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Supported Comorbidity Mappings and Scores

Alessandro Gasparini

2024-07-16

Source: vignettes/B-comorbidity-scores.Rmd
B-comorbidity-scores.Rmd

The {comorbidity} R package can be used to identify comorbidity conditions and calculate comorbidity scores based on ICD codes data. Supported mapping and weighting algorithms are described below, including relevant references.

Examples showing how to apply each algorithm are included in a separate vignette.

Supported Mapping Algorithms

The {comorbidity} package can apply comorbidity mappings corresponding to the Charlson and the Elixhauser comorbidity scores. Both ICD-9 and ICD-10 coding systems are supported, with algorithms described in the paper by Quan et al. (2005). The resulting mapping algorithms are denoted with charlson_icd9_quan and charlson_icd10_quan for the Charlson score (based on ICD-9 and ICD-10 systems, respectively), elixhauser_icd9_quan and elixhauser_icd10_quan for the Elixhauser score.

Furthermore, the Swedish (Ludvigsson et al., 2021) and Australian (Sundararajan et al., 2004) modifications of the Charlson score are implemented as well, and identified by charlson_icd10_se and charlson_icd10_am respectively.

Supported Weighting Algorithms

Different weighting algorithms have been proposed to combine the different conditions into a single measure, for both the Charlson and the Elixhauser index.

Currently, the following weighting algorithms are supported for the Charlson score:

  • The original weights by Charlson et al. (1987), denoted with charlson;

  • Updated weights by Quan et al. (2011), denoted with quan.

Then, for the Elixhauser score:

  • Weights proposed by van Walraven et al. (2009), denoted with vw;

  • The Swiss weights modification by Sharma et al. (2021), denoted with swiss.

References

  • Charlson ME et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases 1987; 40:373-383. DOI: 10.1016/0021-9681(87)90171-8

  • Elixhauser A et al. Comorbidity measures for use with administrative data. Medical Care 1998; 36(1):8-27. DOI: 10.1097/00005650-199801000-00004

  • Ludvigsson JF et al. Adaptation of the Charlson Comorbidity Index for register-based research in Sweden. Clinical Epidemiology 2021; 13:21–41. DOI: 10.2147/clep.s282475

  • Quan H et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical Care 2005; 43(11):1130-1139. DOI: 10.1097/01.mlr.0000182534.19832.83

  • Quan H et al. Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. American Journal of Epidemiology 2011;173(6):676-82. DOI: 10.1093/aje/kwq433

  • Sharma N et al. Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data. BMC Health Services Research 2021; 21(1). DOI: 10.1186/s12913-020-05999-5

  • Sundararajan V et al. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. Journal of Clinical Epidemiology 2004; 57(12):1288-1294. DOI: 10.1016/j.jclinepi.2004.03.012

  • van Walraven C, Austin PC, Jennings A, Quan H and Forster AJ. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Medical Care 2009; 47(6):626-633. DOI: 10.1097/MLR.0b013e31819432e5