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Predictors of Readmission after Inpatient Plastic Surgery

BACKGROUND: Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery. METHODS: The 2011 National Surgical Quality Impr...

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Autores principales: Jain, Umang, Salgado, Christopher, Mioton, Lauren, Rambachan, Aksharananda, Kim, John YS
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Plastic and Reconstructive Surgeons 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961607/
https://www.ncbi.nlm.nih.gov/pubmed/24665418
http://dx.doi.org/10.5999/aps.2014.41.2.116
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author Jain, Umang
Salgado, Christopher
Mioton, Lauren
Rambachan, Aksharananda
Kim, John YS
author_facet Jain, Umang
Salgado, Christopher
Mioton, Lauren
Rambachan, Aksharananda
Kim, John YS
author_sort Jain, Umang
collection PubMed
description BACKGROUND: Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery. METHODS: The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both "Plastics" as their recorded surgical specialty and inpatient status. Readmission was tracked through the "Unplanned Readmission" variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission. RESULTS: A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD) (odds ratio [OR], 2.01; confidence interval [CI], 1.12-3.60; P=0.020), previous percutaneous coronary intervention (PCI) (OR, 2.69; CI, 1.21-5.97; P=0.015), hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001), bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046), American Society of Anesthesiologists (ASA) class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004), and obesity (body mass index ≥30) (OR, 1.43; CI, 1.09-1.88, P=0.011) to be significant predictors of readmission. CONCLUSIONS: Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations.
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spelling pubmed-39616072014-03-24 Predictors of Readmission after Inpatient Plastic Surgery Jain, Umang Salgado, Christopher Mioton, Lauren Rambachan, Aksharananda Kim, John YS Arch Plast Surg Original Article BACKGROUND: Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmission following inpatient plastic surgery. METHODS: The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both "Plastics" as their recorded surgical specialty and inpatient status. Readmission was tracked through the "Unplanned Readmission" variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission. RESULTS: A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD) (odds ratio [OR], 2.01; confidence interval [CI], 1.12-3.60; P=0.020), previous percutaneous coronary intervention (PCI) (OR, 2.69; CI, 1.21-5.97; P=0.015), hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001), bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046), American Society of Anesthesiologists (ASA) class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004), and obesity (body mass index ≥30) (OR, 1.43; CI, 1.09-1.88, P=0.011) to be significant predictors of readmission. CONCLUSIONS: Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations. The Korean Society of Plastic and Reconstructive Surgeons 2014-03 2014-03-12 /pmc/articles/PMC3961607/ /pubmed/24665418 http://dx.doi.org/10.5999/aps.2014.41.2.116 Text en Copyright © 2014 The Korean Society of Plastic and Reconstructive Surgeons http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Jain, Umang
Salgado, Christopher
Mioton, Lauren
Rambachan, Aksharananda
Kim, John YS
Predictors of Readmission after Inpatient Plastic Surgery
title Predictors of Readmission after Inpatient Plastic Surgery
title_full Predictors of Readmission after Inpatient Plastic Surgery
title_fullStr Predictors of Readmission after Inpatient Plastic Surgery
title_full_unstemmed Predictors of Readmission after Inpatient Plastic Surgery
title_short Predictors of Readmission after Inpatient Plastic Surgery
title_sort predictors of readmission after inpatient plastic surgery
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961607/
https://www.ncbi.nlm.nih.gov/pubmed/24665418
http://dx.doi.org/10.5999/aps.2014.41.2.116
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