Job request: 15992
- Organisation:
- Bennett Institute
- Workspace:
- opensafely-internal-interactive
- ID:
- f2isoh6fcxfxciin
This page shows the technical details of what happened when the authorised researcher Lucy Bridges 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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bu4zoveis4puiezg
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- Job identifier:
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ltnvtomqstb6q6of
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- Job identifier:
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lbgwvwphal7ea7yj
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- Job identifier:
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vuggw5z5ab4hqdcq
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- Job identifier:
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qujvyrsgc5r2tokj
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- Job identifier:
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lrkljcsznkdaxsg5
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- Job identifier:
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vykrf6odejn6gged
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- Job identifier:
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z3lyuhjbc6snl7ws
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- Job identifier:
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kvko6iv7ac4qly3t
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population_ethnicity_01GTM8RXTN1H66AGY6C1J7T01A:
run: cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--param end_date="2023-02-22"
--output-dir output/01GTM8RXTN1H66AGY6C1J7T01A --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/01GTM8RXTN1H66AGY6C1J7T01A/input_ethnicity.csv.gz
generate_study_population_01GTM8RXTN1H66AGY6C1J7T01A:
run: cohortextractor:latest generate_cohort
--study-definition study_definition
--param codelist_1_path="codelists/codelist_1.csv"
--param codelist_1_type="medication"
--param codelist_2_path="codelists/codelist_2.csv"
--param codelist_2_type="event"
--param codelist_1_frequency="monthly"
--param time_value="6"
--param time_scale="months"
--param time_event="before"
--param codelist_2_comparison_date="event_1_date"
--param operator="AND"
--param population="adults"
--param breakdowns="sex,age,imd"
--index-date-range="2022-08-26 to 2023-02-22 by month"
--output-dir=output/01GTM8RXTN1H66AGY6C1J7T01A
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/01GTM8RXTN1H66AGY6C1J7T01A/input_*.csv.gz
join_cohorts_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
cohort-joiner:v0.0.38
--lhs output/01GTM8RXTN1H66AGY6C1J7T01A/input_20*.csv.gz
--rhs output/01GTM8RXTN1H66AGY6C1J7T01A/input_ethnicity.csv.gz
--output-dir output/01GTM8RXTN1H66AGY6C1J7T01A/joined
needs: [generate_study_population_01GTM8RXTN1H66AGY6C1J7T01A, generate_study_population_ethnicity_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
highly_sensitive:
cohort: output/01GTM8RXTN1H66AGY6C1J7T01A/joined/input_20*.csv.gz
generate_measures_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
python:latest python analysis/measures.py
--breakdowns="sex,age,imd"
--input_dir="output/01GTM8RXTN1H66AGY6C1J7T01A/joined"
--measure="med_review"
needs: [join_cohorts_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
measure: output/01GTM8RXTN1H66AGY6C1J7T01A/joined/measure*rate.csv
decile_measure: output/01GTM8RXTN1H66AGY6C1J7T01A/joined/measure*rate_deciles.csv
top_5_table_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
python:latest python analysis/top_5.py
--codelist-1-path="codelists/codelist_1.csv"
--codelist-2-path="codelists/codelist_2.csv"
--output-dir="output/01GTM8RXTN1H66AGY6C1J7T01A"
needs: [generate_measures_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
tables: output/01GTM8RXTN1H66AGY6C1J7T01A/joined/top_5*.csv
deciles_chart_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
deciles-charts:v0.0.33
--input-files output/01GTM8RXTN1H66AGY6C1J7T01A/joined/measure_practice_rate_deciles.csv
--output-dir output/01GTM8RXTN1H66AGY6C1J7T01A/joined
config:
show_outer_percentiles: true
tables:
output: true
charts:
output: true
needs: [generate_measures_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
deciles_charts: output/01GTM8RXTN1H66AGY6C1J7T01A/joined/deciles_*.*
plot_measure_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
python:latest python analysis/plot_measures.py
--breakdowns="sex,age,imd"
--output-dir output/01GTM8RXTN1H66AGY6C1J7T01A
needs: [generate_measures_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
measure: output/01GTM8RXTN1H66AGY6C1J7T01A/plot_measure*.png
event_counts_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
python:latest python analysis/event_counts.py --input_dir="output/01GTM8RXTN1H66AGY6C1J7T01A/joined" --output_dir="output/01GTM8RXTN1H66AGY6C1J7T01A"
needs: [join_cohorts_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
measure: output/01GTM8RXTN1H66AGY6C1J7T01A/event_counts.json
generate_report_01GTM8RXTN1H66AGY6C1J7T01A:
run: >
python:latest python analysis/render_report.py
--report-title="DMARDs & Medication Review - OpenSAFELY Service Restoration Observatory"
--population="adults"
--breakdowns="sex,age,imd"
--codelist-1-name="DMARDs"
--codelist-2-name="Medication Review - OpenSAFELY Service Restoration Observatory"
--codelist-1-link="opensafely/dmards/2020-06-23"
--codelist-2-link="opensafely/medication-review-opensafely-service-restoration-observatory/24b50f64"
--time-value="6"
--time-scale="months"
--time-event="before"
--start-date="2022-08-26"
--end-date="2023-02-22"
--num-practices=1000
--request-id="01GTM8RXTN1H66AGY6C1J7T01A"
needs: [event_counts_01GTM8RXTN1H66AGY6C1J7T01A, deciles_chart_01GTM8RXTN1H66AGY6C1J7T01A, top_5_table_01GTM8RXTN1H66AGY6C1J7T01A, plot_measure_01GTM8RXTN1H66AGY6C1J7T01A]
outputs:
moderately_sensitive:
notebook: output/01GTM8RXTN1H66AGY6C1J7T01A/report.html
Timeline
-
Created:
-
Started:
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Finished:
-
Runtime: 06:09:10
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- opensafely-internal-interactive
- Requested by
- Lucy Bridges
- Branch
- main
- Force run dependencies
- Yes
- Git commit hash
- 7697e31
- Requested actions
-
-
run_all
-
Code comparison
Compare the code used in this Job Request