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Compute Charlson comorbidity index (CCI) score

charlson_comorbidity_index.Rd

Based on the methodology from Charlson et al. 1988, Quan H et al. 2005, and Quan et al. 2011 using ICD-10 codes as the mapping algorithm, implemented in the R comorbidity package by Gasparini, 2018.

Can compute either CCI score at admission based on HSMR Methodology or for the entire patient encounter. The default is to compute comorbidity at admission.

Usage

charlson_comorbidity_index(
  ipdiag,
  erdiag,
  at_admission = TRUE,
  raw_comorbidities = FALSE
)

Arguments

ipdiag

(data.table or data.frame)
ipdiagnosis table as defined in the GEMINI Data Repository Dictionary.

erdiag

(data.table or data.frame)
erdiagnosis table as defined in the GEMINI Data Repository Dictionary. Typically, ER diagnoses should be included when deriving comorbidity in order to increase sensitivity. However, in certain scenarios, users may choose to only include IP diagnoses by specifying erdiag = NULL. This may be useful when comparing cohorts with different rates of ER admissions.

at_admission

(logical)
Whether to calculate the score for all comorbidities or for only pre-admit comorbidities.

raw_comorbidities

(logical)
Whether to output a data.table of raw comorbidities as opposed to pre-computed scores.

Value

(data.table)
By default, for each encounter, outputs the comorbidity score. If raw_comorbidities is TRUE, outputs a wide data.table with a column for each comorbidity for each encounter.

Details

A hierarchy of comorbidities is used when calculating the cormorbidity score, but not when outputting raw_comorbidites. This affects comorbidities present in a patient with different degrees of severity. See documentation for comorbidity::comorbidity() for details.

References

  • Charlson M, et al. Journal of Chronic Diseases, 1988. https://doi.org/10.1016/0021-9681(87)90171-8

  • Quen H, et al. Med Care, 2005. https://www.jstor.org/stable/3768193

  • Quan H, et al. Am J Epidemiol, 2011. https://doi.org/10.1093/aje/kwq433

  • Gasparini A. JOSS, 2018. https://doi.org/10.21105/joss.00648