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Predictors of Early and Late Unplanned Intensive Care Unit Readmission: A Retrospective Cohort Study
Youn-Jung Son1, Gi-Ock Kim2, Yun Mi Lee3
1Lambda Alpha-at-Large, Professor, Red Cross College of Nursing, Chung-Ang University, Seoul, Republic of Korea.
Insights
Reducing intensive care unit (ICU) readmissions requires understanding risk factors. Early readmissions are linked to ward admission and prolonged mechanical ventilation, while late readmissions involve ward admission, tracheostomy, extended ventilation, and renal replacement therapy.
Area of Science:
- Critical Care Medicine
- Health Services Research
Background:
- Intensive care unit (ICU) readmission is a key indicator of critical care quality.
- Reducing unplanned ICU readmissions can improve patient outcomes and optimize resource allocation.
- Limited data exist on the specific predictors of unplanned ICU readmissions.
Purpose of the Study:
- To identify risk factors for unplanned ICU readmission.
- To differentiate predictors for early (within 48 hours) and late (after 48 hours) readmissions.
Main Methods:
- Retrospective cohort study design.
- Analysis of electronic medical records from 739 patients in a tertiary academic medical center's ICU.
- Multivariable multinomial logistic regression to identify predictors of ICU readmission.
Main Results:
- Overall readmission rate was 8.9% (1.8% early, 7.1% late).
- Early readmission predictors: ICU admission from ward (OR=4.14) and mechanical ventilation >14 days (OR=13.25).
- Late readmission predictors: ICU admission from ward (OR=2.69), tracheostomy (OR=3.58), mechanical ventilation >14 days (OR=4.77), and continuous renal replacement therapy (OR=4.57).
Conclusions:
- Specific risk factors predict early and late ICU readmissions.
- Clinical judgment, team communication, and institutional support are crucial for preventing readmissions.
- Prospective multicenter studies are needed to validate findings and explore post-ICU outcomes.
Purpose:
Intensive care unit (ICU) readmission is considered one of the major quality indicators of critical care. Reducing ICU readmission can improve patients' outcomes and optimize health resources, but there are limited data on the predictors of unplanned ICU readmission. This study aimed to identify the risk factors associated with unplanned ICU readmission within 48 hr (early) and after 48 hr (late) from ICU discharge.
Design:
Retrospective cohort study.
Methods:
Data were collected from patients' electronic medical records in a 24-bed medical ICU at a tertiary academic medical center in Busan, South Korea. Among all the patients admitted to the medical ICU (n = 1,033) between January 2015 and December 2017, 739 eligible patients were analyzed. A multivariable multinomial logistic regression model was conducted to identify predictors of ICU readmission.
Findings:
Out of the 739 patients analyzed, 66 (8.9%) were readmitted to the medical ICU: 13 (1.8%) as early readmission and 53 (7.1%) as late readmission. Two significant predictors were identified for early readmission: ICU admission from the ward (odds ratio [OR] = 4.14; 95% confidence interval [CI] 1.25, 13.67) and mechanical ventilation support >14 days (OR = 13.25; 95% CI 1.78, 98.89). For late ICU admission, there were four risk factors: ICU admission from the ward (OR = 2.69; 95% CI 1.44, 5.05), tracheostomy placement (OR = 3.58; 95% CI 1.49, 8.59), mechanical ventilation support >14 days (OR = 4.77; 95% CI 1.67, 13.63), and continuous renal replacement therapy (OR = 4.57; 95% CI 2.42, 8.63).
Conclusions:
To prevent unplanned ICU readmission in patients at high risk, it is necessary to investigate further the role of clinical judgment and communication within the ICU clinical team and institutional-level support regarding ICU readmission events.
Clinical Relevance:
Both ICU nurses and nurses in post-ICU settings should be aware of the potential risk factors associated with early and late ICU readmission. Predictors and readmission strategies may be different for early and late readmissions. Prospective multicenter studies are needed to examine how these factors influence post-ICU outcomes.
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