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The number of discharge medications predicts thirty-day hospital readmission: a cohort study

BACKGROUND: Hospital readmission occurs often and is difficult to predict. Polypharmacy has been identified as a potential risk factor for hospital readmission. However, the overall impact of the number of discharge medications on hospital readmission is still undefined. METHODS: To determine whethe...

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Autores principales: Picker, David, Heard, Kevin, Bailey, Thomas C., Martin, Nathan R., LaRossa, Gina N., Kollef, Marin H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512093/
https://www.ncbi.nlm.nih.gov/pubmed/26202163
http://dx.doi.org/10.1186/s12913-015-0950-9
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author Picker, David
Heard, Kevin
Bailey, Thomas C.
Martin, Nathan R.
LaRossa, Gina N.
Kollef, Marin H.
author_facet Picker, David
Heard, Kevin
Bailey, Thomas C.
Martin, Nathan R.
LaRossa, Gina N.
Kollef, Marin H.
author_sort Picker, David
collection PubMed
description BACKGROUND: Hospital readmission occurs often and is difficult to predict. Polypharmacy has been identified as a potential risk factor for hospital readmission. However, the overall impact of the number of discharge medications on hospital readmission is still undefined. METHODS: To determine whether the number of discharge medications is predictive of thirty-day readmission using a retrospective cohort study design performed at Barnes-Jewish Hospital from January 15, 2013 to May 9, 2013. The primary outcome assessed was thirty-day hospital readmission. We also assessed potential predictors of thirty-day readmission to include the number of discharge medications. RESULTS: The final cohort had 5507 patients of which 1147 (20.8 %) were readmitted within thirty days of their hospital discharge date. The number of discharge medications was significantly greater for patients having a thirty-day readmission compared to those without a thirty-day readmission (7.2 ± 4.1 medications [7.0 medications (4.0 medications, 10.0 medications)] versus 6.0 ± 3.9 medications [6.0 medications (3.0 medications, 9.0 medications)]; P < 0.001). There was a statistically significant association between increasing numbers of discharge medications and the prevalence of thirty-day hospital readmission (P < 0.001). Multiple logistic regression identified more than six discharge medications to be independently associated with thirty-day readmission (OR, 1.26; 95 % CI, 1.17–1.36; P = 0.003). Other independent predictors of thirty-day readmission were: more than one emergency department visit in the previous six months, a minimum hemoglobin value less than or equal to 9 g/dL, presence of congestive heart failure, peripheral vascular disease, cirrhosis, and metastatic cancer. A risk score for thirty-day readmission derived from the logistic regression model had good predictive accuracy (AUROC = 0.661 [95 % CI, 0.643–0.679]). CONCLUSIONS: The number of discharge medications is associated with the prevalence of thirty-day hospital readmission. A risk score, that includes the number of discharge medications, accurately predicts patients at risk for thirty-day readmission. Our findings suggest that relatively simple and accessible parameters can identify patients at high risk for hospital readmission potentially distinguishing such individuals for interventions to minimize readmissions.
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spelling pubmed-45120932015-07-24 The number of discharge medications predicts thirty-day hospital readmission: a cohort study Picker, David Heard, Kevin Bailey, Thomas C. Martin, Nathan R. LaRossa, Gina N. Kollef, Marin H. BMC Health Serv Res Research Article BACKGROUND: Hospital readmission occurs often and is difficult to predict. Polypharmacy has been identified as a potential risk factor for hospital readmission. However, the overall impact of the number of discharge medications on hospital readmission is still undefined. METHODS: To determine whether the number of discharge medications is predictive of thirty-day readmission using a retrospective cohort study design performed at Barnes-Jewish Hospital from January 15, 2013 to May 9, 2013. The primary outcome assessed was thirty-day hospital readmission. We also assessed potential predictors of thirty-day readmission to include the number of discharge medications. RESULTS: The final cohort had 5507 patients of which 1147 (20.8 %) were readmitted within thirty days of their hospital discharge date. The number of discharge medications was significantly greater for patients having a thirty-day readmission compared to those without a thirty-day readmission (7.2 ± 4.1 medications [7.0 medications (4.0 medications, 10.0 medications)] versus 6.0 ± 3.9 medications [6.0 medications (3.0 medications, 9.0 medications)]; P < 0.001). There was a statistically significant association between increasing numbers of discharge medications and the prevalence of thirty-day hospital readmission (P < 0.001). Multiple logistic regression identified more than six discharge medications to be independently associated with thirty-day readmission (OR, 1.26; 95 % CI, 1.17–1.36; P = 0.003). Other independent predictors of thirty-day readmission were: more than one emergency department visit in the previous six months, a minimum hemoglobin value less than or equal to 9 g/dL, presence of congestive heart failure, peripheral vascular disease, cirrhosis, and metastatic cancer. A risk score for thirty-day readmission derived from the logistic regression model had good predictive accuracy (AUROC = 0.661 [95 % CI, 0.643–0.679]). CONCLUSIONS: The number of discharge medications is associated with the prevalence of thirty-day hospital readmission. A risk score, that includes the number of discharge medications, accurately predicts patients at risk for thirty-day readmission. Our findings suggest that relatively simple and accessible parameters can identify patients at high risk for hospital readmission potentially distinguishing such individuals for interventions to minimize readmissions. BioMed Central 2015-07-23 /pmc/articles/PMC4512093/ /pubmed/26202163 http://dx.doi.org/10.1186/s12913-015-0950-9 Text en © Picker et al. 2015 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 Article
Picker, David
Heard, Kevin
Bailey, Thomas C.
Martin, Nathan R.
LaRossa, Gina N.
Kollef, Marin H.
The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title_full The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title_fullStr The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title_full_unstemmed The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title_short The number of discharge medications predicts thirty-day hospital readmission: a cohort study
title_sort number of discharge medications predicts thirty-day hospital readmission: a cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512093/
https://www.ncbi.nlm.nih.gov/pubmed/26202163
http://dx.doi.org/10.1186/s12913-015-0950-9
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