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Identifying the relationship between unstable vital signs and intensive care unit (ICU) readmissions: an analysis of 10-year of hospital ICU readmissions

机译:确定不稳定的生命体征与重症监护股(ICU)重建之间的关系:对10年医院ICU阅览室的分析

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Advanced healthcare information systems capture extensive electronic healthcare records (EHR) to provide accurate healthcare delivery and make informed clinical and management decisions. EHR also include records of Intensive Care Unit (ICU) admissions, discharges, readmissions and more. This study aims to investigate trends and patterns from electronically recorded vital signs and identify the relationship between vital signs and ICU readmissions. After appropriate ethics approvals and permissions, we obtained access to the MIMIC-III dataset. A total of 150 patient data has been selected from the MIMIC-III dataset to evaluate the vital signs patterns, which included heart rate, respiratory rate, temperature for patients admitted twice in the ICU. Statistical analysis was conducted to identify the key patterns associated with the vital signs of the selected patient samples. The study findings indicate that the mean value of heart rate and respiratory rate was within the normal range for all incidents. However, there was a small difference between the readmission-day of the vital signs compared with the previous admission recordings. The finding also suggests that hospital length of stay (LOS) for patients was high for the second admission compared to the first admission. We identified a key relationship between the vital signs and ICU readmissions, it is evident that discharges with unstable vitals are directly linked to readmissions. Additionally, it is also observed that the LOS varies depending on the stability of the vital signs. In future, a larger sample with more variables are required, such as modifiable (medications, procedures, room temperature, discharge time) and non-modifiable (age, ethnicity, family history) which could explain the significance of longer LOS and its impact on patient-condition, readmission and mortality rate.
机译:先进的医疗保健信息系统捕获广泛的电子医疗保健记录(EHR),以提供准确的医疗保健交付,并提供明智的临床和管理决策。 EHR还包括重症监护单位(ICU)录取,排放,入院等记录。本研究旨在调查电子记录生命体征的趋势和模式,并确定生命体征和ICU阅内克之间的关系。在适当的道德批准和权限之后,我们获得了对模拟-III数据集的访问权限。从MIMIC-III数据集中选择了总共150个患者数据,以评估含有心率,呼吸速率,在ICU中接受两次患者的心率,呼吸率,温度的生命体征模式。进行统计分析以鉴定与所选患者样品的生命体征相关的关键模式。研究结果表明,心率和呼吸速率的平均值在所有事件的正常范围内。然而,与先前的入场记录相比,生命体征的再访日之间存在较小的差异。该发现还表明,与第一次入场相比,第二次入场的患者的住院时间(LOS)很高。我们确定了生命体征和ICU再入院之间的关键关系,显然具有不稳定的生命权的排放与入伍直接相关。另外,还观察到,LOS根据生命体征的稳定性而变化。未来,需要具有更多变量的更大样本,例如可修改的(药物,程序,室温,放电时间)和不可改志性(年龄,种族,家族史),其可以解释更长的洛杉矶及其影响的重要性患者条件,入院和死亡率。

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