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作 者:郭建芳 雷越辰 胡宗苗 冯琴琴 张朝 张萍 吴爽爽 张慧 GUO Jianfang;LEI Yuechen;HU Zongmiao;FENG Qinqin;ZHANG Zhao;ZHANG Ping;WU Shuangshuang;ZHANG Hui(521 Hospital of Norinco Group,Xi'an 710065;Ordnance Industrial Hygiene Research Institute,Xi'an 710065,China)
机构地区:[1]西安兵器工业五二一医院,陕西西安710065 [2]兵器工业卫生研究所,陕西西安710065
出 处:《临床医学研究与实践》2023年第21期178-182,共5页Clinical Research and Practice
基 金:2021年度所级科技和管理创新项目(No.104)。
摘 要:目的临床药师应用人工智能技术,结合本院实际情况对合理用药监测系统(PASS)进行优化,以期增加常见不合理用药问题警示,提升药学服务水平。方法通过问卷调查收集临床对PASS提示的需求,依据本院近年常见不合理用药情况,确定待维护警示内容。通过自定义优化PASS,实时审核用药合理性。比较优化前、后警示情况及弹出警示信息价值。结果本次PASS优化共自定义维护3315条警示信息。优化后,门急诊红灯、橙灯警示及住院红灯、黑灯、橙灯警示多于优化前,门急诊黑灯警示少于优化前,差异具有统计学意义(P<0.01)。优化后,门急诊剂量范围、配伍浓度、钾离子监测警示项目少于优化前,相互作用、儿童用药、成人用药、老人用药、重复用药、超多日用量、自由自定义警示项目多于优化前,差异具有统计学意义(P<0.05);优化后,住院剂量范围、体外配伍、药物禁忌证、成人用药、妊娠用药、重复用药、钾离子监测、自由自定义警示项目多于优化前,儿童用药警示项目少于优化前,差异具有统计学意义(P<0.05)。优化后,认为弹出警示信息非常有帮助的医务人员占比高于优化前,差异具有统计学意义(P<0.05)。结论优化PASS可提升本院人工智能水平,提高药师服务水平,扩大药学服务范围。Objective Clinical pharmacists apply artificial intelligence technology to optimize the prescription automatic screening system(PASS)based on actual situation of our hospital,in order to increase warnings of common unreasonable drug use issues,and improve the level of pharmaceutical service.Methods A questionnaire survey was conducted to collect the clinical demand for PASS prompts,and the warning content to be maintained was determined based on the common unreasonable drug use in our hospital in recent years.By customizing and optimizing PASS,real-time review of medication rationality was achieved.The warning situation and value of pop-up warning messages before and after optimization were compared.Results A total of 3315 warning messages were customized and maintained for this PASS optimization.After optimization,the red light,orange light warnings in outpatient and emergency department and red light,black light,orange light warnings in inpatients were more than those before optimization,the black light warnings in outpatient and emergency department was less than that before optimization,and the differences were statistically significant(P<0.01).After optimization,the dosage range,compatibility concentration and potassium ion monitoring warning items in outpatient and emergency department were less than those before optimization,while the interaction,children's medication,adult medication,elderly medication,repeated medication,excessive daily dosage and freely customized warning items were more than those before optimization,and the differences were statistically significant(P<0.05);after optimization,the dosage range,in vitro compatibility,drug contraindications,adult medication,pregnancy medication,repeated medication,potassium ion monitoring and freely customized warning items in inpatients were more than those before optimization,the children's medication warning items was less than that before optimization,and the differences were statistically significant(P<0.05).After optimization,the proportion of medi
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