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Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty
PURPOSE: Total knee arthroplasty (TKA) is increasing in frequency and cost. Optimization of discharge location may reduce total expenditure while maximizing patient outcomes. Although preoperative illness rating systems—including the American Society for Anesthesiologists Physical Classification Sys...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Knee Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5853174/ https://www.ncbi.nlm.nih.gov/pubmed/29482304 http://dx.doi.org/10.5792/ksrr.17.079 |
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author | Rudasill, Sarah Dattilo, Jonathan R. Liu, Jiabin Clements, Ari Nelson, Charles L. Kamath, Atul F. |
author_facet | Rudasill, Sarah Dattilo, Jonathan R. Liu, Jiabin Clements, Ari Nelson, Charles L. Kamath, Atul F. |
author_sort | Rudasill, Sarah |
collection | PubMed |
description | PURPOSE: Total knee arthroplasty (TKA) is increasing in frequency and cost. Optimization of discharge location may reduce total expenditure while maximizing patient outcomes. Although preoperative illness rating systems—including the American Society for Anesthesiologists Physical Classification System (ASA), severity of illness scoring system (SOI), and Mallampati rating scale (MP)—are associated with patient morbidity and mortality, their predictive value for discharge location, length of stay (LOS), and total costs remains unclear. MATERIALS AND METHODS: We conducted a retrospective analysis of 677 TKA patients (550 primary and 127 revision) treated at a single institution. The influence of ASA, SOI, and MP scores on discharge locations, LOS, and total costs was assessed using multivariable regression analyses. RESULTS: None of the systems were significant predictors of discharge location following TKA. SOI scores of major or higher (β=2.08 days, p<0.001) and minor (β=−0.25 days, p=0.009) significantly predicted LOS relative to moderate scores. Total costs were also significantly predicted by SOI scores of major or higher (β=$6,155, p=0.022) and minor (β=−$1,163, p=0.007). CONCLUSIONS: SOI scores may be harnessed as a predictive tool for LOS and total costs following TKA, but other mechanisms are necessary to predict discharge location. |
format | Online Article Text |
id | pubmed-5853174 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Korean Knee Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-58531742018-03-20 Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty Rudasill, Sarah Dattilo, Jonathan R. Liu, Jiabin Clements, Ari Nelson, Charles L. Kamath, Atul F. Knee Surg Relat Res Original Article PURPOSE: Total knee arthroplasty (TKA) is increasing in frequency and cost. Optimization of discharge location may reduce total expenditure while maximizing patient outcomes. Although preoperative illness rating systems—including the American Society for Anesthesiologists Physical Classification System (ASA), severity of illness scoring system (SOI), and Mallampati rating scale (MP)—are associated with patient morbidity and mortality, their predictive value for discharge location, length of stay (LOS), and total costs remains unclear. MATERIALS AND METHODS: We conducted a retrospective analysis of 677 TKA patients (550 primary and 127 revision) treated at a single institution. The influence of ASA, SOI, and MP scores on discharge locations, LOS, and total costs was assessed using multivariable regression analyses. RESULTS: None of the systems were significant predictors of discharge location following TKA. SOI scores of major or higher (β=2.08 days, p<0.001) and minor (β=−0.25 days, p=0.009) significantly predicted LOS relative to moderate scores. Total costs were also significantly predicted by SOI scores of major or higher (β=$6,155, p=0.022) and minor (β=−$1,163, p=0.007). CONCLUSIONS: SOI scores may be harnessed as a predictive tool for LOS and total costs following TKA, but other mechanisms are necessary to predict discharge location. Korean Knee Society 2018-03 2018-03-01 /pmc/articles/PMC5853174/ /pubmed/29482304 http://dx.doi.org/10.5792/ksrr.17.079 Text en Copyright © 2018 Korean Knee Society This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Rudasill, Sarah Dattilo, Jonathan R. Liu, Jiabin Clements, Ari Nelson, Charles L. Kamath, Atul F. Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title | Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title_full | Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title_fullStr | Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title_full_unstemmed | Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title_short | Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty |
title_sort | using illness rating systems to predict discharge location following total knee arthroplasty |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5853174/ https://www.ncbi.nlm.nih.gov/pubmed/29482304 http://dx.doi.org/10.5792/ksrr.17.079 |
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