• Title/Summary/Keyword: 환자 재입실

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Risk Factors of Unplanned Readmission to Intensive Care Unit (중환자실 환자의 비계획적 재입실 위험 요인)

  • Kim, Yu Jeong;Kim, Keum Soon
    • Journal of Korean Clinical Nursing Research
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    • v.19 no.2
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    • pp.265-274
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    • 2013
  • Purpose: The aim of this study was to determine the risk factors contributed to unplanned readmission to intensive care unit (ICU) and to investigate the prediction model of unplanned readmission. Methods: We retrospectively reviewed the electronic medical records which included the data of 3,903 patients who had discharged from ICUs in a university hospital in Seoul from January 2011 to April 2012. Results: The unplanned readmission rate was 4.8% (n=186). The nine variables were significantly different between the unplanned readmission and no readmission groups: age, clinical department, length of stay at 1st ICU, operation, use of ventilator during 24 hours a day, APACHE II score at ICU admission and discharge, direct nursing care hours and Glasgow coma scale total score at 1st ICU discharge. The clinical department, length of stay at 1st ICU, operation and APACHE II score at ICU admission were the significant predictors of unplanned ICU readmission. The predictive model's area under the curve was .802 (p<.001). Conclusion: We identified the risk factors and the prediction model associated with unplanned ICU readmission. Better patient assessment tools and knowledge about risk factors could contribute to reduce unplanned ICU readmission rate and mortality.

The Risk Factors Related to Early Readmission to the Intensive Care Unit. (중환자실 조기 재입실 관련 위험요인)

  • Jang, Jin Nyoung;Lee, Yun Mi;Park, Hyo Jin;Lee, Hyeon Ju
    • Journal of Korean Critical Care Nursing
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    • v.12 no.1
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    • pp.36-45
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    • 2019
  • Purpose : The purpose of this study was to identify status and characteristics of patients who have been readmitted to ICU, and to analyze risk factors associated with the readmission to ICU within 48hours. Method: Data were collected from patient's electronic medical reports from one hospital in B city. Participants were 2,937 patients aged 18 years old or older admitted to the ICU. Data were analyzed using odd ratios (ORs) from multivariate logistic regressions. Results: 2.2% of the 2,937 patients were early readmitted to ICU. Risk factors for early readmission to ICU were existence of respiratory disease, use of mechanical ventilator, and duration of hospitalization (longer). Conclusion: The assessment on the respiratory system of the patient who will be discharged from the ICU was identified as an important nursing activity. Therefore, the respiratory system management and education should be actively conducted. In addition, early ICU readmission may be prevented and decreased if a link was built to share the information on patient condition between the ICU and general wards.

Case Control Study Identifying the Predictors of Unplanned Intensive Care Unit Readmission After Discharge (집중치료실 퇴실환자의 비계획성 재입실 예측 인자를 규명하기 위한 사례대조군 연구)

  • Park, Myoung Ok;Oh, Hyun Soo
    • Journal of Korean Critical Care Nursing
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    • v.11 no.3
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    • pp.45-57
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    • 2018
  • Purpose : This study was performed to identify the influencing factors of unplanned intensive care unit (ICU) readmission. Methods : The study adopted a Rretrospective case control cohort design. Data were collected from the electronic medical records of 844 patients who had been discharged from the ICUs of a university hospital in Incheon from June 2014 to December 2014. Results : The study found the unplanned ICU readmission rate was to be 6.4%(n=54). From the univariate analysis revealed that, major symptoms at $1^{st}$ ICU admission, severity at $1^{st}$ ICU admission (CPSCS and APACHE II), duration of applying ventilator application during $1^{st}$ ICU admission, severity at $1^{st}$ discharge from ICU (CPSCS, APACHE II, and GCS), and application of $FiO_2$ with oxygen therapy, implementation of sputum expectoration methods, and length of stay of ICU at $1^{st}$ ICU discharge were appeared to be significant; further, decision tree model analysis revealed that while only 4 variables (sputum expectoration methods, length of stay of ICU, $FiO_2$ with oxygen therapy at $1^{st}$ ICU discharge, and major symptoms at $1^{st}$ ICU admission) were shown to be significant. Conclusions : Since sputum expectoration method was the most important factor to predictor of unplanned ICU readmission, a assessment tool for the patients' capability of sputum expectoration needs to should be developed and implemented, and standardized ICU discharge criteria, including the factors identified from the by empirical evidences, might should be developed to decrease the unplanned ICU readmission rate.