Job request: 17385
- Organisation:
- Bennett Institute
- Workspace:
- the-impact-of-covid-19-on-the-care-of-people-with-sickle-cell-disease-interactive
- ID:
- tcjwldri4b6vltua
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 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
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- Job identifier:
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33f5xssergmubw7b
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- Job identifier:
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3ygcfenls6zg4xke
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- Job identifier:
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waww2hivszelfhee
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- Job identifier:
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gxjpmkenltnyxsnp
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- Job identifier:
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6fgypolqiyfo7uns
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- Job identifier:
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mlck3hr32vu6yxjx
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- Job identifier:
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3cyfklrxonenfjxl
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- Job identifier:
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t7dk7m32qxhxl7xh
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- Job identifier:
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vpyjgsindxpiox2v
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population_ethnicity_01GZ17GWKP5NBK3SY82GJAE1XX:
run: cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--param end_date="2023-03-31"
--output-dir output/01GZ17GWKP5NBK3SY82GJAE1XX --output-format=feather
outputs:
highly_sensitive:
cohort: output/01GZ17GWKP5NBK3SY82GJAE1XX/input_ethnicity.feather
generate_study_population_weekly_01GZ17GWKP5NBK3SY82GJAE1XX:
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/01GZ17GWKP5NBK3SY82GJAE1XX
--output-format=feather
--output-file=output/01GZ17GWKP5NBK3SY82GJAE1XX/input_weekly_2023-04-10.feather
outputs:
highly_sensitive:
cohort: output/01GZ17GWKP5NBK3SY82GJAE1XX/input_weekly_2023-04-10.feather
generate_study_population_01GZ17GWKP5NBK3SY82GJAE1XX:
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/01GZ17GWKP5NBK3SY82GJAE1XX
--output-format=feather
outputs:
highly_sensitive:
cohort: output/01GZ17GWKP5NBK3SY82GJAE1XX/input_*.feather
join_cohorts_01GZ17GWKP5NBK3SY82GJAE1XX:
run: >
cohort-joiner:v0.0.38
--lhs output/01GZ17GWKP5NBK3SY82GJAE1XX/input_20*.feather
--rhs output/01GZ17GWKP5NBK3SY82GJAE1XX/input_ethnicity.feather
--output-dir output/01GZ17GWKP5NBK3SY82GJAE1XX/joined
needs: [generate_study_population_01GZ17GWKP5NBK3SY82GJAE1XX, generate_study_population_ethnicity_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
highly_sensitive:
cohort: output/01GZ17GWKP5NBK3SY82GJAE1XX/joined/input_20*.feather
generate_measures_01GZ17GWKP5NBK3SY82GJAE1XX:
run: >
python:latest -m analysis.measures
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--input-dir="output/01GZ17GWKP5NBK3SY82GJAE1XX/joined"
needs: [join_cohorts_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
moderately_sensitive:
measure: output/01GZ17GWKP5NBK3SY82GJAE1XX/joined/measure_all.csv
decile_measure: output/01GZ17GWKP5NBK3SY82GJAE1XX/joined/measure_practice_rate_deciles.csv
top_5_table_01GZ17GWKP5NBK3SY82GJAE1XX:
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/01GZ17GWKP5NBK3SY82GJAE1XX"
needs: [generate_measures_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
moderately_sensitive:
tables: output/01GZ17GWKP5NBK3SY82GJAE1XX/joined/top_5*.csv
plot_measure_01GZ17GWKP5NBK3SY82GJAE1XX:
run: >
python:latest python analysis/plot_measures.py
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--output-dir output/01GZ17GWKP5NBK3SY82GJAE1XX
needs: [generate_measures_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
moderately_sensitive:
measure: output/01GZ17GWKP5NBK3SY82GJAE1XX/plot_measure*.png
deciles: output/01GZ17GWKP5NBK3SY82GJAE1XX/deciles_chart.png
event_counts_01GZ17GWKP5NBK3SY82GJAE1XX:
run: >
python:latest -m analysis.event_counts --input-dir="output/01GZ17GWKP5NBK3SY82GJAE1XX" --output-dir="output/01GZ17GWKP5NBK3SY82GJAE1XX"
needs: [join_cohorts_01GZ17GWKP5NBK3SY82GJAE1XX, generate_study_population_weekly_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
moderately_sensitive:
measure: output/01GZ17GWKP5NBK3SY82GJAE1XX/event_counts.json
generate_report_01GZ17GWKP5NBK3SY82GJAE1XX:
run: >
python:latest python analysis/render_report.py
--output-dir="output/01GZ17GWKP5NBK3SY82GJAE1XX"
--population="all"
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--codelist-1-name="Phenoxymethylpenicillin (oral preparations only)"
--codelist-2-name="Sickle (SPL-AtRiskv4) (SNOMED CT)"
--codelist-1-link="opensafely/phenoxymethylpenicillin-oral-preparations-only/14b427f8"
--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_01GZ17GWKP5NBK3SY82GJAE1XX, top_5_table_01GZ17GWKP5NBK3SY82GJAE1XX, plot_measure_01GZ17GWKP5NBK3SY82GJAE1XX]
outputs:
moderately_sensitive:
notebook: output/01GZ17GWKP5NBK3SY82GJAE1XX/report.html
Timeline
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Created:
-
Started:
-
Finished:
-
Runtime: 19:24:05
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
- Backend
- TPP
- Requested by
- Andrew Brown
- Branch
- main
- Force run dependencies
- Yes
- Git commit hash
- 181dee2
- Requested actions
-
-
run_all
-
Code comparison
Compare the code used in this Job Request