| 집중치료실 퇴실환자의 비계획성 재입실 예측 인자를 규명하기 위한 사례대조군 연구 |
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박명옥, 오현수 |
1인하대학교 간호학과
2인하대학교 간호학과 |
| Case Control Study Identifying the Predictors of Unplanned Intensive Care Unit Readmission After Discharge |
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Myoung Ok Park, Hyun Soo Oh |
1Doctoral Candidate, Department of Nursing, Inha University, Incheon, Korea. poohgirl98@hanmail.net
2Professor, Department of Nursing, Inha University, Incheon, Korea. |
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| Abstract |
PURPOSE
This study was performed to identify the influencing factors of unplanned intensive care unit (ICU) readmission.
METHOD
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 APACHEII), duration of applying ventilator application during 1(st) ICU admission, severity at 1(st) discharge from ICU (CPSCS, APACHEII, and GCS), and application of FiO₂ 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, FiO₂ with oxygen therapy at 1(st) ICU discharge, and major symptoms at 1(st) ICU admission) were shown to be significant.
CONCLUSION
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. |
| Key Words:
Intensive care unit, Readmission, Decision tree model |
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