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Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country

BACKGROUND: The Charlson Comorbidity Index (CCI) can be automatically calculated from the International Classification of Disease (ICD) code. However, the feasibility of this transformation has not been acknowledged, particularly in hospitals without a qualified ICD coding system. Here, we investiga...

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Autores principales: Mo, Liyi, Xie, Zhen, Liu, Guohui, He, Qiang, Mo, Zhiming, Wu, Yanhua, Wang, Wenji, Ding, Feng, Liao, Yuanjiang, Hao, Li, Lu, Chen, Sun, Jin, Xu, Libin, Zhang, Yusheng, Ghappar, Rizwangul, Peng, Hongwei, Wei, Xiaohong, Xie, Jinglie, Chen, Yuanhan, Liang, Xinling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236530/
https://www.ncbi.nlm.nih.gov/pubmed/32423399
http://dx.doi.org/10.1186/s12913-020-05273-8
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author Mo, Liyi
Xie, Zhen
Liu, Guohui
He, Qiang
Mo, Zhiming
Wu, Yanhua
Wang, Wenji
Ding, Feng
Liao, Yuanjiang
Hao, Li
Lu, Chen
Sun, Jin
Xu, Libin
Zhang, Yusheng
Ghappar, Rizwangul
Peng, Hongwei
Wei, Xiaohong
Xie, Jinglie
Chen, Yuanhan
Liang, Xinling
author_facet Mo, Liyi
Xie, Zhen
Liu, Guohui
He, Qiang
Mo, Zhiming
Wu, Yanhua
Wang, Wenji
Ding, Feng
Liao, Yuanjiang
Hao, Li
Lu, Chen
Sun, Jin
Xu, Libin
Zhang, Yusheng
Ghappar, Rizwangul
Peng, Hongwei
Wei, Xiaohong
Xie, Jinglie
Chen, Yuanhan
Liang, Xinling
author_sort Mo, Liyi
collection PubMed
description BACKGROUND: The Charlson Comorbidity Index (CCI) can be automatically calculated from the International Classification of Disease (ICD) code. However, the feasibility of this transformation has not been acknowledged, particularly in hospitals without a qualified ICD coding system. Here, we investigated the utility of coding-based CCI in China. METHODS: A multi-center, population-based, retrospective observational study was conducted, using a dataset incorporating 2,464,395 adult subjects from 15 hospitals. CCI was calculated using both ICD-10-based and diagnosis-based method, according to the transformation rule reported previously and to the literal description from discharge diagnosis, respectively. A κ coefficient of variation was used as a measure of agreement between the above two methods for each hospital. The discriminative abilities of the two methods were compared using the receiver-of-operating characteristic curve (ROC) for prediction of in-hospital mortality. RESULTS: Total agreement between the ICD-based and diagnosis-based CCI for each index ranged from 86.1 to 100%, with κ coefficients from 0.210 [95% confidence interval (CI) 0.208–0.212] to 0.932 (95% CI 0.924–0.940). None of the 19 indices of CCI had a κ coefficient > 0.75 in all the hospitals included for study. The area under the curve of ROC for in-hospital mortality of all 15 hospitals was significantly lower for ICD-based than diagnosis-based CCI [0.735 (0.732, 0.739) vs 0.760 (0.757, 0.764)], indicative of more limited discriminative ability of the ICD-based calculation. CONCLUSIONS: CCI calculated using ICD-10 coding did not agree with diagnosis-based CCI. ICD-based CCI displayed diminished discrimination performance in terms of in-hospital mortality, indicating that this method is not promising for CCI scoring in China under the present circumstances.
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spelling pubmed-72365302020-05-29 Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country Mo, Liyi Xie, Zhen Liu, Guohui He, Qiang Mo, Zhiming Wu, Yanhua Wang, Wenji Ding, Feng Liao, Yuanjiang Hao, Li Lu, Chen Sun, Jin Xu, Libin Zhang, Yusheng Ghappar, Rizwangul Peng, Hongwei Wei, Xiaohong Xie, Jinglie Chen, Yuanhan Liang, Xinling BMC Health Serv Res Research Article BACKGROUND: The Charlson Comorbidity Index (CCI) can be automatically calculated from the International Classification of Disease (ICD) code. However, the feasibility of this transformation has not been acknowledged, particularly in hospitals without a qualified ICD coding system. Here, we investigated the utility of coding-based CCI in China. METHODS: A multi-center, population-based, retrospective observational study was conducted, using a dataset incorporating 2,464,395 adult subjects from 15 hospitals. CCI was calculated using both ICD-10-based and diagnosis-based method, according to the transformation rule reported previously and to the literal description from discharge diagnosis, respectively. A κ coefficient of variation was used as a measure of agreement between the above two methods for each hospital. The discriminative abilities of the two methods were compared using the receiver-of-operating characteristic curve (ROC) for prediction of in-hospital mortality. RESULTS: Total agreement between the ICD-based and diagnosis-based CCI for each index ranged from 86.1 to 100%, with κ coefficients from 0.210 [95% confidence interval (CI) 0.208–0.212] to 0.932 (95% CI 0.924–0.940). None of the 19 indices of CCI had a κ coefficient > 0.75 in all the hospitals included for study. The area under the curve of ROC for in-hospital mortality of all 15 hospitals was significantly lower for ICD-based than diagnosis-based CCI [0.735 (0.732, 0.739) vs 0.760 (0.757, 0.764)], indicative of more limited discriminative ability of the ICD-based calculation. CONCLUSIONS: CCI calculated using ICD-10 coding did not agree with diagnosis-based CCI. ICD-based CCI displayed diminished discrimination performance in terms of in-hospital mortality, indicating that this method is not promising for CCI scoring in China under the present circumstances. BioMed Central 2020-05-18 /pmc/articles/PMC7236530/ /pubmed/32423399 http://dx.doi.org/10.1186/s12913-020-05273-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
Mo, Liyi
Xie, Zhen
Liu, Guohui
He, Qiang
Mo, Zhiming
Wu, Yanhua
Wang, Wenji
Ding, Feng
Liao, Yuanjiang
Hao, Li
Lu, Chen
Sun, Jin
Xu, Libin
Zhang, Yusheng
Ghappar, Rizwangul
Peng, Hongwei
Wei, Xiaohong
Xie, Jinglie
Chen, Yuanhan
Liang, Xinling
Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title_full Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title_fullStr Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title_full_unstemmed Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title_short Feasibility of coding-based Charlson comorbidity index for hospitalized patients in China, a representative developing country
title_sort feasibility of coding-based charlson comorbidity index for hospitalized patients in china, a representative developing country
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236530/
https://www.ncbi.nlm.nih.gov/pubmed/32423399
http://dx.doi.org/10.1186/s12913-020-05273-8
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