Skip to content

Job request: 25299

Organisation:
King's College London
Workspace:
zoster_incidence_imids
ID:
6xw6zwbcaibr6u43
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Zijing Yang 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:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_2.py --output output/dataset.arrow
    outputs:
      highly_sensitive:
        dataset: output/dataset.arrow

  generate_incident_treatment_dataset:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_drug.py --output output/dataset_incident_treatment.arrow
    outputs:
      highly_sensitive:
        dataset: output/dataset_incident_treatment.arrow

  data_cleaning:
    run: r:latest analysis/data_cleaning.R
    needs:
    - generate_dataset
    outputs:
      highly_sensitive:
        table1: output/dt.csv

  data_cleaning_treatment:
    run: r:latest analysis/data_cleaning_treatment.R
    needs:
    - generate_incident_treatment_dataset
    outputs:
      highly_sensitive:
        table1: output/dt_incident_treatment.csv
      moderately_sensitive:
        table2: output/drug_freq_by_disease.csv
        table3: output/drug_freq_by_disease_redact.csv

  Incidence_by_drug:
    run: r:latest analysis/Incidence_by_drug.R
    needs:
    - data_cleaning_treatment
    outputs:
      moderately_sensitive:
        table1: output/csDMARD_freq_arthritis_redact.csv


  generate_zoster_prevalence:
    run: ehrql:v1 generate-measures analysis/population_measure_V2.py --output output/Incidence_age_gender_measure.csv
    outputs:
      highly_sensitive:
        measure: output/Incidence_age_gender_measure.csv
        
  Baseline_table:
    run: r:latest analysis/baseline_table.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/baseline_by_imids.csv
        table2: output/baseline_all_imids.csv
        table3: output/baseline_categorical_redact.csv
        table4: output/baseline_continuous_redact.csv       

  practice_registrations_table:
    run: r:latest analysis/practice_registrations_table.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/combined_imid_summary.csv

  Incidence_rate_agge:
    run: r:latest analysis/age_zosterrate_V2.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/Zoster_incidence_proportion_by_exact_age.csv
        table2: output/Zoster_incidence_proportion_by_agegroup.csv
        table3: output/Zoster_incidence_proportion_by_exact_age_redact.csv
        table4: output/Zoster_incidence_proportion_by_agegroup_redact.csv

  Incidence_rate_age_gender:
    run: r:latest analysis/age_gender_zosterrate.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/Zoster_incidence_proportion_by_exact_age_gender_redact.csv
        table2: output/Zoster_incidence_proportion_by_agegroup_gender_redact.csv

  Vaccination_table:
    run: r:latest analysis/vaccination_region_year.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/vaccination_summary.csv
        table2: output/eligiable_vaccination_summary.csv
        table3: output/vaccination_summary_redact.csv
        table4: output/eligiable_vaccination_summary_redact.csv

  Incidence_overall_table:
    run: r:latest analysis/Incidence_imids_diag_V4.R
    needs:
    - data_cleaning
    outputs:
      moderately_sensitive:
        table1: output/Adjusted_incidence_overall_redact.csv
        table2: output/Crude_incidence_allimids_redact.csv

  Incidence_adjusted_table:
    run: r:latest analysis/Incidence_imids_age_gender_V2.R
    needs:
    - data_cleaning
    outputs:
     moderately_sensitive:
        table1: output/Ajusted_incidence_allimids.csv
        table2: output/Adjusted_incidence_allimids_quarterly.csv
        table3: output/Adjusted_incidence_allimids_redact.csv
        table4: output/Adjusted_incidence_allimids_quarterly_redact.csv

  Incidence_adjusted_plot:
    run: r:latest analysis/Quarterly_incidence_plot.R
    needs:
    - data_cleaning
    - Incidence_adjusted_table
    outputs:
     moderately_sensitive:
        plot1: output/Incidence_quarterly_plot.png
        plot2: output/Incidence_quarterly_IMID_plot.png

  Incidence_adjusted_incident_table:
    run: r:latest analysis/Incidence_imids_age_gender_incident.R
    needs:
    - data_cleaning
    outputs:
     moderately_sensitive:
        table1: output/Ajusted_incidence_allimids_incident.csv

  Incidence_adjusted_region_table:
    run: r:latest analysis/Incidence_imids_age_gender_region_V1.R
    needs:
    - data_cleaning
    outputs:
     moderately_sensitive:
        table1: output/Adjusted_incidence_by_region_part1.csv
        table2: output/Adjusted_incidence_by_region_part2.csv
        table3: output/Adjusted_incidence_by_region_period2022.csv
        table4: output/Adjusted_incidence_by_region_period2021.csv
        table5: output/Adjusted_incidence_by_region_part1_redact.csv
        table6: output/Adjusted_incidence_by_region_part2_redact.csv
        table7: output/Adjusted_incidence_by_region_period2022_redact.csv
        table8: output/Adjusted_incidence_by_region_period2021_redact.csv


  Incidence_adjusted_covid_table:
    run: r:latest analysis/Incidence_imids_age_gender_covid.R
    needs:
    - data_cleaning
    outputs:
     moderately_sensitive:
        table1: output/Adjusted_incidence_by_imids_period2021_redact.csv
        table2: output/Adjusted_incidence_by_imids_period2022_redact.csv
        table3: output/Adjusted_incidence_by_allimids_region_period2021_redact.csv
        table4: output/Adjusted_incidence_by_allimids_period2022_redact.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:27

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

Job request

Status
Succeeded
Backend
TPP
Workspace
zoster_incidence_imids
Requested by
Zijing Yang
Branch
main
Force run dependencies
No
Git commit hash
d880139
Requested actions
  • Incidence_by_drug

Code comparison

Compare the code used in this job request