Vehicle of Clinical Wards / 中国药房

ABSTRACT

OBJECTIVE:To investigate the optimization scheme for variety and quantity of drugs equipped in emergency medical vehicle of clinical wards in order to meet the clinical first-aid drugs needs timely and accurately. METHODS:Used with large data analysis, by analyzing the data of drug use for large-scale and medium-scale first-aid in our hospital during May 2016-Mar. 2017 (before optimization equipment),the ratio of fully satisfied first-aid demand was calculated. The drug variety on the emergency medical vehicle of our hospital was determined according to the related first-aid drug catalogue. In addition,every drug was arranged respectively in ascending order according to the quantity used in firs-aid before optimization equipment,and then the number in 75％ quantile of each variety was determined as the target quantity using quartile method. The drugs were arranged in descending order according to use frequency in ambulance,drug variety of each ward was determined according to 95％ accumulative ratio. The ratio of drug variety outside ambulance used in first-aid was calculated after optimization (Apr.-Jul. 2017),and then compared with before optimization equipment. The rationality of optimization scheme was validated. RESULTS:Before optimization,there were 8 drug varieties equipped in emergency medical vehicle of our hospital,and 4 injections of each variety were prepared;the ratio of fully satisfied first-aid demand was 38％(776 times/2042 times). After optimization equipment,19 kinds of first-aid drugs which used mostly were determinated in the whole hospital,and the quantities of all kinds of drugs had been equipped scientifically;the ratio of fully satisfied first-aid demand was 78％(636 times/815 times). According to the characteristics of each ward,a personalized scheme (including specific varieties and corresponding quantities) was made. The ratio of drug variety outside emergency medical vehicle decreased from 46.42％ to 25.51％ in average. CONCLUSIONS:The optimization scheme formulated according to large data analysis can accurately meet clinical first-aid demand.