Intensive care readmission: A contemporary review of the literature

Elliott, Malcolm; Worrall‐Carter, Linda; Page, Karen

doi:10.1016/j.iccn.2013.10.005

Cited by 47 publications

(36 citation statements)

References 80 publications

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“…Patients readmitted to the ICU experience more adverse events, with in-hospital mortality rates up to six times higher than non-readmitted patients [5]. Readmitted patients reduce ICU bed availability and it is possible that ICU facilities could be used more efficiently if ICU readmissions could be prevented [1–4].…”

Section: Introductionmentioning

confidence: 99%

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Sluisveld¹,

Bakhshi‐Raiez

Keizer

et al. 2017

BMC Health Serv Res

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BackgroundVariation in intensive care unit (ICU) readmissions and in-hospital mortality after ICU discharge may indicate potential for improvement and could be explained by ICU discharge practices. Our objective was threefold: (1) describe variation in rates of ICU readmissions within 48 h and post-ICU in-hospital mortality, (2) describe ICU discharge practices in Dutch hospitals, and (3) study the association between rates of ICU readmissions within 48 h and post-ICU in-hospital mortality and ICU discharge practices.MethodsWe analysed data on 42,040 admissions to 82 (91.1%) Dutch ICUs in 2011 from the Dutch National Intensive Care Evaluation (NICE) registry to describe variation in standardized ICU readmission and post-ICU mortality rates using funnel-plots. We send a questionnaire to all Dutch ICUs. 75 ICUs responded and their questionnaire data could be linked to 38,498 admissions in the NICE registry. Generalized estimation equations analyses were used to study the association between ICU readmissions and post-ICU mortality rates and the identified discharge practices, i.e. (1) ICU discharge criteria; (2) bed managers; (3) early discharge planning; (4) step-down facilities; (5) medication reconciliation; (6) verbal and written handover; (7) monitoring of post-ICU patients; and (8) consulting ICU nurses. In all analyses, the outcomes were corrected for patient-related confounding factors.ResultsThe standardized rate of ICU readmissions varied between 0.14 and 2.67 and 20.8% of the hospitals fell outside the 95% control limits and 3.6% outside the 99.8% control limits. The standardized rate of post-ICU mortality varied between 0.07 and 2.07 and 17.1% of the hospitals fell outside the 95% control limits and 4.9% outside the 99.8% control limits. We could not demonstrate an association between the eight ICU discharge practices and rates of ICU readmissions or post-ICU in-hospital mortality. Implementing a higher number of ICU discharge practices was also not associated with better patient outcomes.ConclusionsWe found both variation in patient outcomes and variation in ICU discharge practices between ICUs. However, we found no association between discharge practices and rates of ICU readmissions or post-ICU mortality. Further research is necessary to find factors, which may influence these patient outcomes, in order to improve quality of care.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2234-z) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Sluisveld¹,

Bakhshi‐Raiez

Keizer

et al. 2017

BMC Health Serv Res

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“…According to a review of 35 evidence-based medical studies, Elliot et al 22 found that subjects readmitted to the ICU were generally older, diagnosed with more comorbidities, showed higher disease severity, and previously stayed at the ICU longer compared with other subjects. Table 3).…”

Section: Influence Of Health Status On Readmissionmentioning

confidence: 99%

“…Previous studies have indicated that the factors causing subject readmission may be related to the care standards of the extended-care units. 22 …”

Section: Influence Of Length Of Stay In the Icumentioning

confidence: 99%

The Risk and Related Factors for Readmission to an ICU Within 7 Days in Mechanically Ventilated Subjects—A Nationwide Population-Based Cohort Study

Chu

Liu²,

Shih

et al. 2015

Respir Care

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BACKGROUND: Readmission of mechanically ventilated patients to an ICU within 7 d reflects not only patient safety but also the quality of care of the ICU. This study aimed to investigate the risk and related factors for readmission to an ICU within 7 d in mechanically ventilated subjects. METHODS: A total of 658,452 mechanically ventilated subjects discharged from an ICU whose age was > 17 y old were obtained from the Taiwan National Health Insurance Research Database for the period from January 1, 2005, to December 31, 2011. The study applied a generalized estimating equation logistic regression model to explore whether the mechanically ventilated subjects were readmitted within 7 d or not and the related factors. RESULTS: A total of 29,657 subjects were readmitted to the ICU within 7 d; the total readmission rate was 4.5%. Also, 64.8% of the subjects with the same diagnosis were returned to the ICU within 7 d. Generalized estimating equation logistic regression model results showed that the factors related to higher risk of readmission were male sex, old age, higher comorbidity score, complications (eg, pneumothorax, subcutaneous emphysema, pneumonia, oxygen toxicity, pulmonary embolism, or pulmonary edema), use of a private hospital ICU, ICU stay >21 d, transfer to a respiratory care center and respiratory care ward, and subsequent transfer to the regional hospital or district hospital. CONCLUSIONS: The risk and related factors of a mechanically ventilated subject whose age is > 17 y old being readmitted to the ICU within 7 d include subject characteristics, health status, hospital attributes, and the length of ICU stay. Therefore, higher risk subjects should receive attention and assessment before transfer or discharge from the ICU to prevent readmission.

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“…Of particular concern is that readmitted patients during the same hospitalization have much worse prognoses than those not readmitted [1]. Patients readmitted have a increased risk of death, length of stay and higher costs [2].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Decision Tree to Predict Readmissions in Intensive Care Unit

Silva

Vieira

Sousa

2015

Lecture Notes in Electrical Engineering

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Abstract. Patients readmissions to Intensive Care Unit (ICU) are introduced as a problem associated with increased mortality, morbidity and costs, which complicates the performance of a good clinical management and medical diagnosis. The aim of this work is to use the fuzzy decision tree using the axiomatic fuzzy set (AFS) theory in a type of coherence membership function to apply in the risk of readmission. Three fitness functions are used to obtain the threshold using different assessment measures: accuracy; area under the curve ROC (AUC); and Cohen's kappa coefficient. The results for this problem data demonstrated that the model using fitness function with Cohen's kappa coefficient obtains better performance than the others fitness functions.

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Intensive care readmission: A contemporary review of the literature

Cited by 47 publications

References 80 publications

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

Variation in rates of ICU readmissions and post-ICU in-hospital mortality and their association with ICU discharge practices

The Risk and Related Factors for Readmission to an ICU Within 7 Days in Mechanically Ventilated Subjects—A Nationwide Population-Based Cohort Study

Fuzzy Decision Tree to Predict Readmissions in Intensive Care Unit

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