I am trying to score each patient in my data based using their ICD10 codes.
library(dplyr)
library(comorbidity)
set.seed(1)
x <- data.frame(
pat_id = sample(100:999, size = 300, replace = TRUE),
code = sample_diag(n = 300)
)
I can successfully create the Charlson scores and the output contains a column with the original patient ids pat_id
charlson <- comorbidity(x = x, id = "pat_id", code = "code", map = "charlson_icd10_quan", assign0 = TRUE, tidy.codes = TRUE)
I've created a row number ID so that I can join to the scores output
charlson_ids <- charlson %>%
mutate(id = row_number()) %>%
select(id,pat_id)
When I convert the charlson index to scores there is no patient id so I am assuming row 1 in the output from charlson above ties to row 1 in scores below??
scores <- score(charlson, weights = NULL, assign0 = FALSE)
scores_df <- data.frame(scores) %>%
mutate(id = row_number())
combined <- charlson_ids %>%
inner_join(scores_df, by = c("id"="id")) %>%
select(-id)
If anyone can suggest a more succinct way to get from individual ICD-10 codes per patient to a comorbidity score per patient I would be grateful for any feedback.
the score() function returns a single value per row of charlson (the output of the comorbidity() function).
Therefore, you can simplify the above as:
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
library(comorbidity)
set.seed(1)
x <- data.frame(
pat_id = sample(seq(5), size = 100, replace = TRUE),
code = sample_diag(n = 100)
)
charlson <- comorbidity(x = x, id = "pat_id", code = "code", map = "charlson_icd10_quan", assign0 = TRUE, tidy.codes = TRUE)
charlson_with_score <- mutate(charlson, score = score(charlson, weights = NULL, assign0 = FALSE))
charlson_with_score
#> pat_id ami chf pvd cevd dementia copd rheumd pud mld diab diabwc hp rend canc
#> 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0
#> 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> 4 4 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> 5 5 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> msld metacanc aids score
#> 1 0 0 0 2
#> 2 0 0 0 1
#> 3 1 0 0 2
#> 4 0 0 0 2
#> 5 0 0 1 2
Created on 2022-03-15 by the reprex package (v2.0.1)
Alternatively, you can pipe all the way through:
x %>%
comorbidity(id = "pat_id", code = "code", map = "charlson_icd10_quan", assign0 = TRUE, tidy.codes = TRUE) %>%
mutate(score = score(x = ., weights = NULL, assign0 = FALSE))
#> pat_id ami chf pvd cevd dementia copd rheumd pud mld diab diabwc hp rend canc
#> 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0
#> 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> 4 4 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> 5 5 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> msld metacanc aids score
#> 1 0 0 0 2
#> 2 0 0 0 1
#> 3 1 0 0 2
#> 4 0 0 0 2
#> 5 0 0 1 2
...but that's just a matter of style, as you can see the results are the same.
Alessandro