Job request: 27154
- Organisation:
- University of Bristol
- Workspace:
- depill-ckd-1
- ID:
- u3zfzttne2gsmdb5
This page shows the technical details of what happened when the authorised researcher Matthew Letts requested one or more actions to be run against real patient data within a secure environment.
By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.
The output security levels are:
-
highly_sensitive
- Researchers can never directly view these outputs
- Researchers can only request code is run against them
-
moderately_sensitive
- Can be viewed by an approved researcher by logging into a highly secure environment
- These are the only outputs that can be requested for public release via a controlled output review service.
Jobs
-
- Action:
- dataset_cleaning_inex
- Status:
- Succeeded
- Job identifier:
-
t554wyd3gs2tcher
-
- Action:
- dataset_process_baseline_meds
- Status:
- Pending
- Job identifier:
-
owf7l3pe7v3xcrx4 - Status message:
- waiting_on_dependencies: Waiting on dependencies
-
- Action:
- analyse_baseline_meds
- Status:
- Pending
- Job identifier:
-
ikjpjbg27ms44un6 - Status message:
- waiting_on_dependencies: Waiting on dependencies
-
- Action:
- generate_dataset_baseline_meds
- Status:
- Pending
- Job identifier:
-
om6sgsun47a2zq7m - Status message:
- waiting_on_db_workers: Waiting on available database workers
Pipeline
Show project.yaml
version: '5.0'
actions:
study_dates:
run: r:v3 analysis/config/config.r
outputs:
highly_sensitive:
study_dates_json: output/study_dates.json
generate_dataset_inex:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_inex.py
--dummy-tables dummy_tables/
--output output/dataset_inex.arrow
# --test-data-file analysis/dataset_definition/test_dataset_definition_inex.py
needs: [study_dates]
outputs:
highly_sensitive:
dataset_inex: output/dataset_inex.arrow
dataset_cleaning_inex:
run: r:v3 analysis/dataset_processing/dataset_cleaning_inex.r
needs: [generate_dataset_inex]
outputs:
highly_sensitive:
dataset_inex_cleaned: output/data/dataset_inex_cleaned.arrow
moderately_sensitive:
cleaning_inex_data_flow: output/data_descriptions/cleaning_inex/data_flow.csv
cleaning_inex_data_descriptions: output/data_descriptions/cleaning_inex/*.txt
cleaning_inex_med_count_summary: output/data_descriptions/cleaning_inex/med_count_summary.csv
cleaning_inex_ckd_sensitivity_counts: output/data_descriptions/cleaning_inex/ckd_sensitivity_counts.csv
generate_dataset_baseline_covariates_general:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_baseline_covariates_general.py
--dummy-tables dummy_tables/
--output output/dataset_baseline_covariates_general.arrow
# --test-data-file analysis/dataset_definition/test_dataset_definition_baseline_covariates_general.py
needs: [study_dates, dataset_cleaning_inex]
outputs:
highly_sensitive:
dataset_baseline_covariates_general: output/dataset_baseline_covariates_general.arrow
# generate_dataset_baseline_covariates_med_specific_ppi:
# run: >
# ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_baseline_covariates_med_specific.py
# --dummy-tables dummy_tables/
# --output output/dataset_baseline_covariates_med_specific_ppi.arrow
# -- --medicine ppi
# needs: [study_dates, dataset_cleaning_inex]
# outputs:
# highly_sensitive:
# dataset_baseline_covariates_med_specific_ppi: output/dataset_baseline_covariates_med_specific_ppi.arrow
# generate_dataset_baseline_covariates_med_specific_statin:
# run: >
# ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_baseline_covariates_med_specific.py
# --dummy-tables dummy_tables/
# --output output/dataset_baseline_covariates_med_specific_statin.arrow
# -- --medicine statin
# needs: [study_dates, dataset_cleaning_inex]
# outputs:
# highly_sensitive:
# dataset_baseline_covariates_med_specific_ppi: output/dataset_baseline_covariates_med_specific_statin.arrow
generate_dataset_baseline_meds:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_baseline_meds.py
--dummy-tables dummy_tables/
--output output/dataset_baseline_meds.arrow
# --test-data-file analysis/dataset_definition/test_dataset_definition_baseline_meds.py
needs: [study_dates, dataset_cleaning_inex]
outputs:
highly_sensitive:
dataset_baseline_meds: output/dataset_baseline_meds.arrow
dataset_process_baseline_meds:
run: r:v3 analysis/dataset_processing/dataset_process_baseline_meds.r
needs: [generate_dataset_baseline_meds, study_dates]
outputs:
highly_sensitive:
dataset_baseline_meds_processed: output/data/dataset_baseline_meds_processed.arrow
moderately_sensitive:
process_baseline_meds_data_flow: output/data_descriptions/process_baseline_meds/data_flow.csv
process_baseline_meds_dmd_not_in_lookup: output/data_descriptions/process_baseline_meds/dmd_not_in_lookup.csv
process_baseline_meds_dmd_unmapped_to_bnf: output/data_descriptions/process_baseline_meds/dmd_unmapped_to_bnf.csv
process_baseline_meds_data_descriptions: output/data_descriptions/process_baseline_meds/*.txt
process_baseline_meds_route_classification_patient_summary: output/data_descriptions/process_baseline_meds/route_classification_patient_summary.csv
analyse_baseline_meds:
run: r:v3 analysis/dataset_analysis/analyse_baseline_meds.r
needs: [dataset_process_baseline_meds, study_dates]
outputs:
highly_sensitive:
dataset_baseline_meds_analysed: output/data/dataset_baseline_meds_analysed.arrow
moderately_sensitive:
analyse_baseline_meds_data_flow: output/data_descriptions/analyse_baseline_meds/data_flow.csv
counts_days_before_index: output/data_descriptions/analyse_baseline_meds/counts_days_before_index.csv
chronic_meds_summary_sens_analysis: output/data_descriptions/analyse_baseline_meds/chronic_meds_summary.csv
chronic_meds_frequency_sens_analysis: output/data_descriptions/analyse_baseline_meds/chronic_meds_frequency.csv
analyse_baseline_meds_data_descriptions: output/data_descriptions/analyse_baseline_meds/*.txt
meds_prevalence_substance: output/data_descriptions/analyse_baseline_meds/meds_prevalence_substance.csv
meds_prevalence_subparagraph: output/data_descriptions/analyse_baseline_meds/meds_prevalence_subparagraph.csv
meds_prevalence_paragraph: output/data_descriptions/analyse_baseline_meds/meds_prevalence_paragraph.csv
bnf_chapters_frequency: output/data_descriptions/analyse_baseline_meds/bnf_chapters_frequency.csv
table_1:
run: r:v3 analysis/dataset_analysis/table_1.r
needs: [dataset_cleaning_inex]
outputs:
moderately_sensitive:
table_1: output/tables/table_1.csv
generate_dataset_discont_meds_baseline_statins:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_discont_meds_baseline.py
--dummy-tables dummy_tables/
--output output/dataset_discont_meds_baseline_statins.arrow
--
--medication statins
needs: [study_dates, dataset_cleaning_inex]
outputs:
highly_sensitive:
dataset_discont_meds_baseline_statins: output/dataset_discont_meds_baseline_statins.arrow
generate_dataset_discont_meds_baseline_ppis:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_discont_meds_baseline.py
--dummy-tables dummy_tables/
--output output/dataset_discont_meds_baseline_ppis.arrow
--
--medication ppis
needs: [study_dates, dataset_cleaning_inex]
outputs:
highly_sensitive:
dataset_discont_meds_baseline_ppis: output/dataset_discont_meds_baseline_ppis.arrow
# add another parameterised action to pull data up to index date for each moi
dataset_process_moi_at_baseline:
run: r:v3 analysis/discontinuation/dataset_processing/dataset_process_moi_at_baseline.r
needs: [generate_dataset_discont_meds_baseline_statins, generate_dataset_discont_meds_baseline_ppis, study_dates]
outputs:
highly_sensitive:
dataset_statins_at_baseline_processed: output/data/dataset_statins_at_baseline_processed.arrow
dataset_statins_at_baseline_data_descriptions: output/data_descriptions/process_moi_at_baseline_statins/*.txt
dataset_ppis_at_baseline_processed: output/data/dataset_ppis_at_baseline_processed.arrow
dataset_ppis_at_baseline_data_descriptions: output/data_descriptions/process_moi_at_baseline_ppis/*.txt
moderately_sensitive:
statins_at_baseline_data_flow: output/data_descriptions/process_moi_at_baseline_statins/data_flow.csv
ppis_at_baseline_data_flow: output/data_descriptions/process_moi_at_baseline_ppis/data_flow.csv
# add more needs/outputs for each medication of interest
generate_dataset_discont_meds_follow_up_statins:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_discont_meds_follow_up.py
--dummy-tables dummy_tables/
--output output/dataset_discont_meds_follow_up_statins.arrow
--
--medication statins
needs: [study_dates, dataset_process_moi_at_baseline]
outputs:
highly_sensitive:
dataset_discont_meds_follow_up_statins: output/dataset_discont_meds_follow_up_statins.arrow
generate_dataset_discont_meds_follow_up_ppis:
run: >
ehrql:v1 generate-dataset analysis/dataset_definition/dataset_definition_discont_meds_follow_up.py
--dummy-tables dummy_tables/
--output output/dataset_discont_meds_follow_up_ppis.arrow
--
--medication ppis
needs: [study_dates, dataset_process_moi_at_baseline]
outputs:
highly_sensitive:
dataset_discont_meds_follow_up_ppis: output/dataset_discont_meds_follow_up_ppis.arrow
# add another parameterised action to pull followup data for each moi
Job statistics
| Status | Count | Percentage |
|---|---|---|
| Pending | 3 | 75% |
| Running | 0 | 0% |
| Succeeded | 1 | 25% |
| Failed | 0 | 0% |
1 / 4 (25%) complete
Timeline
-
Created:
-
Started:
-
Runtime: 00:22:56
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job request
- Status
-
Running
- Backend
- TPP
- Workspace
- depill-ckd-1
- Requested by
- Matthew Letts
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- dfcedc7
- Requested actions
-
-
dataset_cleaning_inex -
generate_dataset_baseline_meds -
dataset_process_baseline_meds -
analyse_baseline_meds
-
Code comparison
Compare the code used in this job request