• 中国科学论文统计源期刊
  • 中国科技核心期刊
  • 美国化学文摘(CA)来源期刊
  • 日本科学技术振兴机构数据库(JST)

临床输血与检验 ›› 2021, Vol. 23 ›› Issue (1): 79-82.DOI: 10.3969/j.issn.1671-2587.2021.01.020

• 临床输血 • 上一篇    下一篇

基于信息化系统输血样本配送管理模式建立与应用研究

李丽玮, 钟宁, 李兴龙, 杨燕, 于建, 李志强   

  1. 200233 上海市交通大学附属第六人民医院
  • 收稿日期:2020-05-16 发布日期:2021-02-22
  • 通讯作者: 李志强,男,浙江绍兴人,主任医师,硕士研究生导师,主要从事血液系统疾病诊治与临床输血反应研究,(E-mail)kcb039@126.com。
  • 作者简介:李丽玮(1987-)女,江苏扬州人,主管技师,硕士,主要从事临床输血血型血清学与分子生物学相关研究,(E-mail)1527352289@qq.com。
  • 基金资助:
    *本课题受上海市科学技术委员会科研计划项目(No.17DZ2200800)资助

Research on Establishment and Application of Blood Transfusion Sample Distribution Management Model Based on Information System

LI Li-wei, ZHONG Ning, LI Xing-long, et al   

  1. Department of Blood Transfusion, The Sixth People's Hospital Affiliated to Shanghai Jiaotong University 200233
  • Received:2020-05-16 Published:2021-02-22

摘要: 目的 建立输血样本精准配送信息化系统管理模式,确保输血安全。方法 应用患者信息系统和临床输血信息管理系统联网动态跟踪,分别观察每月平均平诊、急诊(抢救)输血样本配送时间,发生样本配送错误和漏送例次数。结果 2016~2017年未实施信息联网配送、2018~2019年实施信息联网动态跟踪配送每月平均平诊输血样本时间分别为(45.0±3.1)min、(40.0±4.2)min、(20.0±3.5)min、(19.0±3.3) min,随年份变化差异有统计学意义(F=170.95,P<0.05);而2016~2017年未实施信息联网配送、2018~2019年实施信息联网动态跟踪配送每月平均急诊(抢救)输血样本时间分别为(16.0±2.4)min、(15.0±2.1)min、(10.0±3.1)min、(9.0±1.8)min,随年份变化差异有统计学意义(F=25.44,P<0.05)。2016年与2017年未实施信息联网动态跟踪输血样本发生配送错误、漏送和滞留数分别为286例次(占7.77‰)、269例次(占6.90‰);而2018年与2019年通过建立信息化系统实施精准配送输血样本均未发生配送错误、漏送和滞留,相互间分别比较差异有统计学意义(χ2=613.49,P<0.05)。结论 构建输血样本信息联网动态跟踪管理在提高配送精准度的同时提高工作效能,可实现临床输血工作质量过程控制。

关键词: 临床输血, 样本管理, 信息化

Abstract: Objective To ensure the safety of blood transfusion , we established an information system management model for the precise distribution of blood transfusion samples. Methods The patient information system and the clinical blood transfusion information management system were used to dynamically track the average delivery time of blood transfusion samples in ordinary and emergency (rescue) departments monthly, and the number of sample delivery errors and missed cases were observed. Results In 2016~2017, information network distribution was not implemented. In 2018~2019, information network dynamic tracking and distribution was implemented. The monthly average blood transfusion sample time for ordinary consultation was 45.0±3.1 min, 40.0±4.2 min, 20.0±3.5 min, 19.0±3.3 min, respectively. There is a statistical difference with the year (F=170.95, P<0.05); while the information network distribution was not implemented in 2016-2017, and the information network dynamic tracking and distribution was implemented in 2018~2019. The monthly average emergency (rescue) blood transfusion sample time was 16.0±2.4 minutes, 15.0±2.1 minutes, 10.0±3.1 minutes, 9.0±1.8 minutes, respectively, there were also statistical differences with the year (F=25.44, P<0.05). In 2016 and 2017, the information network was not implemented to dynamically track the number of delivery errors, missed deliveries and detentions of blood transfusion samples were 286 cases (accounting for 7.77‰) and 269 cases (accounting for 6.90‰) respectively; the establishment was applied in 2018 and 2019, The accurate distribution of blood transfusion samples in the information system did not cause any delivery error, missed delivery and detention, and there were statistical differences between them (χ2=613.49, P<0.05). Conclusion The establishment of dynamic tracking management of blood transfusion sample information network can improve the accuracy of distribution and work efficiency, and also realize the quality process control of clinical blood transfusion work.

Key words: Blood Transfusion, Sample management, Informatization

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