Intervention Effect of PIVAS Pharmacists on Unreasonable Medical Orders
Objective To provide a reference for standardizing intravenous medication orders and improving the rational application of clinical intravenous medication.Methods The unreasonable medical orders of the hospital from October 2021 to September 2022 were collected from the Pharmacy Intravenous Admixture Services(PIVAS),the overall profile,distribution,and reasons for unreasonable medical orders in the hospital and each department were analyzed,and the intervention effect of PIVAS pharmacists the was evaluated.Results From October 2021 to September 2022,79 520 PIVAS orders were issued,including 552 unreasonable orders(accounting for 0.69%).Unreasonable medical orders was most common in the departments of oncology,orthopedics,and thoracic surgery,with incidence rates of 60.87%,14.31%,and 10.14%,respectively.The main types of unreasonable medical orders were unreasonable dosage,unreasonable solvent,unreasonable dosing concentration,and unreasonable use frequency,with incidence rates of 29.71%,21.92%,21.74%,and 19.20%,respectively.The main reasons for unreasonable medical orders were inadequate prior communication,poor clinical understanding,and unfamiliarity with drug inserts.Through the prescription review and intervention of the PIVAS pharmacists,the communication and training with physicians were strengthened,the number of unreasonable medical orders gradually decreased,and the incidence of unreasonable medical orders was basically controlled within 1%.Conclusion PIVAS pharmacists' intervention in unreasonable medical orders,and timely detection and correction can effectively reduce the medication risks caused by irregular and unreasonable clinical orders for intravenous infusion drugs,provide pharmaceutical support for improving the safety of intravenous medication,and ensure the rationality,safety,and effectiveness of clinical intravenous medication.
pharmacy intravenous admixture servicesunreasonable medical ordersrational drug useintervention effect
万方数据
维普
