library(codemapper)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
all_lkps_maps_dummy <- build_all_lkps_maps_dummy()ICD10 codes may be recorded as either ‘ICD10_CODE’ or ‘ALT_CODE’ format. For example, ‘E10.9’ (Type 1 diabetes mellitus without complications) is recorded as ‘E109’ in ‘ALT_CODE’ format.
Both formats are provided in the ICD10 lookup table:
all_lkps_maps_dummy$icd10_lkp
#> # A tibble: 197 × 13
#> .rowid ICD10_CODE ALT_CODE USAGE USAGE_UK DESCRIPTION MODIFIER_4 MODIFIER_5
#> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 1 A00 A00 DEFAULT 3 Cholera NA NA
#> 2 2 A00.0 A000 DEFAULT 3 Cholera du… NA NA
#> 3 3 A00.1 A001 DEFAULT 3 Cholera du… NA NA
#> 4 4 A00.9 A009 DEFAULT 3 Cholera, u… NA NA
#> 5 5 A01.0 A010 DEFAULT 3 Typhoid fe… NA NA
#> 6 6 A02 A02 DEFAULT 3 Other salm… NA NA
#> 7 7 A02.0 A020 DEFAULT 3 Salmonella… NA NA
#> 8 8 A02.1 A021 DEFAULT 3 Salmonella… NA NA
#> 9 9 A02.2 A022 DEFAULT 3 Localized … NA NA
#> 10 10 A02.8 A028 DEFAULT 3 Other spec… NA NA
#> # … with 187 more rows, and 5 more variables: QUALIFIERS <chr>,
#> # GENDER_MASK <chr>, MIN_AGE <chr>, MAX_AGE <chr>, TREE_DESCRIPTION <chr>However only the ‘ALT_CODE’ format is used in all other mapping tables that include ICD10 codes:
all_lkps_maps_dummy$icd9_icd10 %>%
select(ICD9,
ICD10,
DESCRIPTION_ICD10)
#> # A tibble: 47 × 3
#> ICD9 ICD10 DESCRIPTION_ICD10
#> <chr> <chr> <chr>
#> 1 0020 A010 Typhoid fever
#> 2 0341 A38X Scarlet fever
#> 3 218 D250 Submucous leiomyoma of uterus
#> 4 218 D251 Intramural leiomyoma of uterus
#> 5 218 D252 Subserosal leiomyoma of uterus
#> 6 218 D259 Leiomyoma of uterus, unspecified
#> 7 2890 D751 Secondary polycythaemia
#> 8 NA E100 Insulin-dependent diabetes mellitus with coma
#> 9 NA E101 Insulin-dependent diabetes mellitus with ketoacidosis
#> 10 NA E102 Insulin-dependent diabetes mellitus with renal complications
#> # … with 37 more rowsSearching for ICD10 codes in ‘ICD10_FORMAT’ will yield no results:
# ICD10_CODE format - no codes found
lookup_codes(codes = "E10.9",
code_type = "icd10",
all_lkps_maps = all_lkps_maps_dummy,
unrecognised_codes = "warning")
#> Warning in handle_unrecognised_codes(unrecognised_codes = unrecognised_codes, :
#> The following 1 codes were not found for 'icd10' in table 'icd10_lkp': 'E10.9'
#> No matching codes found. Returning `NULL`
#> NULL
# ALT_CODE format - now recognised
lookup_codes(codes = "E109",
code_type = "icd10",
all_lkps_maps = all_lkps_maps_dummy,
unrecognised_codes = "warning")
#> # A tibble: 1 × 3
#> code description code_type
#> <chr> <chr> <chr>
#> 1 E109 Type 1 diabetes mellitus Without complications icd10Use reformat_icd10_codes() to convert from one form to the other:
reformat_icd10_codes(icd10_codes = c("E10.9"),
all_lkps_maps = all_lkps_maps_dummy,
input_icd10_format = "ICD10_CODE",
output_icd10_format = "ALT_CODE") %>%
lookup_codes(code_type = "icd10",
all_lkps_maps = all_lkps_maps_dummy)
#> # A tibble: 1 × 3
#> code description code_type
#> <chr> <chr> <chr>
#> 1 E109 Type 1 diabetes mellitus Without complications icd10While for many ICD10 codes simply removing the ‘.’ will correctly convert from ‘ICD10_CODE’ format to ‘ALT_CODE’ format, this approach will not work in the following cases:
Undivided 3 character ICD10 codes, which have an appended ‘X’ character in ‘ALT_CODE’ format. For example, ‘I10’ for Essential (primary) hypertension is recorded as ‘I10X’.
reformat_icd10_codes(icd10_codes = c("I10"),
all_lkps_maps = all_lkps_maps_dummy,
input_icd10_format = "ICD10_CODE",
output_icd10_format = "ALT_CODE") %>%
lookup_codes(code_type = "icd10",
all_lkps_maps = all_lkps_maps_dummy)
#> # A tibble: 1 × 3
#> code description code_type
#> <chr> <chr> <chr>
#> 1 I10X Essential (primary) hypertension icd10ICD10 codes with a 5th character modifier. In these cases, a single code in ‘ICD10_CODE’ format will map to multiple codes in ’ALT_CODE`format and vice versa.
# ICD10_CODE to ALT_CODE
m90_alt_code <- reformat_icd10_codes(icd10_codes = c("M90.0"),
all_lkps_maps = all_lkps_maps_dummy,
input_icd10_format = "ICD10_CODE",
output_icd10_format = "ALT_CODE") %>%
lookup_codes(code_type = "icd10",
all_lkps_maps = all_lkps_maps_dummy)
#> The following 1 input ICD10 codes do not have a 1-to-1 ICD10_CODE-to-ALT_CODE mapping: 'M90.0'. There will therefore be *more* output than input codes
m90_alt_code
#> # A tibble: 11 × 3
#> code description code_type
#> <chr> <chr> <chr>
#> 1 M900 Tuberculosis of bone icd10
#> 2 M9000 Tuberculosis of bone Multiple sites icd10
#> 3 M9001 Tuberculosis of bone Shoulder region icd10
#> 4 M9002 Tuberculosis of bone Upper arm icd10
#> 5 M9003 Tuberculosis of bone Forearm icd10
#> 6 M9004 Tuberculosis of bone Hand icd10
#> 7 M9005 Tuberculosis of bone Pelvic region and thigh icd10
#> 8 M9006 Tuberculosis of bone Lower leg icd10
#> 9 M9007 Tuberculosis of bone Ankle and foot icd10
#> 10 M9008 Tuberculosis of bone Other icd10
#> 11 M9009 Tuberculosis of bone Site unspecified icd10
# ALT_CODE to ICD10_CODE
reformat_icd10_codes(
icd10_codes = m90_alt_code$code,
all_lkps_maps = all_lkps_maps_dummy,
input_icd10_format = "ALT_CODE",
output_icd10_format = "ICD10_CODE"
)
#> The following 11 input ICD10 codes do not have a 1-to-1 ICD10_CODE-to-ALT_CODE mapping: 'M900', 'M9000', 'M9001', 'M9002', 'M9003', 'M9004', 'M9005', 'M9006', 'M9007', 'M9008', 'M9009'. There will therefore be *fewer* output than input codes
#> [1] "M90.0"