This function generates a list of DuckDB tibbles representing the Danish health registers and the data necessary to run the algorithm. The dataset contains individuals who should not be included in the final classified cohort.
Value
A named list of 9 duckplyr::duckdb_tibble() objects, each representing a
different health register: bef, lmdb, lpr_adm, lpr_diag,
kontakter, diagnoser, sysi, sssy, and lab_forsker.
Details
The generated data is used in testthat tests to ensure the algorithm
behaves as expected under a wide range of conditions, but it is also intended
to be explored by users to better understand how the algorithm logic works
and to be shown in the documentation.
Examples
non_cases()
#> $bef
#> # A duckplyr data frame: 3 variables
#> pnr koen foed_dato
#> <chr> <int> <chr>
#> 1 nc_pcos_1 2 19800101
#> 2 nc_pcos_2 2 19800101
#> 3 nc_pcos_3 2 19800101
#> 4 nc_preg_1 2 19800101
#> 5 nc_preg_2 2 19800101
#> 6 nc_preg_3 2 19800101
#> 7 nc_preg_4 2 19800101
#> 8 164409653234 1 19230301
#> 9 952443913885 2 19330321
#> 10 679714832266 2 19591020
#> # ℹ more rows
#>
#> $diagnoser
#> # A duckplyr data frame: 4 variables
#> dw_ek_kontakt diagnosekode diagnosetype senere_afkraeftet
#> <chr> <chr> <chr> <chr>
#> 1 1 DI10 A Nej
#> 2 2 DO00 A Nej
#> 3 3 DZ33 A Nej
#> 4 942848630572354208 DZ39321P A Ja
#> 5 069594786879610784 DQ447 B Nej
#> 6 103668538248089087 DQ438P B Ja
#> 7 568625840943904921 DS78 B Nej
#> 8 849133686529524253 DX6701 B Nej
#> 9 371073944504254886 DE470 A Nej
#> 10 844730233259097607 DC795E B Nej
#> # ℹ more rows
#>
#> $kontakter
#> # A duckplyr data frame: 4 variables
#> cpr dw_ek_kontakt hovedspeciale_ans dato_start
#> <chr> <chr> <chr> <chr>
#> 1 nc_pcos_1 1 medicinsk endokrinologi 20210101
#> 2 nc_pcos_2 1 medicinsk endokrinologi 20190101
#> 3 nc_pcos_3 1 medicinsk endokrinologi 20190101
#> 4 nc_preg_3 1 abc 20200101
#> 5 nc_preg_4 1 abc 20200101
#> 6 nc_preg_3 2 abc 20200101
#> 7 nc_preg_4 3 abc 20200101
#> 8 164409653234 942848630572354208 Almen medicin 20150812
#> 9 952443913885 069594786879610784 Børne- og ungdomspsykiatri 20150710
#> 10 679714832266 103668538248089087 Neurologi 20221028
#> # ℹ more rows
#>
#> $lab_forsker
#> # A duckplyr data frame: 4 variables
#> patient_cpr samplingdate analysiscode value
#> <chr> <chr> <chr> <dbl>
#> 1 nc_pcos_1 20210101 NPU27300 48
#> 2 nc_pcos_2 20190101 NPU03835 6.5
#> 3 nc_pcos_3 20190101 NPU03835 6.5
#> 4 nc_preg_1 20170301 NPU27300 48
#> 5 nc_preg_2 20180301 NPU03835 6.5
#> 6 nc_preg_3 20190301 NPU03835 6.5
#> 7 nc_preg_4 20200301 NPU27300 48
#> 8 164409653234 20171105 NPU15168 86.4
#> 9 952443913885 20110925 NPU86660 1.43
#> 10 679714832266 20211015 NPU81556 74.9
#> # ℹ more rows
#>
#> $lmdb
#> # A duckplyr data frame: 6 variables
#> pnr volume eksd atc apk indo
#> <chr> <dbl> <chr> <chr> <dbl> <chr>
#> 1 nc_pcos_1 10 20210101 A10BA02 5 0000276
#> 2 nc_pcos_2 10 20190101 A10BA02 5 0000276
#> 3 nc_pcos_3 10 20190101 A10BA02 5 0000276
#> 4 nc_preg_1 10 20180101 A10 5 0000000
#> 5 nc_preg_2 10 20180101 A10 5 0000000
#> 6 nc_preg_3 10 20200101 A10 5 0000000
#> 7 nc_preg_4 10 20200101 A10 5 0000000
#> 8 164409653234 9.24 20240410 R06AX17 5.05 9477070
#> 9 952443913885 3.93 20180228 D07AC08 5.39 2229609
#> 10 679714832266 3.14 20120310 A08AA09 9.19 6934228
#> # ℹ more rows
#>
#> $lpr_adm
#> # A duckplyr data frame: 4 variables
#> pnr c_spec recnum d_inddto
#> <chr> <chr> <chr> <chr>
#> 1 nc_pcos_1 08 1 20180101
#> 2 nc_pcos_2 08 1 20170101
#> 3 nc_pcos_3 08 1 20170101
#> 4 nc_preg_1 08 1 20180101
#> 5 nc_preg_2 08 1 20180101
#> 6 nc_preg_1 08 2 20180101
#> 7 nc_preg_2 08 3 20180101
#> 8 164409653234 46 942848630572354208 20150812
#> 9 952443913885 58 069594786879610784 20150710
#> 10 679714832266 54 103668538248089087 20221028
#> # ℹ more rows
#>
#> $lpr_diag
#> # A duckplyr data frame: 3 variables
#> recnum c_diag c_diagtype
#> <chr> <chr> <chr>
#> 1 1 149 A
#> 2 2 DO00 A
#> 3 3 DZ33 A
#> 4 942848630572354208 E9511 A
#> 5 069594786879610784 08459 A
#> 6 103668538248089087 31502 B
#> 7 568625840943904921 59401 B
#> 8 849133686529524253 31154 B
#> 9 371073944504254886 Y9001 A
#> 10 844730233259097607 63000 A
#> # ℹ more rows
#>
#> $sssy
#> # A duckplyr data frame: 4 variables
#> pnr barnmak speciale honuge
#> <chr> <int> <chr> <chr>
#> 1 nc_pcos_1 0 53 2101
#> 2 nc_pcos_2 0 53 1901
#> 3 nc_pcos_3 0 53 1901
#> 4 nc_preg_1 0 53 2001
#> 5 nc_preg_2 0 53 2001
#> 6 nc_preg_3 0 53 2001
#> 7 nc_preg_4 0 53 2001
#> 8 164409653234 0 15168 2315
#> 9 952443913885 1 86660 0523
#> 10 679714832266 0 81556 1141
#> # ℹ more rows
#>
#> $sysi
#> # A duckplyr data frame: 4 variables
#> pnr barnmak speciale honuge
#> <chr> <int> <chr> <chr>
#> 1 nc_pcos_1 0 53 2101
#> 2 nc_pcos_2 0 53 1901
#> 3 nc_pcos_3 0 53 1901
#> 4 nc_preg_1 0 53 2001
#> 5 nc_preg_2 0 53 2001
#> 6 nc_preg_3 0 53 2001
#> 7 nc_preg_4 0 53 2001
#> 8 164409653234 0 15168 9023
#> 9 952443913885 1 86660 9641
#> 10 679714832266 0 81556 9151
#> # ℹ more rows
#>