Adding names to longitudinal and service sector codes
tutorial_add_info.RmdIntro
This tutorial show how to append additional information to a longitudinal or service-sector table in bigquerry.
Information to add includes, name of the medical codes in English, name for the type of visit, name for the type of provider.
Set up
This tutorial has been developed using dummy data under the Atlas development project. To execute it in Sandbox, be sure to change the following paths.
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following object is masked from 'package:testthat':
#>
#> matches
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(bigrquery)
library(FinnGenUtilsR)
bigrquery::bq_auth(path = Sys.getenv("GCP_SERVICE_KEY"))
project_id <- "atlas-development-270609"
test_longitudinal_data_table <- "atlas-development-270609.sandbox_tools_r10.finngen_r10_service_sector_detailed_longitudinal_v2"
fg_codes_info_table <- "atlas-development-270609.medical_codes.fg_codes_info_v2"
tmp_schema <- "sandbox"Generate a table in service sector format
For example we create a subset of the main service sector table by querying latest 20 events from subject “FG00000001”:
sql <- paste("SELECT * FROM ", test_longitudinal_data_table, "WHERE FINNGENID='FG00000001' ORDER BY APPROX_EVENT_DAY DESC LIMIT 20")
event_for_subject_1 <- bq_project_query(project_id, sql)We can see that this table does not currently have information about the medical codes:
bq_table_download(event_for_subject_1)
#> # A tibble: 20 × 16
#> FINNGENID SOURCE EVENT_AGE APPROX_EVENT_DAY CODE1 CODE2 CODE3 CODE4 CODE5 CODE6 CODE7 CODE8 CODE9 ICDVER CATEGORY INDEX
#> <chr> <chr> <dbl> <date> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PURCH 66.7 2017-11-27 R01AD09 <NA> 474643 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7585
#> 2 FG00000001 PRIM_OUT 66.7 2017-11-19 A28 <NA> <NA> <NA> R10 T11 32311 <NA> <NA> <NA> ICP1 7
#> 3 FG00000001 PURCH 66.5 2017-09-23 M01AE01 <NA> 552190 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7583
#> 4 FG00000001 INPAT 66.5 2017-09-05 I676 <NA> <NA> 4 1 20G <NA> <NA> <NA> 10 1 5
#> 5 FG00000001 PRIM_OUT 66.5 2017-09-05 A98 <NA> <NA> <NA> R20 T42 51321 <NA> <NA> <NA> ICP1 3203
#> 6 FG00000001 INPAT 66.5 2017-09-05 X59 <NA> <NA> 4 1 20G <NA> <NA> <NA> 10 EX1 5
#> 7 FG00000001 PURCH 66.4 2017-08-30 <NA> 103 <NA> 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7590
#> 8 FG00000001 PRIM_OUT 66.4 2017-08-14 SPAT1053 <NA> <NA> <NA> R50 T11 32311 <NA> <NA> <NA> OP1 5256
#> 9 FG00000001 OPER_OUT 66.4 2017-07-31 TPH00 <NA> <NA> <NA> 92 77 <NA> <NA> <NA> <NA> NOM1 6
#> 10 FG00000001 PURCH 66.2 2017-06-10 R03BA02 203 482612 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7588
#> 11 FG00000001 PURCH 66.2 2017-06-07 N06DA02 <NA> 198650 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7591
#> 12 FG00000001 PURCH 66.2 2017-05-30 R01BA51 <NA> 428284 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7587
#> 13 FG00000001 PURCH 66.1 2017-05-08 R03BA01 203 593319 2 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7586
#> 14 FG00000001 PURCH 66.0 2017-03-18 R03BB04 203 021617 2 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7593
#> 15 FG00000001 PURCH 66.0 2017-03-12 H03AA01 <NA> 193102 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7584
#> 16 FG00000001 PURCH 66.0 2017-03-08 C10AA01 <NA> 003664 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7592
#> 17 FG00000001 PURCH 66.0 2017-03-06 M01AH05 <NA> 011260 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 3201
#> 18 FG00000001 INPAT 66.0 2017-03-02 W00 <NA> <NA> 0 1 30 <NA> <NA> <NA> 10 EX1 6
#> 19 FG00000001 INPAT 66.0 2017-03-02 K409 <NA> <NA> 0 1 30 <NA> <NA> <NA> 10 1 6
#> 20 FG00000001 PURCH 65.9 2017-02-02 C09DA06 205 009688 1 <NA> <NA> <NA> <NA> <NA> <NA> <NA> 7589Adding info to medical codes
Function fg_bq_append_code_info_to_longitudinal_data
adds new columns with information about the medical code used in each
event/row.
event_for_subject_1_with_translations <- fg_bq_append_code_info_to_longitudinal_data(
project_id, event_for_subject_1, fg_codes_info_table)For example: code, for the original code; name_en, for the name of the code in English; name_fi for the name of the code in Finnish; and omop_concept_id, to find additional info in Atlas.
bq_table_download(event_for_subject_1_with_translations) |>
dplyr::select(FINNGENID, SOURCE, APPROX_EVENT_DAY, CODE1, CODE2, CODE3, code, name_en, name_fi, omop_concept_id)
#> # A tibble: 20 × 10
#> FINNGENID SOURCE APPROX_EVENT_DAY CODE1 CODE2 CODE3 code name_en name_fi omop_…¹
#> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PURCH 2017-11-27 R01AD09 <NA> 474643 R01AD09 mometasone; nasal <NA> 216050…
#> 2 FG00000001 PRIM_OUT 2017-11-19 A28 <NA> <NA> A28 Limited function/disability NOS Toimin… 202900…
#> 3 FG00000001 PURCH 2017-09-23 M01AE01 <NA> 552190 M01AE01 ibuprofen; systemic, rectal <NA> 216039…
#> 4 FG00000001 INPAT 2017-09-05 I676 <NA> <NA> I67.6 Nonpyogenic thrombosis of intracranial venous system <NA> 455721…
#> 5 FG00000001 PRIM_OUT 2017-09-05 A98 <NA> <NA> A98 Health maint/preventive medicine Tervey… 202900…
#> 6 FG00000001 INPAT 2017-09-05 X59 <NA> <NA> X59 Exposure to unspecified factor <NA> 457564…
#> 7 FG00000001 PURCH 2017-08-30 <NA> 103 <NA> <NA> <NA> <NA> <NA>
#> 8 FG00000001 PRIM_OUT 2017-08-14 SPAT1053 <NA> <NA> SPAT1053 Memory test Muisti… 200400…
#> 9 FG00000001 OPER_OUT 2017-07-31 TPH00 <NA> <NA> TPH00 Phlebotomy Laskim… 201100…
#> 10 FG00000001 PURCH 2017-06-10 R03BA02 203 482612 R03BA02 budesonide; inhalant <NA> 216032…
#> 11 FG00000001 PURCH 2017-06-07 N06DA02 <NA> 198650 N06DA02 donepezil; oral <NA> 216047…
#> 12 FG00000001 PURCH 2017-05-30 R01BA51 <NA> 428284 R01BA51 phenylpropanolamine, combinations; oral <NA> 216032…
#> 13 FG00000001 PURCH 2017-05-08 R03BA01 203 593319 R03BA01 beclometasone; inhalant <NA> 216032…
#> 14 FG00000001 PURCH 2017-03-18 R03BB04 203 021617 R03BB04 tiotropium bromide; inhalant <NA> 216032…
#> 15 FG00000001 PURCH 2017-03-12 H03AA01 <NA> 193102 H03AA01 levothyroxine sodium; systemic <NA> 216027…
#> 16 FG00000001 PURCH 2017-03-08 C10AA01 <NA> 003664 C10AA01 simvastatin; oral <NA> 216018…
#> 17 FG00000001 PURCH 2017-03-06 M01AH05 <NA> 011260 M01AH05 etoricoxib; oral <NA> 216039…
#> 18 FG00000001 INPAT 2017-03-02 W00 <NA> <NA> W00 Fall on same level involving ice and snow <NA> 457562…
#> 19 FG00000001 INPAT 2017-03-02 K409 <NA> <NA> K40.9 Unilateral or unspecified inguinal hernia, without ob… <NA> 455433…
#> 20 FG00000001 PURCH 2017-02-02 C09DA06 205 009688 C09DA06 candesartan and diuretics; oral <NA> 216018…
#> # … with abbreviated variable name ¹omop_concept_idIf an event/row uses more than one medical code
Some events include more than one medical code, or more than one way
to understand a medical code. Parameters in
fg_bq_append_code_info_to_longitudinal_data allows to chose
how to name the medical code in this situations.
For example:
- PURCH_map_to = “VNR”, tells to use the VNR code in PURCH register, instead of the default ATC
- ICD10fi_map_to = “CODE1”, tells to use only the first code in ICD10fi, instead of the default CODE1*CODE2 combination code
event_for_subject_1_with_translations <- fg_bq_append_code_info_to_longitudinal_data(
project_id, event_for_subject_1, fg_codes_info_table,
PURCH_map_to = "VNR",
ICD10fi_map_to = "CODE1"
)
one_patient_long_data <- bq_table_download(event_for_subject_1_with_translations)
bq_table_download(event_for_subject_1_with_translations) |>
dplyr::select(FINNGENID, SOURCE, APPROX_EVENT_DAY, CODE1, CODE2, CODE3, code, name_en, name_fi, omop_concept_id)
#> # A tibble: 20 × 10
#> FINNGENID SOURCE APPROX_EVENT_DAY CODE1 CODE2 CODE3 code name_en name_fi omop_…¹
#> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PURCH 2017-11-27 R01AD09 <NA> 474643 474643 NASONEX nasal spray, suspension 50 mikrog/annos; 3 x … <NA> 203000…
#> 2 FG00000001 PRIM_OUT 2017-11-19 A28 <NA> <NA> A28 Limited function/disability NOS Toimin… 202900…
#> 3 FG00000001 PURCH 2017-09-23 M01AE01 <NA> 552190 552190 BURANA film-coated tablet 600 mg; 30 FOL <NA> 203001…
#> 4 FG00000001 INPAT 2017-09-05 I676 <NA> <NA> I67.6 Nonpyogenic thrombosis of intracranial venous system <NA> 455721…
#> 5 FG00000001 PRIM_OUT 2017-09-05 A98 <NA> <NA> A98 Health maint/preventive medicine Tervey… 202900…
#> 6 FG00000001 INPAT 2017-09-05 X59 <NA> <NA> X59 Exposure to unspecified factor <NA> 457564…
#> 7 FG00000001 PURCH 2017-08-30 <NA> 103 <NA> <NA> <NA> <NA> <NA>
#> 8 FG00000001 PRIM_OUT 2017-08-14 SPAT1053 <NA> <NA> SPAT1053 Memory test Muisti… 200400…
#> 9 FG00000001 OPER_OUT 2017-07-31 TPH00 <NA> <NA> TPH00 Phlebotomy Laskim… 201100…
#> 10 FG00000001 PURCH 2017-06-10 R03BA02 203 482612 482612 PULMICORT TURBUHALER inhalation powder 200 mikrog/ann… <NA> 203001…
#> 11 FG00000001 PURCH 2017-06-07 N06DA02 <NA> 198650 <NA> <NA> <NA> <NA>
#> 12 FG00000001 PURCH 2017-05-30 R01BA51 <NA> 428284 428284 LUNERIN oral solution; 100ML <NA> 203001…
#> 13 FG00000001 PURCH 2017-05-08 R03BA01 203 593319 593319 BECLOMET EASYHALER inhalation powder 200 mikrog/annos… <NA> 203000…
#> 14 FG00000001 PURCH 2017-03-18 R03BB04 203 021617 021617 SPIRIVA inhalation powder, hard capsule 18 mikrog; 90… <NA> 203000…
#> 15 FG00000001 PURCH 2017-03-12 H03AA01 <NA> 193102 193102 THYROXIN tablet 100 mikrog; 100 kpl <NA> 203000…
#> 16 FG00000001 PURCH 2017-03-08 C10AA01 <NA> 003664 003664 LIPCUT film-coated tablet 40 mg; 30 <NA> 203000…
#> 17 FG00000001 PURCH 2017-03-06 M01AH05 <NA> 011260 011260 ARCOXIA film-coated tablet 90 mg; 7 FOL <NA> 203000…
#> 18 FG00000001 INPAT 2017-03-02 W00 <NA> <NA> W00 Fall on same level involving ice and snow <NA> 457562…
#> 19 FG00000001 INPAT 2017-03-02 K409 <NA> <NA> K40.9 Unilateral or unspecified inguinal hernia, without ob… <NA> 455433…
#> 20 FG00000001 PURCH 2017-02-02 C09DA06 205 009688 009688 ATACAND PLUS tablet 16/12,5 mg; 98 fol <NA> 203000…
#> # … with abbreviated variable name ¹omop_concept_idSe the help, for more options
?fg_append_code_info_to_longitudinal_data_sqlReduce code precision
ICD10fi, ICD9fi, ICD8fi, ATC, and NCSPfi, code systems reflect the hierarchy of the code by the first letters on them.
It is possible to truncate these medical codes before the information is added. This in practice adds the code and names of the parent codes.
event_for_subject_1_with_translations <- fg_bq_append_code_info_to_longitudinal_data(
project_id, event_for_subject_1, fg_codes_info_table,
ICD10fi_precision = 3,
ICD9fi_precision = 3,
ICD8fi_precision = 3,
ATC_precision = 3,
NCSPfi_precision = 2
)We can see in column code the trucated code and in
name_en the name of the trucated code.
bq_table_download(event_for_subject_1_with_translations) |>
dplyr::select(FINNGENID, SOURCE, APPROX_EVENT_DAY, CODE1, CODE2, CODE3, code, name_en, name_fi, omop_concept_id)
#> # A tibble: 20 × 10
#> FINNGENID SOURCE APPROX_EVENT_DAY CODE1 CODE2 CODE3 code name_en name_fi omop_…¹
#> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PURCH 2017-11-27 R01AD09 <NA> 474643 R01 NASAL PREPARATIONS <NA> 216050…
#> 2 FG00000001 PRIM_OUT 2017-11-19 A28 <NA> <NA> A28 Limited function/disability NOS Toiminnanvajaus… 202900…
#> 3 FG00000001 PURCH 2017-09-23 M01AE01 <NA> 552190 M01 ANTIINFLAMMATORY AND ANTIRHEUMATIC PRODUCTS <NA> 216039…
#> 4 FG00000001 INPAT 2017-09-05 I676 <NA> <NA> I67 Other cerebrovascular diseases <NA> 455817…
#> 5 FG00000001 PRIM_OUT 2017-09-05 A98 <NA> <NA> A98 Health maint/preventive medicine Terveyden ylläp… 202900…
#> 6 FG00000001 INPAT 2017-09-05 X59 <NA> <NA> X59 Exposure to unspecified factor <NA> 457564…
#> 7 FG00000001 PURCH 2017-08-30 <NA> 103 <NA> <NA> <NA> <NA> <NA>
#> 8 FG00000001 PRIM_OUT 2017-08-14 SPAT1053 <NA> <NA> SPAT1053 Memory test Muistitutkimus 200400…
#> 9 FG00000001 OPER_OUT 2017-07-31 TPH00 <NA> <NA> <NA> <NA> <NA> <NA>
#> 10 FG00000001 PURCH 2017-06-10 R03BA02 203 482612 R03 DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES <NA> 216032…
#> 11 FG00000001 PURCH 2017-06-07 N06DA02 <NA> 198650 N06 PSYCHOANALEPTICS <NA> 216046…
#> 12 FG00000001 PURCH 2017-05-30 R01BA51 <NA> 428284 R01 NASAL PREPARATIONS <NA> 216050…
#> 13 FG00000001 PURCH 2017-05-08 R03BA01 203 593319 R03 DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES <NA> 216032…
#> 14 FG00000001 PURCH 2017-03-18 R03BB04 203 021617 R03 DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES <NA> 216032…
#> 15 FG00000001 PURCH 2017-03-12 H03AA01 <NA> 193102 H03 THYROID THERAPY <NA> 216027…
#> 16 FG00000001 PURCH 2017-03-08 C10AA01 <NA> 003664 C10 LIPID MODIFYING AGENTS <NA> 216018…
#> 17 FG00000001 PURCH 2017-03-06 M01AH05 <NA> 011260 M01 ANTIINFLAMMATORY AND ANTIRHEUMATIC PRODUCTS <NA> 216039…
#> 18 FG00000001 INPAT 2017-03-02 W00 <NA> <NA> W00 Fall on same level involving ice and snow <NA> 457562…
#> 19 FG00000001 INPAT 2017-03-02 K409 <NA> <NA> K40 Inguinal hernia <NA> 455433…
#> 20 FG00000001 PURCH 2017-02-02 C09DA06 205 009688 C09 AGENTS ACTING ON THE RENIN-ANGIOTENSIN SYSTEM <NA> 216017…
#> # … with abbreviated variable name ¹omop_concept_idAdding info to visit type
Function
fg_bq_append_visit_type_info_to_service_sector_data adds
new columns with information about the visit type.
In the service-sector data, information about the visit type is
defined in CODE5 to CODE9 depending on the SOURCE and time period.
fg_bq_append_visit_type_info_to_service_sector_data
abstracts this nuances, and assign one visit type code per row. Notice
that a visit may contain more than one event/row. Events/rows belonging
to the same visit share the same combination of SOURCE+INDEX.
event_for_subject_1_with_visit_type <- fg_bq_append_visit_type_info_to_service_sector_data(
project_id, event_for_subject_1, fg_codes_info_table
)
bigrquery::bq_table_download(event_for_subject_1_with_visit_type) |>
dplyr::select(FINNGENID, SOURCE, INDEX, APPROX_EVENT_DAY, CODE5, CODE6, CODE8, CODE9, visit_type_code, visit_type_name_en)
#> # A tibble: 20 × 10
#> FINNGENID SOURCE INDEX APPROX_EVENT_DAY CODE5 CODE6 CODE8 CODE9 visit_type_code visit_type_name_en
#> <chr> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PRIM_OUT 7 2017-11-19 R10 T11 <NA> <NA> PRIM_OUT|R10|T11 PRIM_OUT | Contact Type: The customer's visit to the …
#> 2 FG00000001 OPER_OUT 6 2017-07-31 92 77 <NA> <NA> OPER_OUT|92 OPER_OUT | Service Sector: Appointment visit, first v…
#> 3 FG00000001 PRIM_OUT 5256 2017-08-14 R50 T11 <NA> <NA> PRIM_OUT|R50|T11 PRIM_OUT | Contact Type: Phone connection | Service T…
#> 4 FG00000001 INPAT 5 2017-09-05 1 20G <NA> <NA> INPAT|1 INPAT | Service Sector: Hospital / health center ward
#> 5 FG00000001 INPAT 6 2017-03-02 1 30 <NA> <NA> INPAT|1 INPAT | Service Sector: Hospital / health center ward
#> 6 FG00000001 INPAT 5 2017-09-05 1 20G <NA> <NA> INPAT|1 INPAT | Service Sector: Hospital / health center ward
#> 7 FG00000001 INPAT 6 2017-03-02 1 30 <NA> <NA> INPAT|1 INPAT | Service Sector: Hospital / health center ward
#> 8 FG00000001 PURCH 7585 2017-11-27 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 9 FG00000001 PURCH 7591 2017-06-07 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 10 FG00000001 PURCH 7593 2017-03-18 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 11 FG00000001 PURCH 7592 2017-03-08 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 12 FG00000001 PURCH 7584 2017-03-12 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 13 FG00000001 PURCH 7586 2017-05-08 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 14 FG00000001 PURCH 7583 2017-09-23 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 15 FG00000001 PURCH 7587 2017-05-30 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 16 FG00000001 PURCH 7589 2017-02-02 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 17 FG00000001 PURCH 7588 2017-06-10 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 18 FG00000001 PURCH 7590 2017-08-30 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 19 FG00000001 PURCH 3201 2017-03-06 <NA> <NA> <NA> <NA> PURCH Entry in kela drug purchases registry
#> 20 FG00000001 PRIM_OUT 3203 2017-09-05 R20 T42 <NA> <NA> PRIM_OUT|R20|T42 PRIM_OUT | Contact Type: Professional's visit to cust…Adding info to provider type
Function
fg_bq_append_provider_info_to_service_sector_data adds new
columns with information about the personal or unit that provided the
diagnose during the visit.
In the service-sector data, information about the provider is defined
in CODE6 to CODE7 depending on the SOURCE.
fg_bq_append_visit_type_info_to_service_sector_data
abstracts this nuances, and assign one provider type code per row.
event_for_subject_1_with_provider <- fg_bq_append_provider_info_to_service_sector_data(
project_id, event_for_subject_1, fg_codes_info_table
)
bigrquery::bq_table_download(event_for_subject_1_with_provider) |>
dplyr::select(FINNGENID, SOURCE, INDEX, APPROX_EVENT_DAY, CODE5, CODE6, CODE8, CODE9, provider_code, provider_name_en, provider_concept_class_id)
#> # A tibble: 20 × 11
#> FINNGENID SOURCE INDEX APPROX_EVENT_DAY CODE5 CODE6 CODE8 CODE9 provider_code provider_name_en provider_concept_class_id
#> <chr> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FG00000001 PURCH 7589 2017-02-02 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 2 FG00000001 PURCH 7588 2017-06-10 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 3 FG00000001 PURCH 7585 2017-11-27 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 4 FG00000001 PURCH 7591 2017-06-07 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 5 FG00000001 PURCH 7590 2017-08-30 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 6 FG00000001 PURCH 7592 2017-03-08 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 7 FG00000001 PURCH 7587 2017-05-30 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 8 FG00000001 PURCH 7593 2017-03-18 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 9 FG00000001 PURCH 7584 2017-03-12 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 10 FG00000001 PURCH 7586 2017-05-08 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 11 FG00000001 PURCH 3201 2017-03-06 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 12 FG00000001 PURCH 7583 2017-09-23 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 13 FG00000001 INPAT 5 2017-09-05 1 20G <NA> <NA> 20G Gastroenterological Surgery MEDSPECfi Level 1
#> 14 FG00000001 INPAT 5 2017-09-05 1 20G <NA> <NA> 20G Gastroenterological Surgery MEDSPECfi Level 1
#> 15 FG00000001 INPAT 6 2017-03-02 1 30 <NA> <NA> 30 Gynecology and childbirth MEDSPECfi Level 0
#> 16 FG00000001 INPAT 6 2017-03-02 1 30 <NA> <NA> 30 Gynecology and childbirth MEDSPECfi Level 0
#> 17 FG00000001 PRIM_OUT 5256 2017-08-14 R50 T11 <NA> <NA> 32311 Nurses ProfessionalCode
#> 18 FG00000001 PRIM_OUT 7 2017-11-19 R10 T11 <NA> <NA> 32311 Nurses ProfessionalCode
#> 19 FG00000001 OPER_OUT 6 2017-07-31 92 77 <NA> <NA> 77 Neurology MEDSPECfi Level 0
#> 20 FG00000001 PRIM_OUT 3203 2017-09-05 R20 T42 <NA> <NA> 51321 Practical nurses ProfessionalCode