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Early warning of nursing risk based on patient electronic medical record information

机译:基于患者电子医疗记录信息的护理风险预警

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In order to study the nursing risk warning of patients’ electronic medical record (EMR) information, data of 200 cases of patient from Eastern Medical District of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital is selected. The Logistic regression model and nursing risk warning information system are used to calculate the death probability of the recovered patients 24 h before discharge and 24 h before the death of the patients. The predictive ability of the system is verified, and incidence of infusion, blood transfusion, surgical patient handover, blood sample collection nursing risk, and corresponding indirect care hours before and after the use of nursing risk warning are compared. The probability of death of the recovered patients within 24 h before discharge is less than 0.5, and the death probability of the dead patients before the death of 24 h is greater than 0.5. After the nursing risk warning is used, the infusion, surgical patient handover, and incidence of blood sample collection nursing risk are significantly lower than those before using the nursing risk warning and the difference is statistically significant. The indirect nursing hours of infusion, blood transfusion, surgical patient handover, and blood sample collection are significantly lower than those before using the nursing risk warning, and the difference is statistically significant. Therefore, the predictive ability of the patient's EMR information risk warning system has important reference value in clinical nursing, which can significantly reduce the incidence of infusion, surgical patient handover, and blood sample collection and nursing risk, reduce the infusion, blood transfusion, surgical patient handover, and indirect nursing hours for collecting blood samples, and improve the quality and efficiency of hospital diagnosis and treatment.
机译:为了研究患者电子医疗记录(EMR)信息的护理风险警告,选择了来自四川医学科学院和四川省人民医院东部医科区患者200例患者的数据。 Logistic回归模型和护理风险警告信息系统用于计算在排出前24小时的回收患者的死亡概率和24小时患者死亡前。比较了系统的预测能力,并进行了染色,输血,手术患者切换,血液样本收集护理风险,以及在使用护理风险警告之前和之后的发生率。在出院前24小时内恢复患者死亡的概率小于0.5,死亡患者死亡概率大于0.5。在使用护理风险警告后,使用输液,外科患者切换和血液样品收集护理风险的发病率明显低于使用护理风险警告,并且差异是统计学意义。输液的间接护理小时,输血,手术患者切换和血液样品收集显着低于使用护理风险警告之前的血液样品收集,差异是统计学意义。因此,患者EMR信息风险警告系统的预测能力在临床护理中具有重要的参考价值,可以显着降低输注,手术患者切换和血液样本收集和护理风险的发生率,降低输注,输血,外科患者切换,以及用于收集血液样本的间接护理时间,提高医院诊断和治疗的质量和效率。

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