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Job request: 25439

Organisation:
King's College London
Workspace:
inflammatory_rheum
ID:
h2kixynzirm277z2
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Mark Russell 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: '4.0'

actions:
             
  generate_dataset_incidence:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_incidence.py --output output/dataset_incidence.csv
    outputs:
      highly_sensitive:
        cohort: output/dataset_incidence.csv
  
  generate_dataset_incidence_ref:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_incidence_ref.py --output output/dataset_incidence_ref.csv
    outputs:
      highly_sensitive:
        cohort: output/dataset_incidence_ref.csv 

  generate_dataset_eia:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_eia.py --output output/dataset_eia.csv
    needs: [generate_dataset_incidence]
    outputs:
      highly_sensitive:
        cohort: output/dataset_eia.csv       

  generate_measures_2016:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2016.csv
      --
      --start-date "2016-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2016.csv

  generate_measures_2017:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2017.csv
      --
      --start-date "2017-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2017.csv             

  generate_measures_2018:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2018.csv
      --
      --start-date "2018-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2018.csv

  generate_measures_2019:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2019.csv
      --
      --start-date "2019-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2019.csv

  generate_measures_2020:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2020.csv
      --
      --start-date "2020-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2020.csv

  generate_measures_2021:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2021.csv
      --
      --start-date "2021-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2021.csv

  generate_measures_2022:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2022.csv
      --
      --start-date "2022-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2022.csv

  generate_measures_2023:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2023.csv
      --
      --start-date "2023-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2023.csv

  generate_measures_2024:
    run: ehrql:v1 generate-measures analysis/dataset_definition_incidence_measures.py
      --output output/measures/measures_incidence_2024.csv
      --
      --start-date "2024-04-01"
      --intervals 12
    needs: [generate_dataset_incidence]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_incidence_2024.csv

  incidence_cleaning:
    run: stata-mp:latest analysis/001_incidence_cleaning.do
    needs: [generate_dataset_incidence, generate_measures_2016, generate_measures_2017, generate_measures_2018, generate_measures_2019, generate_measures_2020, generate_measures_2021, generate_measures_2022, generate_measures_2023, generate_measures_2024]
    outputs:
      moderately_sensitive:
        log1: logs/incidence_cleaning.log   
        table1: output/tables/incidence_rates_rounded.csv
        table2: output/tables/incidence_rates_rounded_subgroups.csv
        tabke3: output/tables/baseline_table_rounded.csv
        
  incidence_graphs:
    run: stata-mp:latest analysis/002_incidence_graphs.do
    needs: [incidence_cleaning]
    outputs:
      moderately_sensitive:
        log1: logs/incidence_graphs.log   
        figure1: output/figures/inc_rate_*.svg
        figure2: output/figures/inc_comp_*.svg
        figure3: output/figures/adj_sex_*.svg
        figure4: output/figures/unadj_age_*.svg
        figure5: output/figures/unadj_imd_*.svg
        figure6: output/figures/unadj_ethn_*.svg

  reference_cleaning:
    run: stata-mp:latest analysis/003_reference_cleaning.do
    needs: [generate_dataset_incidence_ref]
    outputs:
      moderately_sensitive:
        log1: logs/reference_cleaning.log   
        table1: output/tables/reference_table_rounded.csv

  run_sarima:
    run: r:latest analysis/200_sarima.R
    needs: [incidence_cleaning]
    outputs:
      moderately_sensitive:
        log1: logs/sarima_log.txt   
        figure1: output/figures/auto_residuals_*.svg
        figure2: output/figures/obs_pred_*.svg
        table1: output/tables/change_incidence_byyear.csv

  # eia_cleaning:
  #   run: stata-mp:latest analysis/100_eia_cleaning.do
  #   needs: [generate_dataset_incidence, generate_dataset_eia]
  #   outputs:
  #     highly_sensitive:
  #       log1: logs/eia_dataset.log   
  #       data1: output/data/file_eia_all.dta  

  # run_box_plots:
  #   run: stata-mp:latest analysis/300_box_plots.do
  #   needs: [eia_cleaning]
  #   outputs:
  #     moderately_sensitive:
  #       log1: logs/box_plots.log   
  #       figure 1: output/figures/regional_qs2_bar_*.svg 
  #       figure 2: output/figures/regional_csdmard_bar_*.svg

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 32:06:39

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

Job request

Status
Succeeded
Backend
TPP
Workspace
inflammatory_rheum
Requested by
Mark Russell
Branch
main
Force run dependencies
Yes
Git commit hash
b74162a
Requested actions
  • run_all

Code comparison

Compare the code used in this job request