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Job request: 17674

Organisation:
Bennett Institute
Workspace:
pincer-measures
ID:
eakh5xe6bjzyucnd
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Louis Fisher 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

Pipeline

Show project.yaml 
version: "3.0"

expectations:
  population_size: 5000

actions:
  generate_study_population_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-09-01 to 2020-05-01 by month" --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/input_*.feather

  generate_study_population_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-06-01 to 2021-02-01 by month" --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/input*.feather

  generate_study_population_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-03-01 to 2021-09-01 by month" --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/inpu*.feather

  generate_study_population_4:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-10-01 to 2022-02-01 by month" --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/in*.feather
        
  generate_study_population_5:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-03-01 to 2023-04-01 by month" --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/i*.feather

  generate_study_population_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/input_ethnicity.feather

  join_ethnicity_region:
    run: python:latest python analysis/join_ethnicity_region.py
    needs:
      [
        generate_study_population_1,
        generate_study_population_2,
        generate_study_population_3,
        generate_study_population_4,
        generate_study_population_5,
        generate_study_population_ethnicity,
      ]
    outputs:
      highly_sensitive:
        cohort: output/inp*.feather

  filter_population:
    run: python:latest python analysis/filter_population.py
    needs: [join_ethnicity_region]
    outputs:
      highly_sensitive:
        cohort: output/input_filtered_*.feather
  
  check_asthma:
    run: python:latest python analysis/asthma_check.py
    needs: [filter_population]
    outputs:
      moderately_sensitive:
        check: output/asthma_check.json

  calculate_numerators:
    run: python:latest python analysis/calculate_numerators.py
    needs: [filter_population]
    outputs:
      highly_sensitive:
        cohort: output/indicator_e_f_*.feather

  calculate_composite_indicators:
    run: python:latest python analysis/composite_indicators.py
    needs: [calculate_numerators, filter_population]
    outputs:
      moderately_sensitive:
        counts: output/*_composite_measure.csv

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
    needs: [filter_population]
    outputs:
      moderately_sensitive:
        measure_csv: output/measure_*_rate.csv

  generate_measures_demographics:
    run: python:latest python analysis/calculate_measures.py
    needs: [calculate_numerators, filter_population]
    outputs:
      moderately_sensitive:
        counts: output/indicator_measure_*.csv
        measure_csv: output/measure*_rate.csv
        demographics: output/demographics_summary_*.csv
  
  produce_stripped_measures:
    run: python:latest python analysis/stripped_measures.py
    needs:
      [
        generate_measures,
        generate_measures_demographics
      ]
    outputs:
      moderately_sensitive:
        measures: output/measure_stripped_*.csv

  generate_summary_counts:
    run: python:latest python analysis/summary_statistics.py
    needs:
      [
        filter_population,
        generate_measures,
        generate_measures_demographics,
        calculate_numerators,
      ]
    outputs:
      moderately_sensitive:
        patient_count: output/patient_count_*.json
        practice_count: output/practice_count_*.json
        summary: output/indicator_summary_statistics_*.json

  generate_plots:
    run: python:latest python analysis/plot_measures.py
    needs:
      [
        generate_measures,
        generate_measures_demographics,
        calculate_composite_indicators,
      ]
    outputs:
      moderately_sensitive:
        counts: output/figures/plot_*.jpeg
        combined: output/figures/combined_plot_*.png
        demographics: output/demographic_aggregates.csv
        medians: output/medians.json

  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/report.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_plots, generate_summary_counts]
    outputs:
      moderately_sensitive:
        notebook: output/report.html

  generate_notebook_updating:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/report_updating.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_plots, generate_summary_counts]
    outputs:
      moderately_sensitive:
        notebook: output/report_updating.html

  generate_dem_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/demographic_report.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_plots]
    outputs:
      moderately_sensitive:
        notebook: output/demographic_report.html

  plot_Q1_comparisons:
    run: r:latest analysis/generate_demographic_slope_plot.R
    needs: [generate_plots]
    outputs:
      moderately_sensitive:
        plots: output/figures/SLOPE_*.png

  run_tests:
    run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose
    outputs:
      moderately_sensitive:
        log: output/pytest.xml

  test_population:
    run: python:latest python analysis/test_population.py
    needs: [filter_population]
    outputs:
      moderately_sensitive:
        counts: output/population_counts.csv
        count: output/patient_count_check.json

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:54

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job request

Status
Succeeded
Backend
TPP
Workspace
pincer-measures
Requested by
Louis Fisher
Branch
main
Force run dependencies
No
Git commit hash
40eb1d9
Requested actions
  • generate_notebook_updating

Code comparison

Compare the code used in this job request