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Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study

BACKGROUND: Hospital readmissions are serious and costly events, and readmission rates are considered to be an indicator of quality in health care management. Several models to identify patients at risk of unplanned readmissions have been developed in Western countries, but little is known about the...

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Autores principales: Tan, Shu Yun, Low, Lian Leng, Yang, Yong, Lee, Kheng Hock
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850678/
https://www.ncbi.nlm.nih.gov/pubmed/24074454
http://dx.doi.org/10.1186/1472-6963-13-366
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author Tan, Shu Yun
Low, Lian Leng
Yang, Yong
Lee, Kheng Hock
author_facet Tan, Shu Yun
Low, Lian Leng
Yang, Yong
Lee, Kheng Hock
author_sort Tan, Shu Yun
collection PubMed
description BACKGROUND: Hospital readmissions are serious and costly events, and readmission rates are considered to be an indicator of quality in health care management. Several models to identify patients at risk of unplanned readmissions have been developed in Western countries, but little is known about their performance in other countries. This paper reports the possible utility of one such model developed in Canada, the LACE index, in patients in a tertiary hospital in Singapore. METHODS: We used administrative data from Singapore General Hospital for patients admitted between 1st January 2006 and 31st December 2010. Data such as demographic and clinical data including disease codes were extracted. The patient cohort was divided into two groups with a LACE index of 10 as the cutoff. Multivariate logistic regression analysis models were used to compare the outcomes between the two groups of patients with adjustment for age, sex, ethnicity, year of discharge, intensive care unit admission, and admission ward class. RESULTS: Overall, 127 550 patients were eligible for analysis. Patients with a LACE index ≥ 10 had a higher risk of 30-day unplanned readmission after index discharge (odds ratio [OR]: 4.37; 95% confidence interval [CI]: 4.18-4.57). After adjustment, the risk remained significant (OR: 4.88; 95% CI: CI 4.57-5.22). The C-statistic for the adjusted model was 0.70 (P < 0.001). Similar results were shown for 90-day unplanned readmission and emergency visits after the same adjustment. CONCLUSION: The use of the LACE index may have significant application in identifying medical patients at high risk of readmission and visits to the Emergency Department in Singapore.
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spelling pubmed-38506782013-12-05 Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study Tan, Shu Yun Low, Lian Leng Yang, Yong Lee, Kheng Hock BMC Health Serv Res Research Article BACKGROUND: Hospital readmissions are serious and costly events, and readmission rates are considered to be an indicator of quality in health care management. Several models to identify patients at risk of unplanned readmissions have been developed in Western countries, but little is known about their performance in other countries. This paper reports the possible utility of one such model developed in Canada, the LACE index, in patients in a tertiary hospital in Singapore. METHODS: We used administrative data from Singapore General Hospital for patients admitted between 1st January 2006 and 31st December 2010. Data such as demographic and clinical data including disease codes were extracted. The patient cohort was divided into two groups with a LACE index of 10 as the cutoff. Multivariate logistic regression analysis models were used to compare the outcomes between the two groups of patients with adjustment for age, sex, ethnicity, year of discharge, intensive care unit admission, and admission ward class. RESULTS: Overall, 127 550 patients were eligible for analysis. Patients with a LACE index ≥ 10 had a higher risk of 30-day unplanned readmission after index discharge (odds ratio [OR]: 4.37; 95% confidence interval [CI]: 4.18-4.57). After adjustment, the risk remained significant (OR: 4.88; 95% CI: CI 4.57-5.22). The C-statistic for the adjusted model was 0.70 (P < 0.001). Similar results were shown for 90-day unplanned readmission and emergency visits after the same adjustment. CONCLUSION: The use of the LACE index may have significant application in identifying medical patients at high risk of readmission and visits to the Emergency Department in Singapore. BioMed Central 2013-09-29 /pmc/articles/PMC3850678/ /pubmed/24074454 http://dx.doi.org/10.1186/1472-6963-13-366 Text en Copyright © 2013 Tan et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tan, Shu Yun
Low, Lian Leng
Yang, Yong
Lee, Kheng Hock
Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title_full Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title_fullStr Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title_full_unstemmed Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title_short Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study
title_sort applicability of a previously validated readmission predictive index in medical patients in singapore: a retrospective study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3850678/
https://www.ncbi.nlm.nih.gov/pubmed/24074454
http://dx.doi.org/10.1186/1472-6963-13-366
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