Comparing the Performance of Charlson and Elixhauser Comorbidity Indices to Predict In-Hospital Mortality Among a Chinese Population
Received 9 December 2019
Accepted for publication 3 March 2020
Published 18 March 2020 Volume 2020:12 Pages 307—316
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Vera Ehrenstein
Miao Cai,1 Echu Liu,2 Ruihua Zhang,3 Xiaojun Lin,4,5 Steven E Rigdon,1 Zhengmin Qian,1 Rhonda Belue,2 Jen-Jen Chang1
1Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA; 2Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA; 3School of Management, Chengdu University of Traditional Chinese Medicine, Chengdu 610075, Sichuan, People’s Republic of China; 4West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of China; 5West China Research Center for Rural Health Development, Sichuan University, Chengdu 610041, Sichuan, People’s Republic of China
Correspondence: Ruihua Zhang
School of Management, Chengdu University of Traditional Chinese Medicine, 1166 Liutaidadao, Chengdu 610075, Sichuan, People’s Republic of China
Objective: Earlier comorbidity measures have been developed or validated using the North American population. This study aims to compare five Charlson or Elixhauser comorbidity indices to predict in-hospital mortality using a large electronic medical record database from Shanxi, China.
Methods: Using the primary diagnosis code and surgery procedure codes, we identified four hospitalized patient cohorts, hospitalized between 2013 and 2017, in Shanxi, China, as follows: congestive heart failure (CHF, n=41,577), chronic renal failure (CRF, n=40,419), diabetes (n=171,355), and percutaneous coronary intervention (PCI, n=39,097). We used logistic regression models and c-statistics to evaluate the in-hospital mortality predictive performance of two multiple comorbidity indicator variables developed by Charlson in 1987 and Elixhauser in 1998 and three single numeric scores by Quan in 2011, van Walraven in 2009, and Moore 2017.
Results: Elixhauser comorbidity indicator variables had consistently higher c-statistics (0.824, 0.843, 0.904, 0.853) than all other four comorbidity measures, across all four disease cohorts. Moore’s comorbidity score outperformed the other two score systems in CHF, CRF, and diabetes cohorts (c-statistics: 0.776, 0.832, 0.869), while van Walraven’s score outperformed all others among PCI patients (c-statistics: 0.827).
Conclusion: Elixhauser comorbidity indicator variables are recommended, when applied to large Chinese electronic medical record databases, while Moore’s score system is appropriate for relatively small databases.
Keywords: comorbidity, Charlson, Elixhauser, administrative data, China
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