Classification schemes are formalized by regular expressions within the classcodes objects. These are computationally effective but sometimes hard to interpret. Use this function to list all codes identified for each group.
Arguments
- object
classcodes object
- coding
either a vector with codes from the original classification, or a name (character vector of length one) of a keyvalue object from package "decoder" (for example "icd10cm" or "atc")
- ...
summary.classcodes(): ignoredprint.summary.classcodes(): arguments passed totibble:::print.tbl()
- cc_args
List of named arguments passed to
set_classcodes()- x
output from
summary.classcodes()
Value
Methods primarily called for their side effects (printing to the screen) but with additional invisible objects returned:
summary.classcodes(): list with input argumentsobjectandcodingunchanged, as well as a data frame (summary) with columns for groups identified (group); the number of codes to be recognized for each group (n) and individual codes within each group (codes).print.summary.classcodes(): argumentxunchanged
See also
Other classcodes:
all_classcodes(),
as.data.frame.classified(),
classcodes,
codebook(),
print.classcodes(),
print.classified(),
set_classcodes(),
visualize.classcodes()
Examples
# summary.classcodes() ----------------------------------------------------
# Summarize all ICD-10-CM codes identified by the Elixhauser
# comorbidity classification
# See `?decoder::icd10cm` for details
summary(elixhauser, coding = "icd10cm")
#> Classification based on: icd10
#>
#> Summary of classcodes object
#>
#> Recognized codes per group:
#>
#> # A tibble: 31 × 3
#> group n codes
#> <chr> <int> <chr>
#> 1 AIDS/HIV 1 B20
#> 2 alcohol abuse 131 E52, F1010, F1011, F10120, F10121, F10129, F…
#> 3 blood loss anemia 1 D500
#> 4 cardiac arrhythmias 73 I441, I442, I4430, I4439, I456, I459, I470, …
#> 5 chronic pulmonary disease 69 I27812, I27822, I27832, I27892, I2792, J40, …
#> 6 coagulopathy 27 D65, D66, D67, D680, D681, D682, D68311, D68…
#> 7 congestive heart failure 36 I099, I1101, I1301, I1321, I255, I420, I425,…
#> 8 deficiency anemia 17 D508, D509, D510, D511, D512, D513, D518, D5…
#> 9 depression 31 F3130, F3131, F3132, F314, F3152, F320, F321…
#> 10 diabetes complicated 243 E1021, E1022, E1029, E10311, E10319, E103211…
#> # ℹ 21 more rows
#>
#> Use function visualize() for a graphical representation.
# Is there a difference if instead considering the Swedish ICD-10-SE?
# See `?decoder::icd10se` for details
summary(elixhauser, coding = "icd10se")
#> Classification based on: icd10
#>
#> Summary of classcodes object
#>
#> Recognized codes per group:
#>
#> # A tibble: 31 × 3
#> group n codes
#> <chr> <int> <chr>
#> 1 AIDS/HIV 22 B200, B201, B202, B203, B204, B205, B206, B2…
#> 2 alcohol abuse 30 E529, F100, F101, F102, F102A, F102B, F102X,…
#> 3 blood loss anemia 1 D500
#> 4 cardiac arrhythmias 45 I441, I441A, I441B, I442, I443, I456, I456A,…
#> 5 chronic pulmonary disease 57 I2782, I2792, J409, J410, J411, J418, J429, …
#> 6 coagulopathy 29 D659, D669, D679, D680, D681, D682, D683, D6…
#> 7 congestive heart failure 19 I099, I1101, I1301, I1321, I255, I420, I425,…
#> 8 deficiency anemia 17 D508, D509, D510, D511, D512, D513, D518, D5…
#> 9 depression 22 F2042, F313, F314, F3152, F320, F321, F322, …
#> 10 diabetes complicated 93 E102, E102A, E102B, E102C, E102W, E102X, E10…
#> # ℹ 21 more rows
#>
#> Use function visualize() for a graphical representation.
# Which ICD-9-CM diagnostics codes are recognized by Charlson according to
# Brusselears et al. 2017 (see `?charlson`)
summary(
charlson, coding = "icd9cmd",
cc_args = list(regex = "icd9_brusselaers")
)
#>
#> Summary of classcodes object
#>
#> Recognized codes per group:
#>
#> # A tibble: 13 × 3
#> group n codes
#> <chr> <int> <chr>
#> 1 cerebrovascular disease 69 430, 431, 4320, 4321, 4329, 43300, 43301…
#> 2 chronic pulmonary disease 48 4160, 4161, 4162, 4168, 4169, 490, 4910,…
#> 3 congestive heart failure 45 40200, 40201, 40210, 40211, 40290, 40291…
#> 4 dementia 21 2900, 29010, 29011, 29012, 29013, 29020,…
#> 5 diabetes complication 31 1960, 1961, 1962, 1963, 1965, 1966, 1968…
#> 6 diabetes without complication 40 25000, 25001, 25002, 25003, 25010, 25011…
#> 7 hemiplegia or paraplegia 628 1400, 1401, 1403, 1404, 1405, 1406, 1408…
#> 8 mild liver disease 67 40300, 40301, 40310, 40311, 40390, 40391…
#> 9 myocardial infarction 31 41000, 41001, 41002, 41010, 41011, 41012…
#> 10 peptic ulcer disease 39 34200, 34201, 34202, 34210, 34211, 34212…
#> 11 peripheral vascular disease 82 4400, 4401, 44020, 44021, 44022, 44023, …
#> 12 renal disease 50 0700, 0701, 07020, 07021, 07022, 07023, …
#> 13 rheumatic disease 179 7100, 7101, 7102, 7103, 7104, 7105, 7108…
#>
#> Use function visualize() for a graphical representation.
# print.summary.classcodes() ----------------------------------------------
# Print all 31 lines of the summarized Elixhauser classcodes object
print(
summary(elixhauser, coding = "icd10cm"),
n = 31
)
#> Classification based on: icd10
#>
#> Summary of classcodes object
#>
#> Recognized codes per group:
#>
#> # A tibble: 31 × 3
#> group n codes
#> <chr> <int> <chr>
#> 1 AIDS/HIV 1 B20
#> 2 alcohol abuse 131 E52, F1010, F1011, F10120, F10121, F101…
#> 3 blood loss anemia 1 D500
#> 4 cardiac arrhythmias 73 I441, I442, I4430, I4439, I456, I459, I…
#> 5 chronic pulmonary disease 69 I27812, I27822, I27832, I27892, I2792, …
#> 6 coagulopathy 27 D65, D66, D67, D680, D681, D682, D68311…
#> 7 congestive heart failure 36 I099, I1101, I1301, I1321, I255, I420, …
#> 8 deficiency anemia 17 D508, D509, D510, D511, D512, D513, D51…
#> 9 depression 31 F3130, F3131, F3132, F314, F3152, F320,…
#> 10 diabetes complicated 243 E1021, E1022, E1029, E10311, E10319, E1…
#> 11 diabetes uncomplicated 13 E1010, E1011, E109, E1100, E1101, E1110…
#> 12 drug abuse 361 F1110, F1111, F11120, F11121, F11122, F…
#> 13 fluid electrolyte disorders 15 E222, E860, E861, E869, E870, E871, E87…
#> 14 hypertension complicated 13 I1102, I119, I1201, I129, I1302, I13101…
#> 15 hypertension uncomplicated 1 I10
#> 16 hypothyroidism 18 E000, E001, E002, E009, E010, E011, E01…
#> 17 liver disease 56 B180, B181, B182, B188, B189, I8500, I8…
#> 18 lymphoma 373 C8100, C8101, C8102, C8103, C8104, C810…
#> 19 metastatic cancer 47 C770, C771, C772, C773, C774, C775, C77…
#> 20 obesity 7 E6601, E6609, E661, E662, E663, E668, E…
#> 21 other neurological disorders 115 G10, G110, G111, G112, G113, G1142, G11…
#> 22 paralysis 45 G041, G1141, G801, G802, G8100, G8101, …
#> 23 peptic ulcer disease 8 K257, K259, K267, K269, K277, K279, K28…
#> 24 peripheral vascular disorder 274 I700, I701, I70201, I70202, I70203, I70…
#> 25 psychoses 20 F200, F201, F202, F203, F205, F2081, F2…
#> 26 pulmonary circulation disorder 24 I2601, I2602, I2609, I2690, I2692, I269…
#> 27 renal failure 16 I1202, I13102, I13112, N181, N182, N183…
#> 28 rheumatoid arthritis 572 L940, L941, L943, M0500, M05011, M05012…
#> 29 solid tumor 485 C000, C001, C002, C003, C004, C005, C00…
#> 30 valvular disease 61 A5200, A5201, A5202, A5203, A5204, A520…
#> 31 weight loss 10 E40, E41, E42, E43, E440, E441, E45, E4…
#>
#> Use function visualize() for a graphical representation.