Description Usage Format See Also Examples
Provides lookup tables for use with Ambulatory care sensitive analyses.
1 |
data frame with 13 rows and 12 fields
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | Observations: 13
Variables: 12
$ cat1 <chr> "Cardiovascular diseases", "Cardiovascular diseases", "Cardiovascular diseases", "Card...
$ cat2 <chr> "Atrial Fibrillation", "Angina", "Chronic heart disease", "Congestive heart failure", ...
$ condition_description <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
$ age <chr> "All ages", "All ages", "All ages", "All ages", "All ages", "All ages", "All ages", "A...
$ primary_diagnosis <chr> "I48", "I20", "I25", "I50;I11.0;J81X;I13.0", "I10X;I11.9", "D51-D52;D50.1;D50.8;D50.9"...
$ secondary_diagnoses <chr> NA, NA, NA, NA, NA, NA, "-D57", NA, NA, NA, NA, "J41-44;J47", NA
$ procedures <chr> NA, "-A-W;-X0-X5", "-A-W;-X0-X5", "-K0-K4;-K50;-K52;-K55-K57;-K60-61;-K67-69;-K71;-K73...
$ prim_diag_regexp <chr> "I48", "I20", "I25", "I50|I110|J81X|I130", "I10X|I119", "D5[12]|D50[189]", "B18[01]", ...
$ proc_regex <chr> NA, "[A-W]|X[0-5]", "[A-W]|X[0-5]", "K[0-4]|K5[025-7]|K6[016-9]|K7[134]", "K[0-4]|K5[0...
$ sec_diag_regex <chr> NA, NA, NA, NA, NA, NA, "-D57", NA, NA, NA, NA, "J4[12347]", NA
$ condition_uid <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13
$ version <chr> "ccg_ois_26", "ccg_ois_26", "ccg_ois_26", "ccg_ois_26", "ccg_ois_26", "ccg_ois_26", "c...
|
Other ambulatory care sensitive datasets: ac_attribution
,
ac_versions
, acs_datasets
,
lu_acc_icd10
1 2 3 4 5 6 7 8 | if (isNamespaceLoaded("dplyr")) {
require("dplyr")
aafractions.ncc::ac_conditions %>%
mutate_if(is.character, as.factor) %>%
select(-starts_with("condition_"), -starts_with("primary")) %>%
summary(16)
}
|
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