Job request: 13522

Organisation:: King's College London
Workspace:: early-inflammatory-arthritis
ID:: vivonhfumijscypo

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 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

Action:

create_cohorts

Status:

Status: Succeeded

Job identifier:

7ybp4yonifyab6dl
Action:

run_box_plots

Status:

Status: Succeeded

Job identifier:

jiwxw22vka7prgmd
Action:

run_itsa_models

Status:

Status: Succeeded

Job identifier:

p2gx3v35d5ujfq7i
Action:

run_baseline_tables

Status:

Status: Succeeded

Job identifier:

sswjxqynyvslfxmu
Action:

run_redacted_tables

Status:

Status: Succeeded

Job identifier:

vdwxvm7rfely2ark
Action:

run_itsa_models_drugs

Status:

Status: Succeeded

Job identifier:

wu3v5xansu6n356v
Action:

convert_image_formats

Status:

Status: Succeeded

Job identifier:

uoobbvw72jnf2efe
Action:

generate_notebook

Status:

Status: Succeeded

Job identifier:

i4o3ltv7jvvdmp54

Pipeline

Show project.yaml

version: '3.0'

expectations:
  population_size: 400000

actions:

  generate_study_population_allpts:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_allpts
    outputs:
      highly_sensitive:
        cohort: output/input_allpts.csv
                  
  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
    outputs:
      highly_sensitive:
        cohort: output/input.csv
  
  create_cohorts_allpts:
    run: stata-mp:latest analysis/001_define_covariates_allpts.do
    needs: [generate_study_population_allpts]
    outputs:
      highly_sensitive:
        log1: logs/cleaning_dataset_allpts.log 
        data1: output/data/file_eia_allpts.dta        

  create_cohorts:
    run: stata-mp:latest analysis/000_define_covariates.do
    needs: [generate_study_population]
    outputs:
      highly_sensitive:
        log1: logs/cleaning_dataset.log 
        data1: output/data/file_eia_all.dta

  run_baseline_tables_allpts:
    run: stata-mp:latest analysis/101_baseline_characteristics_allpts.do
    needs: [create_cohorts_allpts]
    outputs:
      moderately_sensitive:
        log1: logs/descriptive_tables_allpts.log      
        doc1: output/tables/baseline_allpts.csv      

  run_baseline_tables:
    run: stata-mp:latest analysis/100_baseline_characteristics.do
    needs: [create_cohorts]
    outputs:
      moderately_sensitive:
        log1: logs/descriptive_tables.log   
        doc1: output/tables/baseline_bydiagnosis.csv   
        doc2: output/tables/baseline_byyear.csv 
        doc3: output/tables/referral_bydiag_nomiss.csv   
        doc4: output/tables/referral_byyear_nomiss.csv   
        doc5: output/tables/referral_byregion_nomiss.csv   
        doc6: output/tables/drug_bydiag_miss.csv 
        doc7: output/tables/drug_byyear_miss.csv 
        doc8: output/tables/drug_byyear_ra_miss.csv   
        doc9: output/tables/drug_byyear_psa_miss.csv
        doc10: output/tables/drug_byyear_undiff_miss.csv
        doc11: output/tables/drug_byyearanddisease.csv
        doc12: output/tables/drug_byyearandregion.csv
        doc13: output/tables/diag_count_bymonth.csv
        doc14: output/tables/diag_count_byyear.csv
        doc15: output/tables/appt_count_bymonth.csv
        doc16: output/tables/diag_count_byyear_ethn.csv
        doc17: output/tables/diag_count_byyear_imd.csv
        doc18: output/tables/diag_count_bymonth_female.csv
        doc19: output/tables/diag_count_bymonth_male.csv
        doc20: output/tables/diag_count_byyear_female.csv
        doc21: output/tables/diag_count_byyear_male.csv
        figure1: output/figures/incidence_twoway_rounded.svg
        figure2: output/figures/incidence_twoway_appt.svg
        figure3: output/figures/incidence_twoway_rounded_female.svg
        figure4: output/figures/incidence_twoway_rounded_male.svg
  
  run_itsa_models:
    run: stata-mp:latest analysis/200_itsa_models.do
    needs: [create_cohorts]
    outputs:
      moderately_sensitive:
        log1: logs/itsa_models.log   
        figure1:  output/figures/ITSA_diagnostic_delay_newey.svg
        figure2:  output/figures/ITSA_diagnostic_delay_prais.svg
        figure3:  output/figures/ITSA_diagnostic_delay_GP_newey.svg
        figure4:  output/figures/ITSA_diagnostic_delay_GP_prais.svg
        doc1: output/tables/gp_to_appt_ITSA_table.csv
  
  run_itsa_models_drugs:
    run: stata-mp:latest analysis/201_itsa_models_drugs.do
    needs: [create_cohorts]
    outputs:
      moderately_sensitive:
        log1: logs/itsa_models_drugs.log   
        figure1:  output/figures/ITSA_csDMARD_delay_newey.svg
        figure2:  output/figures/ITSA_csDMARD_delay_prais.svg
        figure3: output/figures/ITSA_csDMARD_delay_newey_sensitivity.svg
        figure4: output/figures/ITSA_csDMARD_delay_prais_sensitivity.svg
        doc1: output/tables/appt_to_csdmard_ITSA_table.csv

  run_box_plots:
    run: stata-mp:latest analysis/300_box_plots.do
    needs: [create_cohorts]
    outputs:
      moderately_sensitive:
        log1: logs/box_plots.log
        figure 1: output/figures/regional_qs1_bar_overall.svg
        figure 2: output/figures/regional_qs1_bar_2019.svg 
        figure 3: output/figures/regional_qs1_bar_2020.svg       
        figure 4: output/figures/regional_qs2_bar_overall.svg  
        figure 5: output/figures/regional_qs2_bar_2019.svg 
        figure 6: output/figures/regional_qs2_bar_2020.svg    
        figure 7: output/figures/regional_qs2_bar_GP_overall.svg  
        figure 8: output/figures/regional_qs2_bar_GP_2019.svg     
        figure 9: output/figures/regional_qs2_bar_GP_2020.svg 
        figure 10: output/figures/regional_qs2_bar_GP_merged.svg
        figure 11: output/figures/regional_qs2_bar_GP_ethnicity.svg
        figure 12: output/figures/regional_qs2_bar_GP_imd.svg
        figure 13: output/figures/regional_csdmard_bar_overall.svg  
        figure 14: output/figures/regional_csdmard_bar_2019.svg     
        figure 15: output/figures/regional_csdmard_bar_2020.svg 
        figure 16: output/figures/regional_csdmard_bar_merged.svg
        figure 17: output/figures/regional_csdmard_bar_ethnicity.svg
        figure 18: output/figures/regional_csdmard_bar_imd.svg

  run_redacted_tables:
    run: stata-mp:latest analysis/400_redacted_tables.do
    needs: [create_cohorts]
    outputs:
      moderately_sensitive:
        log1: logs/redacted_tables.log   
        doc1: output/tables/table_1_rounded_bydiag.csv   
        doc2: output/tables/table_mean_bydiag_rounded.csv 
        doc3: output/tables/table_median_bydiag_rounded.csv   
        doc4: output/tables/table_median_bydiag_rounded_to21.csv   
        doc5: output/tables/ITSA_tables_appt_delay_rounded.csv   
        doc6: output/tables/ITSA_tables_csdmard_delay_rounded.csv 
        doc7: output/tables/drug_byyearanddisease_rounded.csv 
        doc8: output/tables/first_csdmard_rounded.csv   
        doc9: output/tables/drug_byyearandregion_rounded.csv
        doc10: output/tables/referral_byregion_rounded.csv
        doc11: output/tables/consultation_medium_rounded.csv
        doc12: output/tables/table_median_bydiag_rounded_to21_report.csv 
        doc13: output/tables/first_csdmard_rounded_report.csv  

  run_redacted_tables_allpts:
    run: stata-mp:latest analysis/401_redacted_tables_allpts.do
    needs: [create_cohorts_allpts]
    outputs:
      moderately_sensitive:
        log1: logs/redacted_tables_allpts.log   
        doc1: output/tables/table_1_rounded_allpts.csv  

  convert_image_formats:
    run: python:latest python analysis/convert_images.py --input_dir output/figures --output_dir output/figures
    needs: [run_baseline_tables, run_itsa_models, run_itsa_models_drugs, run_box_plots, run_redacted_tables]
    outputs:
      moderately_sensitive:
        figures: output/figures/*.png           

  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: [convert_image_formats,run_baseline_tables, run_itsa_models, run_itsa_models_drugs, run_box_plots, run_redacted_tables]
    outputs:
      moderately_sensitive:
        notebook: output/report.html

Timeline

Created: 1 year, 11 months ago 25 Nov 2022 19:57:34 UTC
Started: 1 year, 11 months ago 25 Nov 2022 19:57:18 UTC
Finished: 1 year, 11 months ago 25 Nov 2022 20:04:46 UTC
Runtime: 00:08:52

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

Job information

Status: Succeeded
Backend: TPP
Workspace: early-inflammatory-arthritis
Requested by: Mark Russell
Branch: main
Force run dependencies: No
Git commit hash: 98055bb
Requested actions: create_cohorts

run_baseline_tables

run_itsa_models

run_itsa_models_drugs

run_box_plots

run_redacted_tables

convert_image_formats

generate_notebook

Code comparison

Compare the code used in this Job Request