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Job request: 27440

Organisation:
Department of Health and Social Care
Workspace:
sv-analysis
ID:
qk3ytamqdcv53kta
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Ailsa Prise 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_dataset
    Status:
    Running
    Job identifier:
    cyqegj6c7x26k65q
  • Action:
    measures_base
    Status:
    Pending
    Job identifier:
    vxkox2yzyszcdvqf
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    measures_demo_female_age_band
    Status:
    Pending
    Job identifier:
    h6jadtndfgv55rs6
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    measures_disorder
    Status:
    Pending
    Job identifier:
    rbq4n5b2jqrtdzfj
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    age_analysis
    Status:
    Pending
    Job identifier:
    fxwiu4i4llpi7eco
    Status message:
    waiting_on_dependencies: Waiting on dependencies
  • Action:
    plots_last_resort_prescribing
    Status:
    Pending
    Job identifier:
    mmvm7skuk75sn7zu
    Status message:
    waiting_on_dependencies: Waiting on dependencies
  • Action:
    measures_epilepsy_prescribing
    Status:
    Pending
    Job identifier:
    wpbl3654zd6c2r6s
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    rates_by_demographics
    Status:
    Pending
    Job identifier:
    vahys5mmrfqzpxf5
    Status message:
    waiting_on_dependencies: Waiting on dependencies
  • Action:
    rates_comorbidity
    Status:
    Pending
    Job identifier:
    bbetov3prftlih27
    Status message:
    waiting_on_dependencies: Waiting on dependencies
  • Action:
    measures_demo_sex
    Status:
    Pending
    Job identifier:
    bt5i4p43x2fstqjr
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    measures_demo_imd
    Status:
    Pending
    Job identifier:
    ktapbfkn2p6mcfd5
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    rates
    Status:
    Pending
    Job identifier:
    xldv7eyooynru7jc
    Status message:
    waiting_on_dependencies: Waiting on dependencies
  • Action:
    measures_comorbidity
    Status:
    Pending
    Job identifier:
    xmpouqqqzscvs7pv
    Status message:
    waiting_on_db_workers: Waiting on available database workers
  • Action:
    measures_demo_age
    Status:
    Pending
    Job identifier:
    ihrahe4cluuoujge
    Status message:
    waiting_on_db_workers: Waiting on available database workers

Pipeline

Show project.yaml 
version: '5.0'

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


  measures_base:
    run: ehrql:v1 generate-measures analysis/measures_base.py
      --output output/measures_base.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_base.csv

  measures_demo_age:
    run: ehrql:v1 generate-measures analysis/measures_demo_age.py
      --output output/measures_demo_age.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_demo_age.csv

  measures_demo_imd:
    run: ehrql:v1 generate-measures analysis/measures_demo_imd.py
      --output output/measures_demo_imd.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_demo_imd.csv

  measures_demo_sex:
    run: ehrql:v1 generate-measures analysis/measures_demo_sex.py
      --output output/measures_demo_sex.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_demo_sex.csv

  measures_demo_female_age_band:
    run: ehrql:v1 generate-measures analysis/measures_demo_female_age_band.py
      --output output/measures_demo_female_age_band.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_demo_female_age_band.csv

  measures_comorbidity:
    run: ehrql:v1 generate-measures analysis/measures_comorbidity.py
      --output output/measures_comorbidity.csv.gz
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      highly_sensitive:
        measure_csv: output/measures_comorbidity.csv.gz

  measures_disorder:
    run: ehrql:v1 generate-measures analysis/measures_disorder.py
      --output output/measures_disorder.csv.gz
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      highly_sensitive:
        measure_csv: output/measures_disorder.csv.gz

  measures_ppp_and_contraceptives:
    run: ehrql:v1 generate-measures analysis/measures_ppp_and_contraceptives.py
      --output output/measures_ppp_and_contraceptives.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_ppp_and_contraceptives.csv

  measures_birth_and_pregnancy_events:
    run: ehrql:v1 generate-measures analysis/measures_birth_and_pregnancy_events.py
      --output output/measures_birth_and_pregnancy_events.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_birth_and_pregnancy_events.csv

  measures_epilepsy_prescribing:
    run: ehrql:v1 generate-measures analysis/measures_epilepsy_prescribing.py
      --output output/measures_epilepsy_prescribing.csv
      --
      --start-date "2014-01-01"
      --intervals 144
    outputs:
      moderately_sensitive:
        measure_csv: output/measures_epilepsy_prescribing.csv

  rates:
    run: python:v2 -m analysis.plots.rates_analysis
          --output output/monthly_sv_prescribed_female_cba.svg
          --output output/monthly_new_starters_female_cba.svg
          --output output/monthly_sv_prescribed.svg
          --output output/monthly_new_starters.svg
    needs: [measures_base]
    outputs:
      moderately_sensitive:
        plot_total: output/monthly_sv_prescribed.svg
        plot_new_starter: output/monthly_new_starters.svg
        plot_sv_prescribed_females_cba: output/monthly_sv_prescribed_female_cba.svg
        plot_new_starters_females_cba: output/monthly_new_starters_female_cba.svg
        sv_new_starter_females_cba_ppp_time_series: output/sv_new_starter_females_cba_ppp_time_series.svg
        sv_prescribed_females_cba_ppp_time_series: output/sv_prescribed_females_cba_ppp_time_series.svg

  rates_comorbidity:
    run: python:v2 -m analysis.plots.sv_prescription_rates_by_condition
          --output output/prescription_rates_by_condition.svg
          --output output/prescription_rates_by_condition_interrupted_time_series.svg
    needs: [measures_comorbidity, measures_disorder]
    outputs:
      moderately_sensitive:
        plot_conditions: output/prescription_rates_by_condition.svg
        plot_conditions_interrupted_time_series: output/prescription_rates_by_condition_interrupted_time_series.svg

  age_analysis:
    run: python:v2 -m analysis.plots.age_analysis
          --output output/yearly_age_band_female_new_starter.svg
    needs: [measures_demo_female_age_band]
    outputs:
      moderately_sensitive:
        plot_new_starter: output/yearly_age_band_female_new_starter.svg

  rates_by_demographics:
    run: python:v2 -m analysis.plots.sv_prescription_demographics_timeseries
          --output output/monthly_new_sv_starters_prescribed_ratio_by_sex.svg --output output/monthly_sv_conditions_prescribed_ratio_by_sex.svg
          --output output/monthly_new_sv_starters_prescribed_ratio_by_ethnicity.svg --output output/monthly_sv_conditions_prescribed_ratio_by_ethnicity.svg
          --output output/monthly_new_sv_starters_prescribed_ratio_by_age.svg --output output/monthly_sv_conditions_prescribed_ratio_by_age.svg
          --output output/monthly_new_sv_starters_prescribed_ratio_by_region.svg --output output/monthly_sv_conditions_prescribed_ratio_by_region.svg
          --output output/monthly_new_sv_starters_prescribed_ratio_by_imd_quintile.svg --output output/monthly_sv_conditions_prescribed_ratio_by_imd_quintile.svg
    needs: [measures_demo_age, measures_demo_imd, measures_demo_sex]
    outputs:
      moderately_sensitive:
        plot_sex_new_starter: output/monthly_new_sv_starters_prescribed_ratio_by_sex.svg
        plot_sex_sv_prescriptions: output/monthly_sv_conditions_prescribed_ratio_by_sex.svg
        plot_age_new_starter: output/monthly_new_sv_starters_prescribed_ratio_by_age.svg
        plot_age_sv_prescriptions: output/monthly_sv_conditions_prescribed_ratio_by_age.svg
        plot_imd_quintile_new_starter: output/monthly_new_sv_starters_prescribed_ratio_by_imd_quintile.svg
        plot_imd_quintile_sv_prescriptions: output/monthly_sv_conditions_prescribed_ratio_by_imd_quintile.svg
  
  plots_ppp_and_contraceptives:
    run: python:v2 -m analysis.plots.plots_ppp_and_contraceptives
    needs: [measures_ppp_and_contraceptives, measures_base]
    outputs:
      moderately_sensitive:
        plot_contraceptive_use: output/monthly_contraceptive_use.svg
        plot_contraceptive_use_trendlines: output/monthly_contraceptive_use_trendlines.svg
        plot_new_starters_to_ppp_and_sv: output/new_starters_to_ppp_and_sv.svg
        plot_new_starters_to_ppp_and_sv_trendlines: output/new_starters_to_ppp_and_sv_trendlines.svg
        new_sv_starter_contraceptive_use: output/new_sv_starter_contraceptive_use.svg
        new_sv_starter_contraceptive_use_trendlines: output/new_sv_starter_contraceptive_use_trendlines.svg
        sv_prescription_females_cba_contraception_comparison: output/sv_prescription_females_cba_contraception_comparison.svg

  plots_birth_and_pregnancy_events:
    run: python:v2 -m analysis.plots.birth_and_pregnancy_events_on_sv
    needs: [measures_birth_and_pregnancy_events]
    outputs:
      moderately_sensitive:
        plot_births_or_pregnancies_with_valproate_history_ppp: output/births_or_pregnancies_with_valproate_history_ppp_trendlines.svg
        plot_births_or_pregnancies_with_valproate_history_covid: output/births_or_pregnancies_with_valproate_history_covid_trendlines.svg
        plot_valproate_history_with_births_or_pregnancies_ppp_trendlines: output/valproate_history_with_births_or_pregnancies_ppp_trendlines.svg
        plot_valproate_history_with_births_or_pregnancies_covid_trendlines: output/valproate_history_with_births_or_pregnancies_covid_trendlines.svg
        plot_births_or_pregnancies_with_recent_valproate_history_ppp: output/births_or_pregnancies_with_recent_valproate_history_ppp_trendlines.svg
        plot_births_or_pregnancies_with_recent_valproate_history_covid: output/births_or_pregnancies_with_recent_valproate_history_covid_trendlines.svg

  plots_last_resort_prescribing:
    run: python:v2 -m analysis.plots.last_resort_prescribing
    needs: [measures_epilepsy_prescribing]
    outputs:
      moderately_sensitive:
        plot_epilepsy_patient_prescribed_sv: output/epilepsy_patient_prescribed_sv.svg
        plot_prescribed_sv_has_epilepsy: output/prescribed_sv_has_epilepsy.svg
        plot_new_starter_prescribed_sv_as_first_epilepsy_med: output/new_starter_prescribed_sv_as_first_epilepsy_med.svg
        plot_new_starter_prescribed_sv_as_first_epilepsy_med_covid_trendlines: output/new_starter_prescribed_sv_as_first_epilepsy_med_covid_trendlines.svg
        plot_new_starter_prescribed_sv_as_first_epilepsy_med_ppp_trendlines: output/new_starter_prescribed_sv_as_first_epilepsy_med_ppp_trendlines.svg

Job statistics

Status Count Percentage
Pending 13 92.9%
Running 1 7.1%
Succeeded 0 0%
Failed 0 0%

0 / 14 (0%) complete

Timeline

  • Created:

  • Started:

  • Runtime:

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

Job request

Status
Running
Backend
TPP
Workspace
sv-analysis
Requested by
Ailsa Prise
Branch
main
Force run dependencies
No
Git commit hash
07e608b
Requested actions
  • generate_dataset
  • measures_base
  • measures_demo_age
  • measures_demo_imd
  • measures_demo_sex
  • measures_demo_female_age_band
  • measures_comorbidity
  • measures_disorder
  • measures_epilepsy_prescribing
  • rates
  • rates_comorbidity
  • age_analysis
  • rates_by_demographics
  • plots_last_resort_prescribing

Code comparison

Compare the code used in this job request