Max Rady College of Medicine

Concept: Charlson Comorbidity Index

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Concept Description

Last Updated: 2023-02-03

Introduction

    This concept contains information on the Charlson Comorbidity Index including: a basic description of the Charlson Comorbidity Index, how the Index is used at MCHP, and a brief historical perspective on the development and changes to the Index over time as presented in different research. The concept also includes access to different versions of SAS® code / SAS® macro code for generating the Charlson Comorbidity Index.

Description of the Charlson Comorbidity Index

Use of the Charlson Comorbidity Index at MCHP

    This section describes the use of the Charlson Comorbidity Index at MCHP. It identifies the source of diagnosis codes in the MCHP Data Repository and how they are relevant for use in the Charlson Comorbidity algorithm, describes and provides access to the SAS® macro code that is available at MCHP for generating the Charlson Comorbidity Index and calculating the Index score, and lists the published MCHP research that have used the Charlson Comorbidity Index with a brief description of how it was used.

    NOTE: The Charlson Comorbidity Index developed at MCHP can be used to measure the comorbidity of individual episodes of hospital care or it can be used to create a longitudinal index based on multiple hospital episodes and medical services / physician claims over time, depending on the purpose of the specific research project.

Source of Diagnosis Codes for the Charlson Comorbidity Index

    The diagnosis codes required for use in the Charlson Comorbidity Index are available from the Hospital Abstracts data and from the Medical Services / Physician Claims data.

    Hospital data contains all the relevant diagnoses during an episode of care as an inpatient. For each diagnosis recorded in the hospital data, a corresponding variable called diagnosis type is used to identify whether the diagnosis is considered a comorbidity (pre-existing condition) or a complication (a condition arising during the hospital stay). Complications are identified by a diagnosis type = "C" (complication) in the data prior to April 1, 2004 (for use with ICD-9-CM codes) or by a diagnosis type = "2" (post-admit comorbidity) in the data beginning on April 1, 2004 (for use with ICD-10 codes). At MCHP, complications can be included or excluded in the Charlson Comorbidity Index algorithm.

    The Medical Services / Physician Claims data contains only one diagnosis code per record, relevant to the reason for the visit to the physician. Although the Charlson Comorbidity Index is originally designed to work with hospital data only, at MCHP we have developed a method that can include 3-digit diagnosis codes from the Medical Services data, if warranted by the research, to expand the scope of comorbidity found in the population. Note: In December 2018, a 5-digit diagnosis code variable was added to the Medical Services data. If recorded, the first 3-digits of both the 3-digit and 5-digit diagnosis code variables will match exactly. The 5-digit diagnosis code variable applies to records from 2015/16 forward and may not be available for all records.

    See the section titled MCHP Charlson Comorbidity Index SAS Macro for the Medical Services / Physician Claims Data (3- and 5-digit ICD-9-CM codes) for more information on using the Medical Services / Physician Claims data.

    Lists of Charlson Comorbidity Index Categories and the Associated ICD Codes

MCHP Charlson Comorbidity Index SAS Macros

    At MCHP there are different SAS macros available that can be used to generate Charlson Comorbidity Index scores. The process involves producing category indicators at the record level from hospital abstracts data and calculating a score for each episode of care, or if desired, reviewing multiple records from hospital abstracts and physician visits data for the same individual over time, and then generating an overall Index score. The SAS code includes:

    • two SAS macros that identify the Charlson Comorbidity categories and the total number of categories for each individual record (hospital episode). One macro is based on ICD-9-CM diagnoses codes and the other is based on ICD-10 diagnoses codes;
    • a SAS macro that identifies the appropriate Charlson Comorbidity category for each record from the Medical Services / Physician Claims data based on 3- and 5-digit ICD-9-CM diagnosis codes; and
    • a SAS macro that calculates a longitudinal Index score based on all of the episodes of hospital care and physician visits for an individual and the applicable weights for each category of comorbidity.

    MCHP Charlson Comorbidity Index SAS Macros for Hospital Data - Individual Episode of Care
    There are two different SAS macros available for working with hospital data: one for use with ICD-9-CM diagnosis codes and one for use with ICD-10 diagnosis codes.

    To run the MCHP Charlson Comorbidity Index SAS macro, a file containing individual hospital records with diagnosis codes and the corresponding diagnosis type is required. Although the Charlson Comorbidity Index was originally designed for use with comorbidities only, there may be times when the Index should consider all diagnoses. For example, if the Index is being used in a longitudinal study, all diagnoses could be included in the Index calculation. However, if the study period only covers a short period of time, including complications may over-estimate the burden of disease.

    The MCHP Charlson Comorbidity Index SAS macros have a parameter option to include all types of diagnoses (type=off) or to limit the diagnoses to exclude complications (type=on). A research decision should be made on whether to include all diagnoses or exclude complications in the Index calculation.

    The two MCHP SAS macros for working with hospital data are available below:


    NOTE: The MCHP SAS macros are based on information in Quan's "Enhanced Charlson Diagnosis-Type SAS code" programs, but modified to be more generalized for use with other data sources and to run more efficiently at MCHP.

    MCHP Charlson Comorbidity Index SAS Macro for the Medical Services / Physician Claims Data (3- and 5-digit ICD-9-CM codes)

    To run the MCHP Charlson Comorbidity Index SAS macro with the Medical Services / Physician Claims data, a file containing individual physician visit records with the diagnosis codes is required.

    CAUTION: the Medical Services data should not be used alone to create the Charlson Comorbidity Index, as many 3-digit ICD-9-CM codes lack the specificity required in the algorithm. The Medical Services data should only be used in conjunction with the Hospital Abstracts data to generate a total Index score. In general, using Medical Services data alone to calculate the Charlson Comorbidity Index is not recommended and goes beyond the original intent of the Index.

    NOTE: In December 2018, a 5-digit diagnosis code variable was added to the Medical Services data. If recorded, the first 3-digits of both the 3-digit and 5-digit diagnosis code variables will match exactly. The 5-digit diagnosis code variable applies to records from 2015/16 forward, but may not be available in all records.

    The use of 3-digit codes requires a modification in the Charlson Comorbidity Index algorithm. These modifications include:

    • combining the two diabetes conditions, "Diabetes With Complication" and "Diabetes Without Complications", into one category because it is not possible to differentiate between the two categories using 3-digit codes. Anyone with ICD code "250" is assigned to the less severe "Diabetes Without Complications" category.
    • deciding to include or exclude certain codes in specific categories due to the specificity issue. For a complete list of the 3-digit ICD-9-CM codes used for each category and the choices that were made for inclusion/exclusion of 3-digit codes in our research, please see Using 3-Digit ICD-9-CM Codes with the Charlson Comorbidity Index.

    See the Notes, Cautions and Limitations section below for more information on specificity and using 3-digit ICD codes in the algorithm.

    The MCHP SAS macro for working with the Medical Services / Physician Claims data (3- and 5-digit ICD-9-CM diagnosis codes) is available below. This SAS code was updated in November 2020 to work with 3- and 5-digit ICD-9-CM diagnosis codes and again in January 2023 to run as a macro.

    MCHP Charlson Comorbidity Index SAS Code - Calculating a Longitudinal Index Score

    This macro will calculate a longitudinal Index score for an individual based on multiple Index records over time. It takes into account all of the comorbidity categories indicated for all episodes of hospital care and physician visits, and the algorithm flags a comorbidity category as present only once during the calculation and does not increase the overall Index score when the same category occurs more than once. This code will also attach the appropriate weight to each category when it is calculating the Index score.

    The MCHP SAS macro for calculating the longitudinal Index score is available below:

MCHP Research Using the Charlson Comorbidity Index

Historical Research Perspective on the Charlson Comorbidity Index

    The Charlson Comorbidity Index was originally developed in 1987. The following is a list of some of the significant historical developments and changes in the Charlson Comorbidity Index that have occurred over time in published research:

    1. Charlson et al. (1987)
    In the original publication "A new method of classifying prognostic comorbidity in longitudinal studies: development and validation" by Charlson et al. (1987), they identified 19 categories of comorbidity and weights were developed for each category based on the adjusted relative risk of one-year mortality. All of the individual weights are summed to produce a single comorbidity score for each patient.

    2. Deyo et al. (1992)

    In the publication "Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases" by Deyo et al. (1992), they assigned corresponding ICD-9-CM diagnosis and procedure codes for each category of the Charlson Comorbidity Index. Two of the original categories, "Leukemia" and "Lymphomas", were combined in the "Any Malignancy" category, thus resulting in a total of 17 different categories.

    3. Romano et al. (1993)

    In the publication "Further evidence concerning the use of a clinical comorbidity index with ICD-9-CM administrative data" by Romano et al. (1993), they compared the list of ICD codes developed by Deyo with a different set of codes, referred to as the Dartmouth-Manitoba codes, developed for use with the Charlson Comorbidity Index. The study illustrated that the assignment of ICD-9-CM codes to the Charlson Comorbidity Index is not straightforward and depends on the type of data and its availability, and concluded that in some cases the differences will have little or a significant impact on the measure of comorbidity.

    4. Halfon et al. (2002)

    In the publication "Measuring potentially avoidable hospital readmissions" by Halfon et al. (2003), they translated the ICD-9-CM diagnosis codes from the Deyo adaptation of the Charlson Comorbidity Index into ICD-10-codes. Appendix C in the article presents the ICD-10 codes and assigned weights that were developed by Halfon.

    5. Schneeweiss et al. (2003)

    In the publication "Improved comorbidity adjustment for predicting mortality in Medicare populations" by Schneeweiss et al. (2003), they investigated methods for adjusting comorbidity measures in order to improve the prediction of mortality in Medicare populations. This research used Romano's adapted Charlson Comorbidity Index and came up with adjusted weights for using the index - see Table 4: Conditions According to the Romano Adaptation of the Charlson Comorbidity Index for Use with Claims Data with original Charlson Index Weights and Weights Derived from New Jersey Medicare Data in the full text publication available from the PubMed Central web site at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1360935/pdf/hesr_165.pdf - accessed October 3, 2014.

    6. Quan et al. (2005)

    In the publication "Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data" by Quan et al. (2005), they "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." They also followed Deyo's coding algorithm, which led to modifications and enhanced coding algorithms for the index. For a listing of the ICD-9-CM and ICD-10 codes used for each category in Quan et al. (2005), please see ICD-9-CM and ICD-10 Coding Algorithms for Charlson Comorbidities.

    Comparison of Halfon and Quan's ICD-10 Coding
    The following link is a table comparing Halfon's and Quan's translations of the Charlson Comorbidity Index using ICD-10 codes: Halfon-Quan Comparison of Charlson ICD-10 Codes. Note: The table also includes Quan's translation of the Elixhauser index.
    The Charlson Comorbidity Index SAS® code developed for this project is available below with Quan's permission:

    7. Sundararajan et al. (2007)
    In the publication "Cross-national comparative performance of three versions of the ICD-10 Charlson Index" by Sundararajan et al. (2007), they compared the performance of three different versions of the Charlson Comorbidity Index using ICD-10 coding and found that all three versions performed satisfactorily.
    8. Li et al. (2008)
    In the publication "Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases" by Li et al. (2008), they assessed the performance of the Charlson Comorbidity Index and the Elixhauser Comorbidity Index using ICD-10 coding systems and found that the "change in coding algorithms did not influence the performance of either ... [index] ... in the prediction of outcome".

Notes, Cautions and Limitations

    The following list of notes, cautions and limitations should be considered when using the Charlson Comorbidity Index:

    1. Although the original Charlson Comorbidity Index was designed to include only comorbidities, there may be times when the Index should consider all diagnoses recorded. For example, if the Index is being used in a longitudinal study, all diagnoses could be included in the Index calculation because they represent comorbidity over time. However, if the study period only covers a short period of time, then including complications may over-estimate the burden of disease.

      At MCHP, the SAS macro code for the Charlson Comorbidity Index has a parameter option to include all diagnoses or to exclude complications. A research decision should be made on whether to include all diagnoses or exclude complications in the Index calculation.

    2. The Charlson Comorbidity Index is designed for use with very specific ICD coding (up to 5-digit ICD-9-CM codes and 7-digit ICD-10 codes) found in the Hospital Abstracts data. This is due to the specificity required to distinguish between diagnoses that should / should not be included in the Index and to be able to properly identify and place codes into the appropriate category.

    3. In general, using only 3-digit ICD codes to calculate the Charlson Comorbidity Index is not recommended because 3-digit codes lack the specificity required to properly categorize diagnoses in the Charlson Comorbidity Index.

SAS code and formats 

Related concepts 

Related terms 

Links 

References 

  • Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40(5):373-383. [Abstract] (View)
  • Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal of Clinical Epidemiology 1992;45(6):613-619. [Abstract] (View)
  • Garland A, Fransoo R, Olafson K, Ramsey C, Yogendran M, Chateau D, McGowan K. The Epidemiology and Outcomes of Critical Illness in Manitoba. Winnipeg, MB: Manitoba Centre for Health Policy, 2012. [Report] [Summary] (View)
  • Halfon P, Eggli Y, van Melle G, Chevalier J, Wasserfallen JB, Burnand B. Measuring potentially avoidable hospital readmissions. J Clin Epidemiol 2002;55(6):573-587. [Abstract] (View)
  • Li B, Evans D, Faris P, Dean S, Quan H. Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Services Research 2008;14(8):12. [Abstract] (View)
  • Lix L, Smith M, Pitz M, Ahmed R, Quon H, Griffith J, Turner D, Hong S, Prior H, Banerjee A, Koseva I, Kulbaba C. Cancer Data Linkage in Manitoba: Expanding the Infrastructure for Research. Winnipeg, MB: Manitoba Centre for Health Policy, 2016. [Report] [Summary] (View)
  • Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43(11):1130-1139. [Abstract] (View)
  • Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, Januel JM, Sundararajan V. 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):676-682. [Abstract] (View)
  • Quan H, Parsons GA, Ghali WA. Validity of information on comorbidity derived rom ICD-9-CCM administrative data. Med Care 2002;40(8):675-685. [Abstract] (View)
  • Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993;46(10):1075-1079. [Abstract] (View)
  • Romano PS, Roos LL, Jollis JG. Response: Further evidence concerning the use of a clinical comorbidity index with ICD-9-CM administrative data. J Clin Epidemiol 1993;46(10):1085-1090. [Abstract] (View)
  • Roos LL, Stranc L, James RC, Li J. Complications, comorbidities, and mortality: improving classification and prediction. Health Serv Res 1997;32(2):229-238. [Abstract] (View)
  • Schneeweiss S, Wang PS, Avorn J, Glynn RJ. Improved comorbidity adjustment for predicting mortality in Medicare populations. Health Serv Res 2003;38(4):1103-1120. [Abstract] (View)
  • Sundararajan V, Quan H, Halfon P, Fushimi K, Luthi JC, Burnand B, Ghali WA, International Methodology Consortium for Coded Health Information (IMECCHI). Cross-national comparative performance of three versions of the ICD-10 Charlson Index. Medical Care 2007;45(12):1210-1215. [Abstract] (View)

Keywords 

  • Charlson Index
  • comorbidity
  • complications
  • Disease
  • Health Measures
  • mortality


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