Job request: 17778
- Organisation:
- The London School of Hygiene & Tropical Medicine
- Workspace:
- healthcare_utilisation_openprompt
- ID:
- lycwjomegfdd3pbv
This page shows the technical details of what happened when the authorised researcher Liang-Yu Lin requested one or more actions to be run against real patient data in the project, within a secure environment.
By cross-referencing the list of jobs with the
pipeline section below, you can infer what
security level
various outputs were written to. Researchers can never directly
view outputs marked as
highly_sensitive
;
they can only request that code runs against them. Outputs
marked as
moderately_sensitive
can be viewed by an approved researcher by logging into a highly
secure environment. Only outputs marked as
moderately_sensitive
can be requested for release to the public, via a controlled
output review service.
Jobs
-
- Job identifier:
-
ycu2pw7aayrivcqj
-
- Job identifier:
-
kuuwtnbgewsg5rna
-
- Job identifier:
-
frtk5wokczepbe2f
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- Job identifier:
-
icnqoqstbz3l4r2u
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- Job identifier:
-
62ricfdul3asa5ja
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- Job identifier:
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vavmp27jldrzaoiw
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- Job identifier:
-
dca4o5hxwzldgyr4
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- Job identifier:
-
zdlc5axfdhysfo5z
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 500
actions:
generate_long_covid_exposure_dataset:
run:
databuilder:v0 generate-dataset
analysis/dataset_definition_unmatched_exp_lc.py
--output output/dataset_exp_lc_unmatched.csv
outputs:
highly_sensitive:
cohort: output/dataset_exp_lc_unmatched.csv
generate_list_gp_use_long_covid_dx:
run:
databuilder:v0 generate-dataset
analysis/dataset_definition_lc_gp_list.py
--output output/dataset_lc_gp_list.csv
outputs:
highly_sensitive:
cohort: output/dataset_lc_gp_list.csv
generate_dataset_comparator_exclude_gp_no_long_covid:
needs: [generate_list_gp_use_long_covid_dx]
run:
databuilder:v0 generate-dataset
analysis/dataset_definition_unmatched_comparator.py
--output output/dataset_comparator_unmatched.csv
outputs:
highly_sensitive:
cohort: output/dataset_comparator_unmatched.csv
test_matching:
run:
python:latest python analysis/match_test.py
needs: [generate_dataset_comparator_exclude_gp_no_long_covid, generate_long_covid_exposure_dataset]
outputs:
highly_sensitive:
matched_cases: output/matched_cases_stp.csv
matched_matches: output/matched_matches_stp.csv
matched_all: output/matched_combined_stp.csv
moderately_sensitive:
matching_report: output/matching_report_stp.txt
import_matched_exposure:
run: >
databuilder:v0
generate-dataset analysis/dataset_definition_matched_cases.py
--output output/matched_cases_with_ehr.csv
needs: [test_matching]
outputs:
highly_sensitive:
cohort: output/matched_cases_with_ehr.csv
import_matched_controls:
run: >
databuilder:v0
generate-dataset analysis/dataset_definition_matched_control.py
--output output/matched_control_with_ehr.csv
needs: [test_matching]
outputs:
highly_sensitive:
cohort: output/matched_control_with_ehr.csv
generate_historical_exp_data:
run:
databuilder:v0 generate-dataset analysis/dataset_definition_hx_unmatched_exp_lc.py
--output output/hx_unmatched_exp.csv
outputs:
highly_sensitive:
hx_cohort: output/hx_unmatched_exp.csv
generate_historical_comp_data_exclude_gp_no_long_covid:
needs: [generate_list_gp_use_long_covid_dx]
run:
databuilder:v0 generate-dataset analysis/dataset_definition_hx_unmatched_com_no_lc.py
--output output/hx_dataset_comp_unmatched.csv
outputs:
highly_sensitive:
hx_cohort: output/hx_dataset_comp_unmatched.csv
historical_matching:
run:
python:latest python analysis/match_historical.py
needs: [generate_historical_exp_data, generate_historical_comp_data_exclude_gp_no_long_covid]
outputs:
highly_sensitive:
matched_cases: output/matched_cases_historical.csv
matched_matches: output/matched_matches_historical.csv
matched_all: output/matched_combined_historical.csv
moderately_sensitive:
matching_report: output/matching_report_historical.txt
import_matched_historical_exposure:
run: >
databuilder:v0
generate-dataset analysis/dataset_definition_hx_matched_exp_lc.py
--output output/hx_matched_cases_with_ehr.csv
needs: [historical_matching]
outputs:
highly_sensitive:
cohort: output/hx_matched_cases_with_ehr.csv
import_matched_historical_controls:
run: >
databuilder:v0
generate-dataset analysis/dataset_definition_hx_matched_comp.py
--output output/hx_matched_control_with_ehr.csv
needs: [historical_matching]
outputs:
highly_sensitive:
cohort: output/hx_matched_control_with_ehr.csv
# Reporting:
report01_matched_datasets:
needs: [import_matched_exposure, import_matched_controls]
run:
r:latest analysis/st01_report_matched.R
outputs:
moderately_sensitive:
matched_table: output/st01_matched_numbers_table.csv
explore_vax_fig: output/st1_exporing_vax_index_date.png
missing_table: output/missing_distribution_table.csv
missing_pattern: output/missing_pattern_current.png
report02_hx_matched_datasets:
needs: [import_matched_historical_exposure, import_matched_historical_controls]
run:
r:latest analysis/st02_report_matched_historical.R
outputs:
moderately_sensitive:
matched_table: output/hx_matched_numbers_table.csv
report_03_hurdle_model:
needs: [import_matched_exposure, import_matched_controls]
run:
r:latest analysis/st03_hurdle_model.R
outputs:
moderately_sensitive:
model_table: output/st03_monthly_visits_crude_hurdle.csv
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 17:16:12
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- healthcare_utilisation_openprompt
- Requested by
- Liang-Yu Lin
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 5f26293
- Requested actions
-
-
generate_long_covid_exposure_dataset
-
generate_list_gp_use_long_covid_dx
-
generate_dataset_comparator_exclude_gp_no_long_covid
-
test_matching
-
import_matched_exposure
-
import_matched_controls
-
report01_matched_datasets
-
report_03_hurdle_model
-
Code comparison
Compare the code used in this Job Request