Job request: 1616

Organisation:
Workspace:: online_consultation
ID:: uxodj6t5i65dqsgf

This page shows the technical details of what happened when the authorised researcher Martina Fonseca 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:

run_model

Status:

Status: Succeeded

Job identifier:

az42xsanmer4liry

Pipeline

Show project.yaml

version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_cohorts_main:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ori
    outputs:
      highly_sensitive:
        cohort: output/input_ori.csv

  run_model:
    run: r:latest analysis/01-createSDtables.R
    needs: [generate_cohorts_main]
    outputs:
      moderately_sensitive:
        log: logs/log-01-createSDtables.txt
        #gtpng1: output/tables/gt_ocpop.png
        #gtpng2: output/tables/gt_gpcpop.png
        #rdata1: output/tables/gt_ocpop.RData
        #rdata2: output/tables/gt_gpcpop.RData        
        #rdata1_discl: output/tables/gt_ocpop_unformatted.csv
        #rdata2_discl: output/tables/gt_gpcpop_unformatted.csv
        #tb01: output/tables/tb01_gpcr_region.csv
        #tb02: output/tables/tb02_gpcr_stp.csv # guidance says to not output identifiable regions
        tb04: output/tables/tb04_gpcr_agesex.csv
        #tb05: output/tables/tb05_gpcr_ethnicity.csv
        #tb06: output/tables/tb06_gpcr_ruc.csv
        #tb07: output/tables/tb07_gpcr_care.csv
        #tb08: output/tables/tb08_gpcr_dis.csv
        #tb09: output/tables/tb09_gpcr_imd.csv

  # https://docs.opensafely.org/en/latest/measures/
  generate_cohorts_long:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_measures_bycode --index-date-range "2019-01-01 to 2020-12-01 by month" --output-dir=output/measures
    outputs:
      highly_sensitive:
        cohort: output/measures/input_measures_bycode_*.csv

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition_measures_bycode --output-dir=output/measures
    needs: [generate_cohorts_long]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measure_*.csv

  run_model_long:
    run: r:latest analysis/03-createnattrends_codes.R
    needs: [generate_cohorts_long]
    outputs:
      moderately_sensitive:
        log: logs/log-03-createnattrends.txt
        tb01: output/tables/sc03_tb01_nattrends.csv
        fig01: output/plots/sc03_fig01_nattrends.svg
        fig02: output/plots/sc03_fig02_nattrends.svg
        fig03: output/plots/sc03_fig03_pracnatcoverage.svg
        fig04: output/plots/sc03_fig04_pracbyregcoverage.svg
        fig07: output/plots/sc03_fig07_ctv3nattrends.svg
        fig08: output/plots/sc03_fig08_ctv3nattrends.svg
        fig05: output/plots/sc03_fig05_ctv3pracnatcoverage.svg
        fig06: output/plots/sc03_fig06_ctv3pracbyregcoverage.svg

  run_model_measures:
    run: r:latest analysis/02-createtemporal.R
    needs: [generate_cohorts_long,generate_measures]
    outputs:
      moderately_sensitive:
        log: logs/log-02-createtemporal.txt
        red_measures: output/tables/redacted_*.csv
        #tb01: output/measures_gpc_pop.csv # redundant into. omit output
        fig01: output/plots/plot_overall_gpc_pop.svg
        #figall: output/plots/plot_each_*_practice.svg
        figquant: output/plots/plot_quantiles_*_practice.svg
        figlogquant: output/plots/plot_logquantiles_*_practice.svg

 

#  run_model_measuresDEBUG:
#    run: r:latest analysis/02-createtemporal_debug.R
#    needs: [generate_cohorts_long,generate_measures]
#    outputs:
#      moderately_sensitive:
#        log: logs/log-02-createtemporal-debug.txt
#        #tb01: output/measures_gpc_pop_debug.csv
#        #fig01: output/plots/plot_overall_gpc_pop_debug.svg
#        #figall: output/plots/plot_each_debug_*_practice.svg
#        #figquant: output/plots/plot_quantiles_debug_*_practice.svg
#        #figquant2: output/plots/plot_quantiles2_debug_*_practice.svg

  #run_model_redactedmeasures:
  #  run: r:latest analysis/02a-createredactedmeasure.R
  #  needs: [generate_cohorts_long,generate_measures]
  #  outputs:
  #    moderately_sensitive:
  #      log: logs/log-02a-createredactedmeasure.txt
  #      red_measures: output/tables/redacted2a_*.csv

### SNOMED check
  generate_cohorts_checksnomed:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_checksnomed
    outputs:
      highly_sensitive:
        cohort: output/input_checksnomed.csv


  run_model_checksnomed:
    run: r:latest analysis/0a-snomedcheck.R
    needs: [generate_cohorts_checksnomed]
    outputs:
      moderately_sensitive:
        log: logs/log-0a-snomedcheck.txt
        tab1: output/tables/sc0a_snomedcheck_tallies.csv

### SRO template pipeline
  SROtem_generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2020-12-01 by month" --output-dir=output
    outputs:
      highly_sensitive:
        cohort: output/input_*.csv

  SROtem_generate_study_population_practice_count:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output
    outputs:
      highly_sensitive:
        cohort: output/input_practice_count.csv

  
  SROtem_generate_measures:
      run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
      needs: [SROtem_generate_study_population]
      outputs:
        moderately_sensitive:
          measure_csv: output/measure_*.csv

  SROtem_get_patient_count:
    run: python:latest python analysis/SROtem_get_patients_counts.py
    needs: [SROtem_generate_study_population]
    outputs:
      moderately_sensitive:
        text: output/patient_count.json


  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/notebooks/SRO-Notebook.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [SROtem_generate_measures, SROtem_generate_study_population_practice_count]
    outputs:
      moderately_sensitive:
        notebook: output/SRO-Notebook.html

Timeline

Created: 3 years, 7 months ago 13 Apr 2021 18:15:50 UTC
Started: 3 years, 7 months ago 13 Apr 2021 18:16:38 UTC
Finished: 3 years, 7 months ago 13 Apr 2021 18:19:06 UTC
Runtime: 00:02:28

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

Job information

Status: Succeeded
Backend: TPP
Workspace: online_consultation
Requested by: Martina Fonseca
Branch: master
Force run dependencies: No
Git commit hash: ce8676d
Requested actions: run_model

Code comparison

Compare the code used in this Job Request