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作 者:薛灏[1] 夏勇[1] 罗厚龙 李明洋 晏耀明[1] 纪玲[1] Xue Hao;Xia Yong;Luo Houlong;Li Mingyang;Yan Yaoming;Ji Ling(Department of Laboratory Medicine,Peking University Shenzhen Hospital,Shenzhen 518036,China)
出 处:《中华检验医学杂志》2024年第5期520-525,共6页Chinese Journal of Laboratory Medicine
摘 要:目的:通过检验前智慧化流程再造,以提高工作效率并减少差错。方法:收集北京大学深圳医院2021年12月至2023年2月门诊的肿瘤和感染标志物检验样本,通过集成样本传输、样本分拣与二次转运及实验室自动化系统,并实现全流程信息化监控。比较检验前智慧化流程自动识别的再造前后的样本人工介入节点、样本采集-检测、采集-报告的周转时间(TAT)、智能预稀释比例、自动识别出检验前差错数量,评估流程再造的效果。采用卡方检验、Fisher精确概率法、Mann-Whitney U检验进行统计学分析。 结果:在实施智能化流程再造后,人工介入节点从原先的13个减少至2个;门诊患者肿瘤标志物一阶段改造后,采集-报告TAT中位数从185(141,242)min降至137(102,183)min( Z=-54.932, P<0.001),二阶段改造后,采集-报告TAT中位数从137(102,183)min降至100(64,150)min( Z=-61.346, P<0.001);感染标志物一阶段改造后,采集-报告TAT中位数从392(282,1386)min降至229(176,323)min( Z=-68.636, P<0.001),二阶段改造后,采集-报告TAT中位数从229(176,323)min降至160(110,236)min( Z=-62.15, P<0.001)。 结论:检验前智慧化流程再造能够优化工作流程、提升效率、减少差错。Objective To improve work efficiency and reduce errors through intelligent pre-analytical process reengineering.Methods Tumor and infection marker test samples from outpatients at Peking University Shenzhen Hospital from December 2021 to February 2023 were collected.The process was integrated with sample transportation,sample sorting and secondary transfer,and laboratory automation systems,while achieving full-process information monitoring.The number of manual intervention nodes,the turnaround time(TAT)from sample collection to testing and from collection to reporting,the proportion of intelligent pre-dilution,and the number of pre-analytical errors automatically identified were compared before and after the intelligent pre-analytical process reengineering to evaluate the effect of the reengineering.Chi-square test,Fisher′s exact probability method,and Mann-Whitney U test were used for statistical analysis.Results After implementing the intelligent process reengineering,the number of manual intervention nodes has been reduced from 13 to 2.For outpatient tumor marker samples,after the first stage of reengineering,the median TAT from collection to reporting decreased from 185(141,242)min to 137(102,183)min(Z=-54.932,P<0.001).After the second stage of reengineering,the median TAT from collection to reporting further decreased from 137(102,183)min to 100(64,150)min(Z=-61.346,P<0.001).For infection marker samples,after the first stage of reengineering,the median TAT from collection to reporting decreased from 392(282,1386)min to 229(176,323)min(Z=-68.636,P<0.001).After the second stage of reengineering,the median TAT from collection to reporting further decreased from 229(176,323)min to 160(110,236)min(Z=-62.15,P<0.001).Conclusion Intelligent pre-analytical process reengineering can optimize workflows,improve efficiency,and reduce errors.
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