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A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care
INTRODUCTION: We sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU. METHODS: We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as wel...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4312433/ https://www.ncbi.nlm.nih.gov/pubmed/25551448 http://dx.doi.org/10.1186/s13054-014-0715-6 |
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author | Hosein, F Shaun Roberts, Derek J Turin, Tanvir Chowdhury Zygun, David Ghali, William A Stelfox, Henry T |
author_facet | Hosein, F Shaun Roberts, Derek J Turin, Tanvir Chowdhury Zygun, David Ghali, William A Stelfox, Henry T |
author_sort | Hosein, F Shaun |
collection | PubMed |
description | INTRODUCTION: We sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU. METHODS: We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality. RESULTS: The analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics. CONCLUSIONS: Using current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward. |
format | Online Article Text |
id | pubmed-4312433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43124332015-02-01 A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care Hosein, F Shaun Roberts, Derek J Turin, Tanvir Chowdhury Zygun, David Ghali, William A Stelfox, Henry T Crit Care Research INTRODUCTION: We sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU. METHODS: We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality. RESULTS: The analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics. CONCLUSIONS: Using current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward. BioMed Central 2014-12-31 2014 /pmc/articles/PMC4312433/ /pubmed/25551448 http://dx.doi.org/10.1186/s13054-014-0715-6 Text en © Hosein et al.; licensee BioMed Central. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Hosein, F Shaun Roberts, Derek J Turin, Tanvir Chowdhury Zygun, David Ghali, William A Stelfox, Henry T A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title | A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title_full | A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title_fullStr | A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title_full_unstemmed | A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title_short | A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
title_sort | meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4312433/ https://www.ncbi.nlm.nih.gov/pubmed/25551448 http://dx.doi.org/10.1186/s13054-014-0715-6 |
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