Job request: 17386
- Organisation:
- Bennett Institute
- Workspace:
- the-impact-of-covid-19-on-the-care-of-people-with-sickle-cell-disease-interactive
- ID:
- my5h6llcwvej53im
This page shows the technical details of what happened when the authorised researcher Andrew Brown 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
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- Job identifier:
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rmvjj5qj7ifporxw
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- Job identifier:
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pf72tt3su6o4dtot
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- Job identifier:
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4myukpyjq5fjj6kj - Error:
- nonzero_exit: Job exited with an error: A transient database error occurred, your job may run if you try it again, if it keeps failing then contact tech support
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- Job identifier:
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uw35s7r3w7ysvd56 - Error:
- dependency_failed: Not starting as dependency failed
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- Job identifier:
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y74tn2fjdgtbasm5 - Error:
- dependency_failed: Not starting as dependency failed
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- Job identifier:
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csxncwhq6gp64xds - Error:
- dependency_failed: Not starting as dependency failed
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- Job identifier:
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5zhjy5nsqxn7llmz - Error:
- dependency_failed: Not starting as dependency failed
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- Job identifier:
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vvp2soq4mukex6zi - Error:
- dependency_failed: Not starting as dependency failed
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- Job identifier:
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7j7bidei5lym2fq3 - Error:
- dependency_failed: Not starting as dependency failed
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population_ethnicity_01GZ17N26M1KMZ5R42MCEDK1R4:
run: cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--param end_date="2023-03-31"
--output-dir output/01GZ17N26M1KMZ5R42MCEDK1R4 --output-format=feather
outputs:
highly_sensitive:
cohort: output/01GZ17N26M1KMZ5R42MCEDK1R4/input_ethnicity.feather
generate_study_population_weekly_01GZ17N26M1KMZ5R42MCEDK1R4:
run: cohortextractor:latest generate_cohort
--study-definition study_definition
--param codelist_1_path="interactive_codelists/codelist_1.csv"
--param codelist_1_type="medication"
--param codelist_2_path="interactive_codelists/codelist_2.csv"
--param codelist_2_type="event"
--param codelist_1_frequency="weekly"
--param time_value="None"
--param time_ever="True"
--param time_scale=""
--param time_event="before"
--param codelist_2_comparison_date="end_date"
--param operator="AND"
--param population="all"
--param breakdowns=""
--index-date_range="2023-04-10 to 2023-04-10 by week"
--output-dir=output/01GZ17N26M1KMZ5R42MCEDK1R4
--output-format=feather
--output-file=output/01GZ17N26M1KMZ5R42MCEDK1R4/input_weekly_2023-04-10.feather
outputs:
highly_sensitive:
cohort: output/01GZ17N26M1KMZ5R42MCEDK1R4/input_weekly_2023-04-10.feather
generate_study_population_01GZ17N26M1KMZ5R42MCEDK1R4:
run: cohortextractor:latest generate_cohort
--study-definition study_definition
--param codelist_1_path="interactive_codelists/codelist_1.csv"
--param codelist_1_type="medication"
--param codelist_2_path="interactive_codelists/codelist_2.csv"
--param codelist_2_type="event"
--param codelist_1_frequency="monthly"
--param time_value="None"
--param time_ever="True"
--param time_scale=""
--param time_event="before"
--param codelist_2_comparison_date="end_date"
--param operator="AND"
--param population="all"
--param breakdowns="sex,age,ethnicity,imd,region"
--index-date-range="2019-09-01 to 2023-03-31 by month"
--output-dir=output/01GZ17N26M1KMZ5R42MCEDK1R4
--output-format=feather
outputs:
highly_sensitive:
cohort: output/01GZ17N26M1KMZ5R42MCEDK1R4/input_*.feather
join_cohorts_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
cohort-joiner:v0.0.38
--lhs output/01GZ17N26M1KMZ5R42MCEDK1R4/input_20*.feather
--rhs output/01GZ17N26M1KMZ5R42MCEDK1R4/input_ethnicity.feather
--output-dir output/01GZ17N26M1KMZ5R42MCEDK1R4/joined
needs: [generate_study_population_01GZ17N26M1KMZ5R42MCEDK1R4, generate_study_population_ethnicity_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
highly_sensitive:
cohort: output/01GZ17N26M1KMZ5R42MCEDK1R4/joined/input_20*.feather
generate_measures_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
python:latest -m analysis.measures
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--input-dir="output/01GZ17N26M1KMZ5R42MCEDK1R4/joined"
needs: [join_cohorts_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
moderately_sensitive:
measure: output/01GZ17N26M1KMZ5R42MCEDK1R4/joined/measure_all.csv
decile_measure: output/01GZ17N26M1KMZ5R42MCEDK1R4/joined/measure_practice_rate_deciles.csv
top_5_table_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
python:latest python analysis/top_5.py
--codelist-1-path="interactive_codelists/codelist_1.csv"
--codelist-2-path="interactive_codelists/codelist_2.csv"
--output-dir="output/01GZ17N26M1KMZ5R42MCEDK1R4"
needs: [generate_measures_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
moderately_sensitive:
tables: output/01GZ17N26M1KMZ5R42MCEDK1R4/joined/top_5*.csv
plot_measure_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
python:latest python analysis/plot_measures.py
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--output-dir output/01GZ17N26M1KMZ5R42MCEDK1R4
needs: [generate_measures_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
moderately_sensitive:
measure: output/01GZ17N26M1KMZ5R42MCEDK1R4/plot_measure*.png
deciles: output/01GZ17N26M1KMZ5R42MCEDK1R4/deciles_chart.png
event_counts_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
python:latest -m analysis.event_counts --input-dir="output/01GZ17N26M1KMZ5R42MCEDK1R4" --output-dir="output/01GZ17N26M1KMZ5R42MCEDK1R4"
needs: [join_cohorts_01GZ17N26M1KMZ5R42MCEDK1R4, generate_study_population_weekly_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
moderately_sensitive:
measure: output/01GZ17N26M1KMZ5R42MCEDK1R4/event_counts.json
generate_report_01GZ17N26M1KMZ5R42MCEDK1R4:
run: >
python:latest python analysis/render_report.py
--output-dir="output/01GZ17N26M1KMZ5R42MCEDK1R4"
--population="all"
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--codelist-1-name="Opioid-containing medicines (oral - excluding drugs for substance misuse) - dm+d"
--codelist-2-name="Sickle (SPL-AtRiskv4) (SNOMED CT)"
--codelist-1-link="opensafely/opioid-containing-medicines-oral-excluding-drugs-for-substance-misuse-dmd/6eb4a72e"
--codelist-2-link="nhsd/sickle-spl-atriskv4-snomed-ct/7083ed37"
--time-value="None"
--time-scale=""
--time-event="before"
--start-date="2019-09-01"
--end-date="2023-03-31"
--time-ever
needs: [event_counts_01GZ17N26M1KMZ5R42MCEDK1R4, top_5_table_01GZ17N26M1KMZ5R42MCEDK1R4, plot_measure_01GZ17N26M1KMZ5R42MCEDK1R4]
outputs:
moderately_sensitive:
notebook: output/01GZ17N26M1KMZ5R42MCEDK1R4/report.html
Timeline
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Created:
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Started:
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Finished:
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Runtime: 09:01:08
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job request
- Status
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Failed
- Backend
- TPP
- Requested by
- Andrew Brown
- Branch
- main
- Force run dependencies
- Yes
- Git commit hash
- 7395891
- Requested actions
-
-
run_all
-
Code comparison
Compare the code used in this job request