Job request: 18833
- Organisation:
- University of Manchester
- Workspace:
- hosp_rate
- ID:
- whtg2ezpq3uddach
This page shows the technical details of what happened when the authorised researcher ali 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
-
- Job identifier:
-
hlca5knn5h65lcxc
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
study_definition_hospitalisation_rate:
run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation_rate --index-date-range "2019-01-01 to 2022-02-01 by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/measures/input_*.csv.gz
generate_measures:
run: cohortextractor:latest generate_measures --study-definition study_definition_hospitalisation_rate --skip-existing --output-dir=output/measures
needs: [study_definition_hospitalisation_rate]
outputs:
moderately_sensitive:
measure_csv: output/measures/measure_*.csv
generate_notebook_hospitalisation_rate:
run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_rate.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_rate --ExecutePreprocessor.timeout=86400
needs: [generate_measures]
outputs:
moderately_sensitive:
notebook: output/hospitalisation_rate/hospitalisation_rate.html
figures: output/hospitalisation_rate/*
# study_definition_hospitalisation_rate_hxdx:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation_rate_hxdx --index-date-range "2019-01-01 to 2022-02-01 by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
# outputs:
# highly_sensitive:
# cohort: output/measures/input*.csv.gz
# generate_measures_hxdx:
# run: cohortextractor:latest generate_measures --study-definition study_definition_hospitalisation_rate_hxdx --skip-existing --output-dir=output/measures
# needs: [study_definition_hospitalisation_rate_hxdx]
# outputs:
# moderately_sensitive:
# measure_csv: output/measures/measur_*.csv
# generate_notebook_hospitalisation_rate_hxdx:
# run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_rate_hxdx.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_rate_hxdx --ExecutePreprocessor.timeout=86400
# needs: [generate_measures_hxdx]
# outputs:
# moderately_sensitive:
# notebook: output/hospitalisation_rate_hxdx/hospitalisation_rate_hxdx.html
# figures: output/hospitalisation_rate_hxdx/*
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 00:18:52
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Code comparison
Compare the code used in this Job Request