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Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data

Hude Quan; Vijaya Sundararajan; Patricia Halfon; Andrew Fong; Bernard Burnand; Jean‐Christophe Luthi; L. Duncan Saunders; Cynthia A Beck · Medical Care · 2005

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OBJECTIVES: Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. METHODS: ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. RESULTS: Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. CONCLUSIONS: These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.

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APA 7

Quan, H, Sundararajan, V, Halfon, P, Fong, A, Burnand, B, Luthi, J, Saunders, L. D, & Beck, C. A. (2005). Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data. https://doi.org/10.1097/01.mlr.0000182534.19832.83

MLA

Quan, Hude, et al. "Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data." 2005. https://doi.org/10.1097/01.mlr.0000182534.19832.83.

Chicago

Quan, Hude, Vijaya Sundararajan, Patricia Halfon, Andrew Fong, Bernard Burnand, Jean‐Christophe Luthi, L. Duncan Saunders, and Cynthia A Beck. 2005. "Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data.". https://doi.org/10.1097/01.mlr.0000182534.19832.83.

Harvard

Quan, H. et al. 2005, Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data, Medical Care, available at: https://doi.org/10.1097/01.mlr.0000182534.19832.83 [Accessed 28 Jun. 2026].

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Título
Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data
Autor / colaboradores
Hude Quan; Vijaya Sundararajan; Patricia Halfon; Andrew Fong; Bernard Burnand; Jean‐Christophe Luthi; L. Duncan Saunders; Cynthia A Beck
Editorial
Medical Care
Año de publicación
2005
Idioma
en

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