Job request: 8890
- Organisation:
- University of Manchester
- Workspace:
- hosp_rate
- ID:
- 7fd7xrza4jad3ihm
This page shows the technical details of what happened when 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 indicated Requested Actions with the
Pipeline section below, you can infer what
security level
various outputs were written to. Outputs marked as
highly_sensitive
can never be viewed directly by a researcher; 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:
-
gah23i74cxsmdzf6
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: 00:00:58
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Code comparison
Compare the code used in this Job Request