The medicalcoder package implements several variants of
the Charlson comorbidities algorithm.
charslon_deyo1992: Deyo’s original set of codes (Deyo, Cherkin, and Ciol 1992; Quan et al.
2005)charlson_quan2005 and charlson_quan2011:
Codes and index scoring (Quan et al. 2005,
2011)charlson_cdmf2019: (Glasheen et
al. 2019)End users can access the lookup tables for the mapping between ICD-9
and ICD-10 codes to conditions and the index scoring in
data.frames from the get_charlson_codes() and
get_charlson_index_scores() calls respectively.
str(get_charlson_codes())
## 'data.frame': 7410 obs. of 9 variables:
## $ icdv : int 9 9 9 9 9 9 9 9 9 9 ...
## $ dx : int 1 1 1 1 1 1 1 1 1 1 ...
## $ full_code : chr "003.1" "007.2" "007.4" "010" ...
## $ code : chr "0031" "0072" "0074" "010" ...
## $ condition : chr "aids" "aids" "aids" "aids" ...
## $ charlson_cdmf2019: int 1 1 1 1 1 1 1 1 1 1 ...
## $ charlson_deyo1992: int 0 0 0 0 0 0 0 0 0 0 ...
## $ charlson_quan2005: int 0 0 0 0 0 0 0 0 0 0 ...
## $ charlson_quan2011: int 0 0 0 0 0 0 0 0 0 0 ...
str(get_charlson_index_scores())
## 'data.frame': 21 obs. of 6 variables:
## $ condition_description: chr "AIDS" "AIDS/HIV" "HIV infection, no AIDS" "Any malignancy" ...
## $ condition : chr "aids" "aidshiv" "hiv" "mal" ...
## $ charlson_cdmf2019 : int 6 NA 3 2 1 1 1 1 2 1 ...
## $ charlson_quan2011 : int NA 4 NA 2 0 1 2 2 1 0 ...
## $ charlson_quan2005 : int NA 6 NA 2 1 1 1 1 2 1 ...
## $ charlson_deyo1992 : int NA 6 NA 2 1 1 1 1 2 1 ...Example: applying the Quan et al.
(2005) variant of the Charlson comorbidities to the
mdcr data is be done as follows.
mdcr_results <-
comorbidities(
data = mdcr,
id.vars = "patid",
icdv.var = "icdv",
icd.codes = "code",
dx.var = "dx",
flag.method = "current",
poa = 1,
method = "charlson_quan2005"
)The return object is a data.frame with 0/1 integer
indicator columns for the relevant conditions, the id.vars (if
applicable), age_score (if age, in years, is supplied),
num_cmrb the number of comorbidities,
cmrb_flag a 0/1 indicator for presence of at least one
comorbidity, and cci the Charlson Comorbidity Index.
str(mdcr_results)
## Classes 'medicalcoder_comorbidities' and 'data.frame': 38262 obs. of 22 variables:
## $ patid : int 10000 10002 10005 10006 10008 10010 10014 10015 10017 10018 ...
## $ aidshiv : int 0 0 0 0 0 0 0 0 0 0 ...
## $ mal : int 0 0 1 0 0 0 0 0 0 0 ...
## $ cebvd : int 0 0 0 0 0 0 0 0 0 0 ...
## $ copd : int 1 0 0 0 0 0 0 0 0 0 ...
## $ chf : int 0 0 0 0 0 0 0 0 0 0 ...
## $ dem : int 0 0 0 0 0 0 0 0 0 0 ...
## $ dmc : int 0 0 0 0 0 0 0 0 0 0 ...
## $ dm : int 0 0 0 0 0 0 0 0 0 0 ...
## $ hp : int 0 0 0 0 0 0 0 1 0 0 ...
## $ mld : int 0 0 0 0 0 0 0 0 0 0 ...
## $ msld : int 0 0 0 0 0 0 0 0 0 0 ...
## $ mst : int 0 0 1 0 0 0 0 0 0 0 ...
## $ mi : int 0 0 0 0 0 0 0 0 0 0 ...
## $ pud : int 0 0 0 0 0 0 0 0 0 0 ...
## $ pvd : int 0 0 0 0 0 0 0 0 0 0 ...
## $ rnd : int 0 0 0 0 0 0 0 0 0 0 ...
## $ rhd : int 0 0 0 0 0 0 0 0 0 0 ...
## $ num_cmrb : int 1 0 2 0 0 0 0 1 0 0 ...
## $ cmrb_flag: int 1 0 1 0 0 0 0 1 0 0 ...
## $ cci : int 1 0 6 0 0 0 0 2 0 0 ...
## $ age_score: int NA NA NA NA NA NA NA NA NA NA ...
## - attr(*, "method")= chr "charlson_quan2005"
## - attr(*, "id.vars")= chr "patid"
## - attr(*, "flag.method")= chr "current"Call summary() on the return object for a list of
summary objects. These can be used to generate output tables to the end
user’s liking.
str(
summary(mdcr_results)
)
## List of 3
## $ conditions :'data.frame': 22 obs. of 4 variables:
## ..$ condition_description: chr [1:22] "AIDS/HIV" "Any malignancy" "Cerebrovascular disease" "Chronic pulmonary disease" ...
## ..$ condition : chr [1:22] "aidshiv" "mal" "cebvd" "copd" ...
## ..$ count : num [1:22] 7 2577 411 3415 684 ...
## ..$ percent : num [1:22] 0.0183 6.7351 1.0742 8.9253 1.7877 ...
## $ age_summary :'data.frame': 1 obs. of 3 variables:
## ..$ age_score: Factor w/ 0 levels: NA
## ..$ count : int 38262
## ..$ percent : num 100
## $ index_summary:'data.frame': 1 obs. of 5 variables:
## ..$ min : int 0
## ..$ q1 : num 0
## ..$ median: num 0
## ..$ q3 : num 1
## ..$ max : int 12x <- summary(mdcr_results)$conditions[, c("condition_description", "count", "percent")]
tab <-
kableExtra::kbl(
x = x,
format = "html",
caption = "Counts and percentages of patients in the mdcr example data sets with the @quan2005 comorbidities.",
col.names = c("", "Count", "Percentage"),
digits = 3
)
tab <- kableExtra::pack_rows(tab, group_label = "Comorbidity", start_row = 1, end_row = 17)
tab <- kableExtra::pack_rows(tab, group_label = "Total Comorbidities", start_row = 18, end_row = nrow(x))
tab| Count | Percentage | |
|---|---|---|
| Comorbidity | ||
| AIDS/HIV | 7 | 0.018 |
| Any malignancy | 2577 | 6.735 |
| Cerebrovascular disease | 411 | 1.074 |
| Chronic pulmonary disease | 3415 | 8.925 |
| Congestive heart failure | 684 | 1.788 |
| Dementia | 13 | 0.034 |
| Diabetes with chronic complications | 13 | 0.034 |
| Diabetes without chronic complications | 445 | 1.163 |
| Hemiplegia or paraplegia | 1177 | 3.076 |
| Liver disease, mild | 632 | 1.652 |
| Liver disease, moderate to severe | 206 | 0.538 |
| Metastatic solid tumor | 453 | 1.184 |
| Myocardial infarction | 10 | 0.026 |
| Peptic ulcer disease | 45 | 0.118 |
| Peripheral vascular disease | 217 | 0.567 |
| Renal disease | 877 | 2.292 |
| Rheumatic disease | 136 | 0.355 |
| Total Comorbidities | ||
| >= 1 | 9789 | 25.584 |
| >= 2 | 1368 | 3.575 |
| >= 3 | 138 | 0.361 |
| >= 4 | 20 | 0.052 |
| >= 5 | 3 | 0.008 |