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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.

Usage

# S3 method for classcodes
summary(object, coding, ..., cc_args = list())

# S3 method for summary.classcodes
print(x, ...)

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(): ignored

  • print.summary.classcodes(): arguments passed to tibble:::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 arguments object and coding unchanged, 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(): argument x unchanged

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.