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Comorbidity Calculations and Tools for ICD-9 and ICD-10 Codes

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.

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icd

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

Introduction

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 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.

Features

  • 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, all via the ‘icd.data’ companion package.
  • 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

Examples

See also the vignettes and examples embedded in the help for each function for more. Here’s a taste:

# install.packages("icd")
library(icd)

# Typical diagnostic code data, with many-to-many relationship
patient_data
#>   visit_id  icd9
#> 1     1000 40201
#> 2     1000  2258
#> 3     1000  7208
#> 4     1000 25001
#> 5     1001 34400
#> 6     1001  4011
#> 7     1002  4011
#> 8     1000  <NA>

# get comorbidities using Quan's application of Deyo's Charlson comorbidity groups
comorbid_charlson(patient_data)
#>         MI   CHF   PVD Stroke Dementia Pulmonary Rheumatic   PUD LiverMild
#> 1000 FALSE  TRUE FALSE  FALSE    FALSE     FALSE     FALSE FALSE     FALSE
#> 1001 FALSE FALSE FALSE  FALSE    FALSE     FALSE     FALSE FALSE     FALSE
#> 1002 FALSE FALSE FALSE  FALSE    FALSE     FALSE     FALSE FALSE     FALSE
#>         DM  DMcx Paralysis Renal Cancer LiverSevere  Mets   HIV
#> 1000  TRUE FALSE     FALSE FALSE  FALSE       FALSE FALSE FALSE
#> 1001 FALSE FALSE      TRUE FALSE  FALSE       FALSE FALSE FALSE
#> 1002 FALSE FALSE     FALSE FALSE  FALSE       FALSE FALSE FALSE

# or go straight to the Charlson scores:
charlson(patient_data)
#> 1000 1001 1002 
#>    2    2    0

# plot summary of Uranium Cancer Registry sample data using AHRQ comorbidities
plot_comorbid(uranium_pathology)

Comorbodities 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(
  unname(unlist(icd_names_charlson)),
  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])))
  },
  character(2)
)
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")):

  • Introduction vignette("introduction", package = "icd")
  • Charlson scores vignette("charlson-scores", package = "icd")
  • Examples using ICD-10 codes vignette("ICD-10", package = "icd")
  • CMS Hierarchical Condition Codes (HCC) vignette("CMS-HCC", package = "icd")
  • Pediatric Complex Chronic Conditions (PCCC) vignette("PCCC", package = "icd")
  • Working with ICD code ranges vignette("ranges", package = "icd")
  • Comparing comorbidity maps vignette("compare-maps", package = "icd")
  • Paper detailing efficient matrix method of comorbidities vignette("efficiency", 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.

?comorbid
?comorbid_hcc
?explain_code
?is_valid

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. The current ICD-10-CM master list is the 2016 set. 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.

Functions in icd

Name Description
attr_short_diag Set short diagnosis flag in C++
expand_range Generate a set of codes between two ICD codes including encompassed children
expand_range.icd10cm Expand range of ICD-10 codes returning only defined codes in ICD-10-CM
get_icd10be2017 ICD-10-BE 2017
get_icd10be2017_pc ICD-10-BE 2017 procedure codes
apply_hier Apply hierarchy and choose naming for each comorbidity map
as.comorbidity_map Set the class of a named list to show it is a comorbidity map.
count_codes_wide Count ICD codes given in wide format
get_icd10cm2015 ICD-10-CM 2015
count_comorbid Count number of comorbidities per patient
as.decimal_diag Get or set whether ICD codes have have an attribute indicating 'short' or 'decimal' format
charlson Calculate Charlson Comorbidity Index (Charlson Score)
attr_decimal_diag Set ICD short-form diagnosis code attribute
convert Convert ICD data between formats and structures.
diff_comorbid show the difference between two comorbidity mappings
count_codes Count ICD codes or comorbidities for each patient
cr sequence columns of comorbidities
download_all_icd_data Download all the additional data at once
get_icd10be2014 Belgian ICD-10-BE
charlson_from_comorbid Calculate Charlson scores from precomputed Charlson comorbidities
comorbid Find comorbidities from ICD-9 codes.
get_icd10cm2015_pc ICD-10-CM Procedure codes for 2015
decimal_to_short Convert Decimal format ICD codes to short format
get_icd10cm2017_pc ICD-10-CM Procedure codes for 2017
get_icd10cm_available Get the ICD-10-CM versions available in this package
get_icd10cm2018 ICD-10-CM 2018
icd10_comorbid_reduce ICD-10 comorbidities by reducing problem size
icd10_map_ahrq_pcs AHRQ ICD-10-PCS categories
get_icd10be2014_pc ICD-10-BE 2014 procedure codes
comorbid_df_to_mat convert comorbidity matrix to data frame
get_icd10cm_latest The latest available version of ICD-10-CM in this package
guess_short Guess whether codes are short_code or decimal_code
get_icd10cm2018_pc ICD-10-CM Procedure codes for 2018
guess_version Guess version of ICD codes
get_cim10fr2019 Localised synonym for get_icd10fr2019, with French column names
icd9_map_hcc Medicare Hierarchical Condition Categories
icd9_map_quan_deyo Quan adaptation of Deyo/Charlson comorbidities
icd9_map_quan_elix Quan adaptation of Elixhauser comorbidities
icd9_map_pccc Pediatric Complex Chronic Conditions
is.icd_long_data Test for class describing patient data
set_icd10cm_active_year Get or set the annual version of ICD-10-CM to use
is_billable Check whether a code is billable according to ICD-9-CM or ICD-10-CM
get_defined Select only defined ICD codes
get_leaf Get billable ICD codes
get_valid invalid subset of decimal or short_code ICD-9 codes
set_icd_class Construct ICD-9 and ICD-10 data types
icd10_sub_chapters ICD-10 sub-chapters
[[.comorbidity_map Extract vector of codes from an ICD comorbidity map
subset extract subset(s) from ICD data
icd10cm2019 United States and Belgium ICD-10-CM
icd9cm2014_leaf The final ICD-9-CM list of leaf (‘billable’) codes
vermont_dx Hospital discharge data from Vermont
wide_to_long Convert ICD data from wide to long format
get_icd10cm2019_pc ICD-10-CM Procedure Codes
get_icd10who2008fr 2008 WHO ICD-10 data in French
icd9cm_billable Deprecated name for the list of annual ICD-9-CM billable/leaf descriptions
is_valid Check whether ICD-9 codes are syntactically valid
is_valid.default Test whether an ICD code is major
print.comorbidity_map Print a comorbidity map
print.icd9 Print ICD codes and comorbidity maps cleanly
uranium_pathology United States Transuranium & Uranium Registries
van_walraven Calculate van Walraven Elixhauser Score
children Get children of ICD codes
combine Combine ICD codes
comorbid_hcc Get Hierarchical Condition Codes (HCC)
get_icd10who2016 2016 WHO ICD-10 data
comorbid_pccc_dx Calculate pediatric complex chronic conditions (PCCC) comorbidities
comorbid_mat_to_df convert comorbidity data frame from matrix
explain_table Explain ICD-9 and ICD-10 codes in English from decimal (123.45 style), Tabulates the decimal format alongside converted non-decimal format.
condense Condense ICD-9 code by replacing complete families with parent codes
icd9MajMinToCode Convert mjr and mnr vectors to single code
expand_range_major Expand two major codes to a range
explain_code Explain ICD-9 and ICD-10 codes in English
explain_table_worker generate table of ICD code explanations
filter_poa Filters data frame based on present-on-arrival flag
generate_neds_pts Generate simulated 'NEDS' data for 'PCCC' and bigger wide data testing
icd9_chapters ICD-9 chapters
get_billable Get the subset of codes that are billable according to ICD-9-CM or ICD-10-CM
get_icd10cm2014 ICD-10-CM 2014
filter_valid Filter ICD codes by validity.
get_icd10cm2014_pc ICD-10-CM Procedure codes for 2014
icd9_map_ahrq AHRQ comorbidities
get_icd10cm_version Get the data for a given version (four-digit year) of ICD-10-CM
get_icd10cm2016_pc ICD-10-CM Procedure codes for 2016
get_icd10fr2019 French ICD-10-FR modification of WHO ICD-10 used in France
get_icd10cm2017 ICD-10-CM 2017
icd-package icd: Comorbidity Calculations and Tools for ICD-9 and ICD-10 Codes
icd9_map_elix Elixhauser comorbidities
get_icd9cm2014_leaf ICD-9-CM, just billable/leaf codes
get_invalid Get invalid ICD codes
long_to_wide Convert ICD data from long to wide format
icd9cm_hierarchy ICD-9-CM diagnosis codes including leaf nodes and branch names up to the three-digit codes.
is.icd9 Test presence of ICD classes
names_elix Comorbidity names
icd10_chapters ICD-10 chapters
icd9_map_single_ccs Clinical Classifications Software (CCS) for ICD9/10-CM
plot_comorbid Basic ordered bar plot showing counts of each comorbidity
icd9_sub_chapters ICD-9 sub-chapters
poa_choices Present-on-admission flags
wide_vs_long Set the ICD data structure class of a matrix or data.frame.
shortcode_icd9 set short_to_decimal attribute
with_icd10cm_version Evaluate code with a particular version of ICD-10-CM
sort_icd Sort or order ICD-9 or ICD-10 codes according to published sequence
is_defined Check whether ICD-9 codes exist
is_leaf Determine whether codes are billable leaf-nodes
set_icd_data_dir Set up the data download cache, give permission to download data
short_to_decimal Convert ICD codes from short to decimal forms
chapters_to_map Convert chapters to lists of codes for use as a comorbidity map
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Vignettes of icd

Name
CMS-HCC.Rmd
ICD-10.Rmd
PCCC.Rmd
charlson-scores.Rmd
compare-maps.Rmd
country-lang-vers-prebuilt.pdf
country-lang-vers.Rnw
custom-maps.Rmd
efficiency-prebuilt.pdf
efficiency.Rnw
gplv3.bib
icd.bib
icdjss.bib
icdpkg.bib
introduction.Rmd
jsslogo.jpg
other.bib
ranges.Rmd
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Details

License GPL-3
URL https://jackwasey.github.io/icd/
BugReports https://github.com/jackwasey/icd/issues
LinkingTo Rcpp (>= 0.12.3), RcppEigen
VignetteBuilder knitr
Classification/ACM-2012 Social and professional topics~Medical records, Applied computing~Health care information systems, Applied computing~Health informatics, Applied computing~Bioinformatics
Copyright See file (inst/)COPYRIGHTS
Encoding UTF-8
Language en-US
LazyData true
LazyDataCompression xz
RoxygenNote 6.1.1.9000
NeedsCompilation yes
Packaged 2019-05-06 21:38:51 UTC; waseyj
Repository CRAN
Date/Publication 2019-05-07 07:50:13 UTC

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