Job request: 17219
- Organisation:
- Bennett Institute
- Workspace:
- opensafely-internal-interactive
- ID:
- yls3p6z4sxzv5hfb
This page shows the technical details of what happened when the authorised researcher George Hickman 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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3cucfoee3j7tudyu
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- Job identifier:
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qhbmaz5j5np6j5kd
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- Job identifier:
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iz6ldu5i4ff7m3w3
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- Job identifier:
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jej4lnhao4g7ozrk
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- Job identifier:
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wdhuqlgcrstpyu5i
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- Job identifier:
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qgptpkzitcxdp6iv
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- Job identifier:
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3c2kleitc4bnh2jy
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- Job identifier:
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u53tzfga2dnlqqse
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population_ethnicity_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--param end_date="2023-03-31"
--output-dir output/01GYA0FM7C9PVSZAKS85ZBBZWX --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/01GYA0FM7C9PVSZAKS85ZBBZWX/input_ethnicity.csv.gz
generate_study_population_01GYA0FM7C9PVSZAKS85ZBBZWX:
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="1"
--param time_ever="False"
--param time_scale="years"
--param time_event="before"
--param codelist_2_comparison_date="end_date"
--param operator="AND"
--param population="adults"
--param breakdowns="sex,age,ethnicity"
--index-date-range="2019-09-01 to 2023-03-31 by month"
--output-dir=output/01GYA0FM7C9PVSZAKS85ZBBZWX
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/01GYA0FM7C9PVSZAKS85ZBBZWX/input_*.csv.gz
join_cohorts_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: >
cohort-joiner:v0.0.38
--lhs output/01GYA0FM7C9PVSZAKS85ZBBZWX/input_20*.csv.gz
--rhs output/01GYA0FM7C9PVSZAKS85ZBBZWX/input_ethnicity.csv.gz
--output-dir output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined
needs: [generate_study_population_01GYA0FM7C9PVSZAKS85ZBBZWX, generate_study_population_ethnicity_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
highly_sensitive:
cohort: output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined/input_20*.csv.gz
generate_measures_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: >
python:latest -m analysis.measures
--breakdowns="sex,age,ethnicity"
--input_dir="output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined"
needs: [join_cohorts_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
moderately_sensitive:
measure: output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined/measure_all.csv
decile_measure: output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined/measure_practice_rate_deciles.csv
top_5_table_01GYA0FM7C9PVSZAKS85ZBBZWX:
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/01GYA0FM7C9PVSZAKS85ZBBZWX"
needs: [generate_measures_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
moderately_sensitive:
tables: output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined/top_5*.csv
plot_measure_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: >
python:latest python analysis/plot_measures.py
--breakdowns="sex,age,ethnicity"
--output-dir output/01GYA0FM7C9PVSZAKS85ZBBZWX
needs: [generate_measures_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
moderately_sensitive:
measure: output/01GYA0FM7C9PVSZAKS85ZBBZWX/plot_measure*.png
deciles: output/01GYA0FM7C9PVSZAKS85ZBBZWX/deciles_chart.png
event_counts_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: >
python:latest python analysis/event_counts.py --input_dir="output/01GYA0FM7C9PVSZAKS85ZBBZWX/joined" --output_dir="output/01GYA0FM7C9PVSZAKS85ZBBZWX"
needs: [join_cohorts_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
moderately_sensitive:
measure: output/01GYA0FM7C9PVSZAKS85ZBBZWX/event_counts.json
generate_report_01GYA0FM7C9PVSZAKS85ZBBZWX:
run: >
python:latest python analysis/render_report.py
--output-dir="output/01GYA0FM7C9PVSZAKS85ZBBZWX"
--population="adults"
--breakdowns="sex,age,ethnicity"
--codelist-1-name="DMARDs"
--codelist-2-name="Care planning medication review simple reference set - NHS Digital"
--codelist-1-link="opensafely/dmards/2020-06-23"
--codelist-2-link="opensafely/care-planning-medication-review-simple-reference-set-nhs-digital/61b13c39"
--time-value="1"
--time-scale="years"
--time-event="before"
--start-date="2019-09-01"
--end-date="2023-03-31"
needs: [event_counts_01GYA0FM7C9PVSZAKS85ZBBZWX, top_5_table_01GYA0FM7C9PVSZAKS85ZBBZWX, plot_measure_01GYA0FM7C9PVSZAKS85ZBBZWX]
outputs:
moderately_sensitive:
notebook: output/01GYA0FM7C9PVSZAKS85ZBBZWX/report.html
Timeline
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Created:
-
Started:
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Finished:
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Runtime: 16:05:55
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job request
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- opensafely-internal-interactive
- Requested by
- George Hickman
- Branch
- main
- Force run dependencies
- Yes
- Git commit hash
- 96f81a4
- Requested actions
-
-
run_all
-
Code comparison
Compare the code used in this job request