This page shows the technical details of what happened when authorised researcher Chris Yeung 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:
-
cbhcyo3utojcuzl4
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2021-02-01 by month" --output-dir=output
outputs:
highly_sensitive:
cohort: output/input_*.csv
generate_study_population_practice_count:
run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output
outputs:
highly_sensitive:
cohort: output/input_practice_count.csv
generate_measures:
run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
needs: [generate_study_population]
outputs:
moderately_sensitive:
measure_csv: output/measure_*.csv
get_practice_count:
run: python:latest python analysis/get_practice_count.py
needs: [generate_study_population_practice_count]
outputs:
moderately_sensitive:
text: output/practice_count.json
get_patient_count:
run: python:latest python analysis/get_patients_counts.py
needs: [generate_study_population]
outputs:
moderately_sensitive:
text: output/patient_count.json
generate_notebook:
run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
needs: [generate_measures, get_practice_count, get_patient_count]
outputs:
moderately_sensitive:
notebook: output/sentinel_measures.html
# generate_notebook_practice:
# run: jupyter:latest jupyter nbconvert /workspace/notebooks/sentinel_measures_by_practice.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
# needs: [generate_measures, get_practice_count, get_patient_count]
# outputs:
# moderately_sensitive:
# notebook: output/sentinel_measures_by_practice.html
# csvs: output/*_check.csv
get_event_summary:
run: python:latest python analysis/get_event_summary.py
needs: [generate_study_population]
outputs:
moderately_sensitive:
text: output/*_event_summary.csv
Timeline
-
Created:
-
Started:
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Finished:
-
Runtime:
These timestamps are generated and stored using the UTC timezone on the backend.
Job information
- Status
-
Failed
Job exited with an error code
- Backend
- GRAPHNET
- Workspace
- sro-measure-cam-test
- Requested by
- Chris Yeung
- Branch
- graphnet
- Force run dependencies
- No
- Git commit hash
- 9939d86
- Requested actions
-
-
generate_study_population
-