Fast comorbidities from ICD-9 and ICD-10 codes, decoding, manipulation and validation


Calculate comorbidities, medical risk scores, and work very quickly and precisely with ICD-9 and ICD-10 codes. This package enables a work flow from raw tables of ICD codes in hospital databases to comorbidities. ICD-9 and ICD-10 comorbidity mappings from Quan (Deyo and Elixhauser versions), Elixhauser and AHRQ included. Common ambiguities and code formats are handled. Comorbidity computation includes Hierarchical Condition Codes, and an implementation of AHRQ Clinical Classifications. Risk scores include those of Charlson and van Walraven. US Clinical Modification, Word Health Organization, Belgian and French ICD-10 codes are supported, most of which are downloaded on demand.

icd is used by many researchers around the world who work in public health, epidemiology, clinical research, nutrition, journalism, health administration, insurance, and more. I’m grateful for contact from people in these fields for their feedback and code contributions, and I’m pleased to say that icd has been used in works like the Pulitzer finalist work on maternal death by ProPublica.


  • find comorbidities of patients based on ICD-9 or ICD-10 codes, e.g. Cancer, Heart Disease
    • several standard mappings of ICD codes to comorbidities are included (Quan, Deyo, Elixhauser, AHRQ, PCCC)
    • very fast assignment of ICD codes to comorbidities (using novel matrix multiplication algorithm and C++ internally – see ‘efficiency’ vignette for details)
  • use your existing wide or long data format, icd can guess which columns are ICD-9 or ICD-10 codes.
  • explain and summarize groups of ICD codes in natural language, using ICD editions from the WHO, USA, France and Belgium. Many different annual editions of these data are available, and these may be downloaded automatically when used, or in bulk with download_all_icd_data().
  • Charlson and Van Walraven score calculations
  • Hierarchical Condition Codes (HCC) from CMS
  • Clinical Classifications Software (CCS) comorbidities from AHRQ
  • Pediatric Complex Chronic Condition comorbidities
  • AHRQ ICD-10 procedure code classification
  • correct conversion between different representations of ICD codes, with and without a decimal points, leading and trailing characters (this is not trivial for ICD-9-CM). ICD-9 to ICD-10 cross-walk is not yet implemented
  • comprehensive test suite to increase confidence in accurate processing of ICD codes

Comorbidities example: make “Table 1” summary data

A common requirement for medical research involving patients is determining new or existing comorbidities. This is often reported in Table 1 of research papers to demonstrate the similarity or differences of groups of patients. This package is focussed on fast and accurate generation of this comorbidity information from raw lists of ICD-9 and ICD-10 codes.

Here we are using the US National Hospital Discharge Survey 2010 data from the nhds package. For the sake of example, let us compare emergency to other admissions. A real table would have more patient features; this primarily demonstrates how to get ICD codes into your Table 1.

NHDS 2010 comorbidities to demonstrate Table One creation. Presented as counts (percentage prevalence in group).

nhds <- nhds::nhds2010
# get the comorbidities using the Quan-Deyo version of the Charlson categories
cmb <- icd::comorbid_quan_deyo(nhds, abbrev_names = FALSE)
nhds <- cbind(nhds, cmb, stringsAsFactors = FALSE)
Y <- nhds$adm_type == "emergency"
tab_dat <- vapply(
  function(x) {
    c(sprintf("%i (%.2f%%)", 
              sum(nhds[Y, x]), 
              100 * mean(nhds[Y, x])),
      sprintf("%i (%.2f%%)",
              sum(nhds[!Y, x]),
              100 * mean(nhds[!Y, x])))
knitr::kable(t(tab_dat), col.names = c("Emergency", "Not emergency"))
Emergency Not emergency
Myocardial Infarction 2707 (3.69%) 1077 (1.38%)
Congestive Heart Failure 12339 (16.84%) 5628 (7.19%)
Periphral Vascular Disease 3798 (5.18%) 3042 (3.89%)
Cerebrovascular Disease 5329 (7.27%) 2748 (3.51%)
Dementia 2175 (2.97%) 728 (0.93%)
Chronic Pulmonary Disease 11989 (16.36%) 6762 (8.64%)
Connective Tissue Disease-Rheumatic Disease 1527 (2.08%) 1131 (1.44%)
Peptic Ulcer Disease 1044 (1.42%) 473 (0.60%)
Mild Liver Disease 2030 (2.77%) 1011 (1.29%)
Diabetes without complications 14399 (19.65%) 9125 (11.66%)
Diabetes with complications 2719 (3.71%) 1449 (1.85%)
Paraplegia and Hemiplegia 1386 (1.89%) 852 (1.09%)
Renal Disease 9322 (12.72%) 4604 (5.88%)
Cancer 2724 (3.72%) 3496 (4.47%)
Moderate or Severe Liver Disease 893 (1.22%) 352 (0.45%)
Metastatic Carcinoma 2100 (2.87%) 1663 (2.12%)
HIV/AIDS 0 (0.00%) 0 (0.00%)

How to get help

Look at the help files for details and examples of almost every function in this package. There are several vignettes showing the main features (See list with vignette(package = "icd")):

Many users have emailed me directly for help, and I’ll do what I can, but it is often better to examine or add to the list of issues so we can help each other. Advanced users may look at the source code, particularly the extensive test suite which exercises all the key functions.

ICD-9 codes

ICD-9 codes are still in heavy use around the world, particularly in the USA where the ICD-9-CM (Clinical Modification) was in widespread use until the end of 2015. ICD-10 has been used worldwide for reporting cause of death for more than a decade, and ICD-11 is due to be released in 2019. ICD-10-CM is now the primary coding scheme for US hospital admission and discharge diagnoses used for regulatory purposes and billing. A vast amount of electronic patient data is recorded with ICD-9 codes of some kind: this package enables their use in R alongside ICD-10.

ICD-9 codes are not numbers, and great care is needed when matching individual codes and ranges of codes. It is easy to make mistakes, hence the need for this package. ICD-9 codes can be presented in short 5 character format, or decimal format, with a decimal place separating the code into two groups. There are also codes beginning with V and E which have different validation rules. Zeroes after a decimal place are meaningful, so numeric ICD-9 codes cannot be used in most cases. In addition, most clinical databases contain invalid codes, and even decimal and non-decimal format codes in different places. This package primarily deals with ICD-9-CM (Clinical Modification) codes, but should be applicable or easily extendable to the original WHO ICD-9 system.

ICD-10 codes

ICD-10 has a somewhat simpler format, with consistent use of a letter, then two alphanumeric characters. However, especially for ICD-10-CM, there are a multitude of qualifiers, e.g. specifying recurrence, laterality, which vastly increase the number of possible codes. This package recognizes validity of codes by syntax alone, or whether the codes appear in a canonical list. There is not yet the capability of converting between ICD-9 and ICD-10, but comorbidities can be generated from older ICD-9 codes and newer ICD-10 codes in parallel, and the comorbidities can then be compared.