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Job request: 25958

Organisation:
University of Nottingham
Workspace:
measures-testing
ID:
4xqm3sjcdy2vtqbq
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Weiyao Meng 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

  • Action:
    generate_patient_measures_for_practices
    Status:
    Pending
    Job identifier:
    nzvqlwe4g7f7nzjx
  • Action:
    process_measures_to_practice_dataset
    Status:
    Pending
    Job identifier:
    2amvixwqdya3thnl
  • Action:
    generate_patient_measures_population_structure
    Status:
    Pending
    Job identifier:
    hs7mxqtpdkzdrigr
  • Action:
    process_patient_measures_population_structure
    Status:
    Pending
    Job identifier:
    p4ujfcbg4xdrblpk
  • Action:
    process_practice_dataset_stp
    Status:
    Pending
    Job identifier:
    3tij2skjflrx4rjf
  • Action:
    process_practice_dataset_region
    Status:
    Pending
    Job identifier:
    256cxmt3mmfybjvt
  • Action:
    process_practice_size_distribution
    Status:
    Pending
    Job identifier:
    zdjfrsvsensckkwm

Pipeline

Show project.yaml 
version: '4.0'

actions:
  # generate_dataset:
  #   run: ehrql:v1 generate-dataset analysis/dataset_definition_patients.py --output output/dataset_patients.csv.gz
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/dataset_patients.csv.gz

  #################################################################
  # Actions defined for checking pregnancy variables

  generate_dataset_preg_2024_11_01:
    run: ehrql:v1 generate-dataset analysis/check_pregnancy_variables/dataset_definition_pregnancy.py --output output/dataset_preg_2024_11_01.csv.gz -- --start_date 2024-11-01
    outputs:
      highly_sensitive:
        dataset: output/dataset_preg_2024_11_01.csv.gz

  generate_dataset_preg_2025_11_01:
    run: ehrql:v1 generate-dataset analysis/check_pregnancy_variables/dataset_definition_pregnancy.py --output output/dataset_preg_2025_11_01.csv.gz -- --start_date 2025-11-01
    outputs:
      highly_sensitive:
        dataset: output/dataset_preg_2025_11_01.csv.gz

  generate_dataset_preg_measures:
    run: ehrql:v1 generate-measures analysis/check_pregnancy_variables/dataset_definition_pregnancy_measures.py --output output/measures/:csv
    outputs:
      moderately_sensitive:
        dataset: output/measures/*.csv

  analyse_preg_measures:
    run: python:v2 analysis/check_pregnancy_variables/pregnancy_checks.py --output output/measures/pregnancy_checks.csv --input output/measures/*.csv
    needs: 
      [generate_dataset_preg_measures]
    outputs:
      moderately_sensitive:
        dataset: output/measures/*by_year.csv
        charts: output/measures/*by_year.png
  
  #################################################################
  # Actions for retrieving patient-level data for each specified month AND combine all into one csv.gz for downstream analysis

  # retrieve csv.gz for each specified month
  generate_patient_dataset_2024_02_01:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_patients.py --dummy-tables dummy_tables --output output/dataset_patients_2024-02-01.csv.gz -- --start_date 2024-02-01
    outputs:
      highly_sensitive:
        dataset: output/dataset_patients_2024-02-01.csv.gz
  generate_patient_dataset_2024_03_01:
    run: ehrql:v1 generate-dataset analysis/dataset_definition_patients.py --dummy-tables dummy_tables --output output/dataset_patients_2024-03-01.csv.gz -- --start_date 2024-03-01
    outputs:
      highly_sensitive:
        dataset: output/dataset_patients_2024-03-01.csv.gz

  # combine monthly tables into one csv.gz
  combine_monthly_patient_gz:
    run: python:v2 analysis/preprocess_combine_gz.py --output output/dataset_patients_combined.csv.gz
    needs: [generate_patient_dataset_2024_02_01, generate_patient_dataset_2024_03_01]
    outputs:
      highly_sensitive:
        dataset: output/dataset_patients_combined.csv.gz

  #################################################################
  # patient-level measures for sense checking; not final measures for analysis
  
  # # local testing with dummy tables
  # generate_patient_measures_population_structure:
  #   run: ehrql:v1 generate-measures analysis/validation/measures_patient_population_structure.py --dummy-tables dummy_tables --output output/patient_measures_population_structure.csv
  #   outputs:
  #     moderately_sensitive:
  #       measure_tables: output/patient_measures_population_structure.csv
  
  generate_patient_measures_population_structure:
    run: ehrql:v1 generate-measures analysis/validation/measures_patient_population_structure.py --output output/patient_measures_population_structure.csv
    outputs:
      moderately_sensitive:
        measure_tables: output/patient_measures_population_structure.csv
  
  process_patient_measures_population_structure:
    run: python:v2 analysis/validation/process_measure_population_structure.py --output output/patient_measures_population_structure_longformat.csv
    needs: [generate_patient_measures_population_structure]
    outputs:
      moderately_sensitive:
        measure_tables: output/patient_measures_population_structure_longformat.csv
  
  # TO ADD: measures for checking PF eligibility variables; consultation count variables
  
  #################################################################
  # Actions defined for getting measures and aggregating into practice-level

  # practice-level data step 1: run patient dataset measures 

  # # version for debugging
  # generate_patient_measures_for_practices:
  #   run: ehrql:v1 generate-measures analysis/practice_variables/measures_practice.py --dummy-tables dummy_tables --output output/practice_measures.csv
  #   outputs:
  #     highly_sensitive:
  #       measure_tables: output/practice_measures.csv

  generate_patient_measures_for_practices:
    run: ehrql:v1 generate-measures analysis/practice_variables/measures_practice.py --output output/practice_measures.csv
    outputs:
      highly_sensitive:
        measure_tables: output/practice_measures.csv
  
  # practice-level data step 2: aggregate patient measures to practice-level data
  process_measures_to_practice_dataset:
    run: python:v2 analysis/practice_variables/process_measures_to_practice_dataset.py --output output/practice_level_data.csv
    needs: [generate_patient_measures_for_practices]
    outputs:
      moderately_sensitive:
        practice_level_data: output/practice_level_data.csv
  
  # practice-level data step 3: extract info from practice-level data
  process_practice_dataset_stp:
    run: python:v2 analysis/practice_variables/practice_to_stp.py --output output/practice_summary_by_stp.csv
    needs: [process_measures_to_practice_dataset]
    outputs:
      moderately_sensitive:
        practice_level_data: output/practice_summary_by_stp.csv
  
  process_practice_dataset_region:
    run: python:v2 analysis/practice_variables/practice_to_region.py --output output/practice_summary_by_region.csv
    needs: [process_measures_to_practice_dataset]
    outputs:
      moderately_sensitive:
        practice_level_data: output/practice_summary_by_region.csv
  
  process_practice_size_distribution:
    run: python:v2 analysis/practice_variables/practice_size_distribution.py --output output/practice_size_distribution.png
    needs: [process_measures_to_practice_dataset]
    outputs:
      moderately_sensitive:
        practice_level_plot: output/practice_size_distribution.png

  #################################################################

# https://actions.opensafely.org/actions/safetab/v3.0.2/
# safetabs: create two-way tables for the specified variables; redact results for small numbers
  # generate_safetabs:
  #   run: safetab:v3.0.2 output/dataset_patients_combined.csv.gz
  #   needs: [combine_monthly_patient_gz]
  #   config:
  #     output_path: output
  #     redaction_limit: 2
  #     tables:
  #       two_way:
  #         tab_type: 2-way
  #         variables:
  #           - sex
  #           - region
  #   outputs:
  #     moderately_sensitive:
  #       safetab_log: output/dataset_patients_combined.csv_tables/table_log.txt
  #       safetab_two_way: output/dataset_patients_combined.csv_tables/two_way/*.md

# https://actions.opensafely.org/actions/cohort-report/v3.0.0/
# generate cohort report; require all variable_types
  # generate_cohort_report:
  #   run: cohort-report:v3.0.0 output/dataset_patients_combined.csv.gz
  #   needs: [combine_monthly_patient_gz]
  #   config:
  #     variable_types:
  #       start_date: date
  #       index_date: date
  #       registered_start: categorical
  #       registered_index: categorical
  #       alive: categorical
  #       sex: categorical
  #       age: int
  #       date_of_birth: date
  #       imd: categorical
  #       ethnicity: categorical
  #       region: categorical
  #   outputs:
  #     moderately_sensitive:
  #       reports: cohort_reports_outputs/descriptives_dataset_patients_combined.csv.html
  #       figures: cohort_reports_outputs/*.png

# https://actions.opensafely.org/actions/dataset-report/v0.0.29/
# dataset report
  # generate_dataset_report:
  #   run: >
  #     dataset-report:v0.0.29
  #       --input-files output/dataset_patients_combined.csv.gz
  #       --output-dir output
  #   needs: [combine_monthly_patient_gz]
  #   outputs:
  #     moderately_sensitive:
  #       dataset_report: output/dataset_patients_combined.html

Timeline

  • Created:

  • Runtime:

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

Job request

Status
Pending
Backend
TPP
Workspace
measures-testing
Requested by
Weiyao Meng
Branch
main
Force run dependencies
Yes
Git commit hash
f5255c5
Requested actions
  • generate_patient_measures_population_structure
  • process_patient_measures_population_structure
  • generate_patient_measures_for_practices
  • process_measures_to_practice_dataset
  • process_practice_dataset_stp
  • process_practice_dataset_region
  • process_practice_size_distribution

Code comparison

Compare the code used in this job request