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Job request: 11697

Organisation:
Bennett Institute
Workspace:
shared-care-monitoring
ID:
6c4s5cvx5ui7ya76
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Andrew Brown 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

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000

actions:
         
  generate_study_population_1:
     run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-12-01 to 2022-08-01 by month" --output-format csv.gz
     outputs:
       highly_sensitive:
         cohort: output/input_*.csv.gz

  generate_study_population_2:
     run: cohortextractor:latest generate_cohort --study-definition study_definition_levothyroxine --index-date-range "2019-12-01 to 2022-08-01 by month" --output-format csv.gz
     outputs:
       highly_sensitive:
         cohort: output/input_levo*.csv.gz
       
  generate_study_population_ethnicity:    
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_ethnicity.csv.gz

  join_cohorts:
    run: >
      cohort-joiner:v0.0.41
        --lhs output/input_20*.csv.gz
        --rhs output/input_ethnicity.csv.gz
        --output-dir output/joined
    needs: [generate_study_population_1, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/joined/input_20*.csv.gz
                  
  generate_measures:
     run: cohortextractor:latest generate_measures --study-definition study_definition --skip-existing --output-dir output/joined
     needs: [join_cohorts]
     outputs:
       moderately_sensitive:
         measure_csv: output/joined/measure_*_rate.csv
         
  generate_measures_levothyroxine:
     run: cohortextractor:latest generate_measures --study-definition study_definition_levothyroxine --skip-existing --output-dir output
     needs: [generate_study_population_2]
     outputs:
       moderately_sensitive:
         measure_csv: output/measure_levo*_rate.csv
         
  generate_practice_deciles_charts:
     run: >
       deciles-charts:v0.0.30
         --input-files output/joined/measure_all_sc_overdue_monitoring_by_practice_rate.csv
         --output-dir output
     needs: [generate_measures]
     outputs:
       moderately_sensitive:
         deciles_charts: output/deciles_*_by_practice_rate.*
         
  redact_counts:
     run: python:latest python analysis/redact_counts.py
     needs: [generate_measures, generate_measures_levothyroxine]
     outputs:
       moderately_sensitive:
         measure_csv: output/rounded/redacted_*.csv
        
  build_test_type_measure:
     run: python:latest python analysis/build_test_type_measure.py
     needs: [generate_measures, generate_measures_levothyroxine, redact_counts]
     outputs:
       moderately_sensitive:
         counts: output/rounded/redacted_test_type.csv
              
  generate_plots:
     run: python:latest python analysis/plots.py
     needs: [generate_measures, generate_measures_levothyroxine, redact_counts, build_test_type_measure]
     outputs:
       moderately_sensitive:
         counts: output/joined/plot_*.png
         
  calculate_unique_patients:
    run: python:latest python analysis/calculate_unique_patients.py
    needs: [generate_study_population_1, join_cohorts]
    outputs:
      moderately_sensitive:
        text: output/patient_count.csv
        
  calculate_rate_changes:
     run: python:latest python analysis/calculate_change.py
     needs: [generate_measures]
     outputs:
       moderately_sensitive:
         measure_csv: output/changes_*.csv

  perform_inferential_stats:
    run: r:latest analysis/impact_comparison.R
    needs: [generate_measures]
    outputs: 
      moderately_sensitive:
        results_population: output/analysis/measures_population_ttest.csv
        results_subgroups: output/analysis/measures_subgroup_ttest_heterogeneity.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:52

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

Job information

Status
Succeeded
Backend
TPP
Workspace
shared-care-monitoring
Requested by
Andrew Brown
Branch
main
Force run dependencies
No
Git commit hash
ce85fa4
Requested actions
  • build_test_type_measure
  • generate_plots

Code comparison

Compare the code used in this Job Request