Charlson Comorbidity Index (CCI)

Evidence Reviewed as of before: 03-02-2009
Author(s): Sabrina Figueiredo, BSc
Editor(s): Lisa Zeltzer, MSc OT; Nicol Korner-Bitensky, PhD OT; Elissa Sitcoff, BA BSc

Purpose

The Charlson Comorbidity Index (CCI) assesses comorbidity level by taking into account both the number and severity of 19 pre-defined comorbid conditions. It provides a weighted score of a client’s comorbidities which can be used to predict short term and long-term outcomes such as function, hospital length of stay and mortality rates. The CCI is the most widely used scoring system for comorbities used by researchers and clinicians (Charlson, Pompei, Ales, & Mackenzie, 1987; Elixhauser, Steiner, Harris, & Coffey, 1998).

In-Depth Review

Purpose of the measure

The Charlson Comorbidity Index (CCI) assesses comorbidity level by taking into account both the number and severity of 19 pre-defined comorbid conditions. It provides a weighted score of a client’s comorbidities which can be used to predict short term and long-term outcomes such as function, hospital length of stay and mortality rates. The CCI is the most widely used scoring system for comorbities used by researchers and clinicians (Charlson, Pompei, Ales, & Mackenzie, 1987; Elixhauser, Steiner, Harris, & Coffey, 1998).

Available versions

The CCI was published by Charlson, Pompei, Ales, and Mackenzie in 1987.

Features of the measure

Items:

The CCI is comprised of 19 comorbid conditions: myocardial infarct, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes, hemiplegia, moderate or several renal disease, diabetes with end organ damage, any tumor, leukemia, lymphoma, moderate or severe liver disease, metastatic solid tumor, AIDS. Each disease is given a different weight based on the strength of its association with 1-year mortality as follows (Charlson et al., 1987):

Assigned weights for diseases Comorbid Conditions
1 Myocardial infarct, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes
2 Hemiplegia, moderate or several renal diseases, diabetes with end organ damage, any tumor, leukemia, lymphoma
3 Moderate or severe liver disease
6 Metastatic solid tumor, AIDS

The CCI can be completed from medical records, administrative databases, or interview-based questionnaires (Bravo, Dubois, Hebert, De Wals, & Messier, 2002).

Scoring:

The total score in the CCI is derived by summing the assigned weights of all comorbid conditions presented by the client. Higher scores indicate a more severe condition and consequently, a worse prognosis (Charlson, Szatrowski, Peterson, & Gold, 1994).

Time:

Not reported

Subscales:

None

Equipment:

Not applicable.

Training:

No specific training is available.

Alternative forms of the CCI

The CCI has a weighted age version, two adaptations to be used with ICD-9 databases, and one version to be used with clients with amputations (Charlson et al., 1994; Deyo, Cherkin, & Ciol, 1992; Melchiore, Findley, & Boda, 1996; Romano, Roos, & Jollis, 1993).

Client suitability

Can be used with:

Clients with stroke.

The CCI is a general scoring system allowing for its use with a variety of populations (Groot, Beckerman, Lankhorst, & Bouter, 2003).

Should not be used in:

To date, there is no information on restrictions for using the CCI.

In what languages is the measure available?

Not applicable

Summary

What does the tool measure? The CCI measures comorbidity level.
What types of clients can the tool be used for? The CCI can be used with, but is not limited to clients with stroke.
Is this a screening or assessment tool? Screening.
Time to administer Not reported.
Versions Age CCI; ICD-9-CM; CCI for clients with amputations.
Other Languages Not applicable
Measurement Properties
Reliability
  • No studies have examined the internal consistency of the CCI.
  • One study has examined the test-retest reliability of the CCI and reported excellent test-retest reliability using Intraclass Correlation Coefficient (ICC) and Spearman’s Rank Correlation.
  • No studies have examined the intra-rater reliability of the CCI.
  • One study examined the inter-rater reliability of the CCI and reported adequate inter-rater reliability using ICC.
Validity

Content:

One study examined the content validity of the CCI by reporting the steps for generating the weighted comorbidity index.

Criterion:

Concurrent:

No studies have examined the concurrent validity of the CCI.

Predictive:

Four studies have examined the predictive validity of the CCI and reported that the CCI was able to predict function at 3 months post-stroke, poor outcomes on the modified Rankin Scale at discharge, and mortality after 1 year. In contrast, the CCI was not able to predict length of stay, Functional Independence Measure scores, and modified Rankin Scale scores at 4 months post-stroke.

Construct:

Convergent:

Three studies examined the convergent validity of the CCI and reported excellent correlations between the CCI and the Functional Comorbidity Index, poor to adequate correlations between the CCI and total numbers of medication consumed, numbers of hospitalization, length of stay, total costs, laboratory studies, therapeutic interventions, consultations and days of interruption of the rehabilitation program using Spearman rank correlation.

Known Groups:

No studies have examined the known groups validity of the CCI.

Floor/Ceiling Effects No studies have examined floor/ceiling effects of the CCI.
Sensitivity/ Specificity No studies have examined the sensitivity/specificity of the CCI.
Does the tool detect change in patients? No studies have examined the responsiveness of the CCI.
Acceptability The CCI is the most widely used index to assess comorbidity.
Feasibility The CCI can be completed from medical records, administrative databases, or interview-based questionnaires.
How to obtain the tool? The CCI can be obtained from its original publication: (Charlson, Pompei, Ales, & Mackenzie, 1987)

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the Charlson Comorbidity Index (CCI) in individuals with stroke. We identified 6 studies.

Reliability

Test-retest:

Katz, Chang, Sangha, Fossel, and Bates (1996) evaluated the test-retest reliability of the questionnaire format of the CCI in 25 inpatients with different diagnoses including stroke. Participants were evaluated by the same rater twice within 24 hours. Test-retest reliability was excellent as calculated using Intraclass Correlation Coefficient (ICC = 0.92) and Spearman’s Rank Correlation (rho = 0.94).

Inter-rater:

Liu, Domen and Chino (1997) assessed the inter-rater reliability of the CCI in 10 clients with stroke. The CCI was administered by two examiners blinded to each other’s scores. Inter-rater reliability, as calculated using Intraclass Correlation Coefficient, was adequate (ICC = 0.67).

Validity

Content:

Charlson et al. (1987) identified the comorbid conditions of 559 inpatients with breast cancer. They then calculated the relationship of potential prognostically important variables to survival using Cox’s regression analysis. Finally, the adjusted relative risk was estimated to each comorbid condition.

Criterion:

Concurrent:

No gold standard exists against which to compare the CCI.

Predictive:

Liu et al. (1997) estimated the ability of the CCI at hospital admission to predict length of stay and the Functional Independence Measure (FIM) score (Keith, Granger, Hamilton, & Sherwin, 1987) at discharge. Predictive validity was calculated in 106 clients with Spearman’s Rank Correlation. Correlation between the CCI and the FIM was poor(rho = -0.19) as was the correlation between the CCI and length of stay (rho = 0.16). These results suggest that the CCI measured at hospital admission may not be predictive of length of stay or the FIM at discharge.

Goldstein, Samsa, Matchar, and Horner (2004) examined in 960 clients with acute stroke whether the CCI measured at admission was able to predict the modified Rankin Scale (mRS) (Rankin, 1957) at hospital discharge, and, 1-year mortality rates. Predictive validity was analyzed using logistic regression. The CCI was dichotomized into low comorbidity (scores <2) and high comorbidity (scores <2) and the mRS into good outcomes (scores <2) and poor outcomes (scores ≥2). Higher CCI scores were associated with a 36% increased odds of having poor outcomes on the modified Rankin Scale and 72% greater odds of death at 1 year post-stroke.

Fischer, Arnold, Nedeltchev, Schoenenberger, Kappeler, Hollinger et al. (2006) verified in 259 clients the ability of the CCI, as measured at admission to a stroke unit, to predict poor outcomes on the modified Rankin Scale (mRS – Rankin, 1957) at 4 months after hospital discharge. The mRS was dichotomized into good outcomes (scores ≤ 2) and poor outcomes (scores >2). Logistic regression analyses revealed that the CCI was not able to predict poor outcomes on the mRS. In this study, the predictors of the mRS score at 4 months post-stroke were stroke severity, atrial fibrilation, coronary artery disease and diabetes.

Tessier, Finch, Daskalopoulou, and Mayo (2008) examined, in 672 participants, the ability of the CCI, the Functional Comorbidity Index (Groll, Bombardier, & Wright, 2005), and a stroke-specific comorbidity index (developed by the same authors) to predict function 3 months post-stroke. Predictive validity was calculated by use of c-statistics to calculate the area under the Receiver Operating Characteristic (ROC) curve. The ability of the CCI (AUC = 0.76), the Functional Comorbidity Index (AUC = 0.71) and the stroke-specific comorbidity index (AUC = 0.71) to predict function at 3 months post-stroke were all adequate. These results suggest that the percentage of patients correctly classified according to their function at 3 months post-stroke is slightly higher when using the CCI over these other comorbidity measures.

Construct:

Convergent/Discriminant

Katz et al. (1996) tested the convergent validity of the CCI by comparing it to self-reported number of prescription medications consumed, number of hospitalizations, length of stay and total financial costs in 170 hospital inpatients, including those with stroke. Correlations, as calculated using Spearman’s Rank Correlation, were all poor between the CCI and self-reported number of prescription medications (rho = 0.06), number of hospitalizations (rho = 0.22), length of stay (rho = 0.20) and total costs (rho = 0.26).

Liu et al. (1997) measured the convergent validity of the CCI in 106 clients with stroke, by comparing it to the number of medication consumed, laboratory studies, therapeutic interventions, number of consultations during hospital’s stay, and days of interruption of participation in rehabilitation due to complications. Adequate correlations were found between the CCI and the total number of medications consumed (rho = 0.48) and poor correlations were found between the CCI and laboratory studies (rho = 0.28), therapeutic interventions (rho = 0.19), consultations (rho = 0.25), and days of interruption of rehabilitation participation (rho = 0.22).

Tessier et al. (2008) analyzed the convergent validity of the CCI by comparing it to the Functional Comorbidity Index (Groll et al., 2005) in 437 clients with Correlations were found to be excellent (rho = 0.62).

Known groups:

No studies have examined known groups validity of the CCI.

Responsiveness

No studies have examined the responsiveness of the CCI.

References

  • Bravo, G., Dubois, M.F., Hebert, R., De Wals, P., & Messier, L. (2002). A perspective evaluation of the Charlson Comorbidity Index for use in long-term care patients. JAGS, 50, 740-745.
  • Charlson, M., Pompei, P., Ales, M.L., & Mackenzie C.R. (1987). A new method of classifying comorbidity in longitudinal studies: Development and validation. J Chronic Dis, 40, 373-393.
  • Charlson, M., Szatrowski, T.P., Peterson, J., & Gold, J. (1994). Validationof a Combined Comorbidity Index. Journal of Clinical Epidemiology, 47(11), 1245-1251.
  • De Groot, V., Beckerman, H., Lankhorst, G.J., & Bouter, L.M. (2003). How to measure comorbidity: A critical review of available methods. Journal of Clinical Epidemiology, 56, 221-229.
  • Deyo, R.A., Cherkin, D.C., & Ciol, M.A. (1992). Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal Clinical Epidemiology, 45, 613-619.
  • Elixhauser, A., Steiner, C., Harris, D.R., & Coffey, R.M. (1998).Comorbidity measures for use with administrative data. Medical Care, 36(1), 8-27.
  • Fischer, U., Nedeltchev, K., Schoenenberger, R.A., Kappeler, L., Hollinger, P.,Schroth, G. et al. (2006). Impact of comorbidity on ischemic stroke outcome. Acta Neurol Scand, 113, 108-113.
  • Goldstein, L.B., Samsa, G.P., Matchar, D.B., & Horner, R.D. (2004). Charlson Index Comorbidity Adjustment for Ischemic Stroke Outcome Studies. Stroke, 35, 1941-1945.
  • Groll, D., Bombardier, C., & Wright, J. (2005). The development of a comorbidity index with physical function as the outcome. Journal of Clinical Epidemiology, 58, 595-602.
  • Hall, W. H., Ramachandran, R., Narayan, S., Jani, A. B., & Vijayakumar, S. (2004). An electronic application for rapidly calculating Charlson comorbidity score. BMC Cancer, 4, 94.
  • Katz, J., Chang, L., Sangha, O., Fossel, A., & Bates, D. (1996). Can comorbidity be measured by questionnaire rather than medical record review? Medical Care, 34(1), 73-84.
  • Keith, R.A., Granger, C.V., Hamilton, B.B., & Sherwin, F.S. (1987). The functional independence measure: A new tool for rehabilitation. Adv Clin Rehabil, 1, 6-18.
  • Liu, M., Domen, K., & Chino, N. (1997). Comorbidity measures for stroke outcome research: A preliminary study. Arch Phys Rehabil, 78, 166-172.
  • Melchiore, P.J., Findley, T., Boda, W. (1996). Functional outcome and comorbidity indexes in the rehabilitation of the traumatic versus the vascular unilateral lower limb amputee. Am J Phys Med Rehabil, 75, 9-14.
  • Rankin, J. (1957). Cerebral vascular accidents in patients over the age of 60. Scott Med J, 2, 200-215.
  • Romano, P.S., Roos, L.L., & Jollis, J.G. (1993). Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. Journal of clinical epidemiology, 46 (10) 1075-1079.
  • Tessier, A., Finch. L., Daskalopoulou, S.S., Mayo, N.E. (2008). Validation of the Charlson Comorbidity Index for Predicting Functional Outcome of Stroke. Arch Phys Med Rehabil, 89, 1276-1283.

See The Measure

How to obtain the CCI

An electronic application for rapidly calculating Charlson Comorbidity Index score

The following link will allow you to download an Excel Spread sheet calculator for Charlson Comorbidity Index: Excel calculator Charlson Index

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