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Job request: 24207

Organisation:
King's College London
Workspace:
incidence_longtermconditions
ID:
oghyprx4anjpc7jk
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: '3.0'

expectations:
  population_size: 1000

actions:
             
  generate_dataset:
    run: ehrql:v1 generate-dataset analysis/dataset_definition.py
      --output output/dataset_definition.csv
      #--
      #--diseases "{diseases}"
    outputs:
      highly_sensitive:
        cohort: output/dataset_definition.csv

  measures_dataset_pmr_2016:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2016.csv
      --
      --start-date "2016-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2016.csv

  measures_dataset_pmr_2017:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2017.csv
      --
      --start-date "2017-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2017.csv

  measures_dataset_pmr_2018:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2018.csv
      --
      --start-date "2018-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2018.csv

  measures_dataset_pmr_2019:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2019.csv
      --
      --start-date "2019-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2019.csv

  measures_dataset_pmr_2020:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2020.csv
      --
      --start-date "2020-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2020.csv

  measures_dataset_pmr_2021:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2021.csv
      --
      --start-date "2021-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2021.csv

  measures_dataset_pmr_2022:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2022.csv
      --
      --start-date "2022-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2022.csv

  measures_dataset_pmr_2023:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2023.csv
      --
      --start-date "2023-04-01"
      --intervals 12
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2023.csv

  measures_dataset_pmr_2024:
    run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
      --output output/measures/measures_dataset_pmr_2024.csv
      --
      --start-date "2024-04-01"
      --intervals 6
      --disease "pmr"
    needs: [generate_dataset]
    outputs:
      highly_sensitive:
        measure_csv: output/measures/measures_dataset_pmr_2024.csv

  # run_data_avail:
  #   run: stata-mp:latest analysis/101_data_availability.do
  #   needs: [generate_dataset]
  #   outputs:
  #     moderately_sensitive:
  #       log1: logs/data_avail_tables.log   
  #       data1: output/data/data_check_*.csv
  
  run_incidence_graphs:
    run: stata-mp:latest analysis/100_incidence_graphs.do
    needs: [generate_dataset, measures_dataset_pmr_2016, measures_dataset_pmr_2017, measures_dataset_pmr_2018, measures_dataset_pmr_2019, measures_dataset_pmr_2020, measures_dataset_pmr_2021, measures_dataset_pmr_2022, measures_dataset_pmr_2023, measures_dataset_pmr_2024]
    outputs:
      moderately_sensitive:
        log1: logs/descriptive_tables.log   
        figure1: output/figures/inc_comp_*.svg
        figure2: output/figures/prev_comp_*.svg
        figure3: output/figures/prev_adj_*.svg
        figure4: output/figures/inc_adj_ma2_*.svg
        figure5: output/figures/adj_ma_sex2_*.svg
        figure6: output/figures/adj_ma_age2_*.svg
        table1: output/tables/arima_nonstandardised.csv
        table2: output/tables/arima_standardised.csv
        table3: output/tables/arima_standardised_s.csv


  run_sarima:
    run: r:latest analysis/200_sarima.R
    needs: [run_incidence_graphs]
    outputs:
      moderately_sensitive:
        log1: logs/sarima_log.txt   
        figure1: output/figures/raw_pre_covid_*.svg
        figure2: output/figures/differenced_pre_covid_*.svg
        figure3: output/figures/seasonal_pre_covid_*.svg
        figure4: output/figures/raw_acf_*.svg
        figure5: output/figures/differenced_acf_*.svg
        figure6: output/figures/seasonal_acf_*.svg
        figure7: output/figures/auto_residuals_*.svg
        figure8: output/figures/obs_pred_*.svg
        table1: output/tables/change_incidence_byyear.csv
        table2: output/tables/values_*.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 47:47:38

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

Job request

Status
Succeeded
Backend
TPP
Workspace
incidence_longtermconditions
Requested by
Mark Russell
Branch
main
Force run dependencies
Yes
Git commit hash
ee49fe0
Requested actions
  • run_all

Code comparison

Compare the code used in this job request