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The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study

Little is known about hospital readmission for patients with diabetes in China. We aimed to assess the temporal pattern, risk factors, and variations of all-cause readmission among hospitalized patients with diabetes in Tianjin, China, from 2008 to 2013. The Tianjin Basic Medical Insurance Register...

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Autores principales: Liu, Xiaoqian, Guo, Yuting, Li, Dandan, Cui, Zhuang, Liu, Yuanyuan, Li, Changping, Ma, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662355/
https://www.ncbi.nlm.nih.gov/pubmed/29049189
http://dx.doi.org/10.1097/MD.0000000000007953
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author Liu, Xiaoqian
Guo, Yuting
Li, Dandan
Cui, Zhuang
Liu, Yuanyuan
Li, Changping
Ma, Jun
author_facet Liu, Xiaoqian
Guo, Yuting
Li, Dandan
Cui, Zhuang
Liu, Yuanyuan
Li, Changping
Ma, Jun
author_sort Liu, Xiaoqian
collection PubMed
description Little is known about hospital readmission for patients with diabetes in China. We aimed to assess the temporal pattern, risk factors, and variations of all-cause readmission among hospitalized patients with diabetes in Tianjin, China, from 2008 to 2013. The Tianjin Basic Medical Insurance Register System database was used to identify discharged patients with diabetes from 2008 to 2013. The influential factors and trends of rehospitalization were analyzed for 30-, 60- and 90-day predicted readmission rates. The Blinder–Oaxaca decomposition was used to explain the readmission variations between 2008 and 2013. The long stay-time at the index hospitalization is a shared risk factor for readmission at 30, 60, and 90 days each year. The 90-day predicted readmission rates were the highest for each year (all P < .001). The adjusted readmission rates generally decreased by year (all P < .001), except for at the 90-day interval, which decreased in 2010 and slightly increased in 2013 (from 7.47% in 2012 to 7.65% in 2013). If the patients had been readmitted to the hospital in 2013 and the only changes that had occurred since 2008 were observable characteristics, then the readmission rates would have decreased by 0.84%, 0.27%, and 0.18% at 30, 60, and 90 days, respectively. The potential policy changes decreased the readmission rates at 1.35%, 2.01%, and 1.04% for the 3 intervals, respectively. Identifying targeted factors for the decrease in readmission rates may help to control readmission, particularly for long-interval patients.
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spelling pubmed-56623552017-11-21 The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study Liu, Xiaoqian Guo, Yuting Li, Dandan Cui, Zhuang Liu, Yuanyuan Li, Changping Ma, Jun Medicine (Baltimore) 6600 Little is known about hospital readmission for patients with diabetes in China. We aimed to assess the temporal pattern, risk factors, and variations of all-cause readmission among hospitalized patients with diabetes in Tianjin, China, from 2008 to 2013. The Tianjin Basic Medical Insurance Register System database was used to identify discharged patients with diabetes from 2008 to 2013. The influential factors and trends of rehospitalization were analyzed for 30-, 60- and 90-day predicted readmission rates. The Blinder–Oaxaca decomposition was used to explain the readmission variations between 2008 and 2013. The long stay-time at the index hospitalization is a shared risk factor for readmission at 30, 60, and 90 days each year. The 90-day predicted readmission rates were the highest for each year (all P < .001). The adjusted readmission rates generally decreased by year (all P < .001), except for at the 90-day interval, which decreased in 2010 and slightly increased in 2013 (from 7.47% in 2012 to 7.65% in 2013). If the patients had been readmitted to the hospital in 2013 and the only changes that had occurred since 2008 were observable characteristics, then the readmission rates would have decreased by 0.84%, 0.27%, and 0.18% at 30, 60, and 90 days, respectively. The potential policy changes decreased the readmission rates at 1.35%, 2.01%, and 1.04% for the 3 intervals, respectively. Identifying targeted factors for the decrease in readmission rates may help to control readmission, particularly for long-interval patients. Wolters Kluwer Health 2017-10-20 /pmc/articles/PMC5662355/ /pubmed/29049189 http://dx.doi.org/10.1097/MD.0000000000007953 Text en Copyright © 2017 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nd/4.0 This is an open access article distributed under the Creative Commons Attribution-NoDerivatives License 4.0, which allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author. http://creativecommons.org/licenses/by-nd/4.0
spellingShingle 6600
Liu, Xiaoqian
Guo, Yuting
Li, Dandan
Cui, Zhuang
Liu, Yuanyuan
Li, Changping
Ma, Jun
The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title_full The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title_fullStr The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title_full_unstemmed The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title_short The prevalence and long-term variation of hospital readmission for patients with diabetes in Tianjin, China: A cross-sectional study
title_sort prevalence and long-term variation of hospital readmission for patients with diabetes in tianjin, china: a cross-sectional study
topic 6600
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662355/
https://www.ncbi.nlm.nih.gov/pubmed/29049189
http://dx.doi.org/10.1097/MD.0000000000007953
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