Job request: 2626

Organisation:
Workspace:: online_consultation
ID:: ujqdn47sc4j5r2ay

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_v2

Status:

Status: Succeeded

Job identifier:

odpypdfkcrhsatjn

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
        #rdata1_unlist: output/tables/gt_ocpop_unlisted.csv
        #rdata2_unlist: output/tables/gt_gpcpop_unlisted.csv
        tb04: output/tables/tb04_gpcr_agesex.csv
        gtpng1: output/tables/gt_ocpop.html
        gtpng2: output/tables/gt_gpcpop.html
        #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
        #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

### Weekly tallies to compare with OC/VC supplier data
  generate_cohorts_weekly2021:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_measures_weekly --index-date-range "2020-01-06 to 2021-03-22 by week" --output-dir=output/measures-week
    outputs:
      highly_sensitive:
        cohort: output/measures-week/input_measures_weekly_*.csv

  generate_measures_weekly2021:
    run: cohortextractor:latest generate_measures --study-definition study_definition_measures_weekly --output-dir=output/measures-week
    needs: [generate_cohorts_weekly2021]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures-week/measure_*.csv

  run_model_weekly2021:
    run: r:latest analysis/04-weekly2021.R
    needs: [generate_cohorts_weekly2021,generate_measures_weekly2021]
    outputs:
      moderately_sensitive:
        log: logs/log-04-weekly2021.txt
        tab1: output/tables/sc04-weeklynattrend.csv

#### Clinical history
  generate_cohorts_v2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_v2
    outputs:
      highly_sensitive:
        cohort: output/input_v2.csv

  run_model_v2:
    run: r:latest analysis/05-createClinicalConditiontables.R
    needs: [generate_cohorts_v2]
    outputs:
      moderately_sensitive:
        log: logs/log-05-createClinicalConditiontables.txt
        gthtml1: output/tables/gt_econsult_pop_pre.html
        gthtml2: output/tables/gt_econsult_pop_post.html
        gthtml3: output/tables/gt_econsult_consultpop_pre.html
        gthtml4: output/tables/gt_econsult_consultpop_post.html
        gtglm1: output/tables/pracglm_submission.html
        gtglm4: output/tables/pracglm_submission_rob_logit.html
        gtglm2: output/tables/pracglm_submission_rob.csv
        gtglm3: output/tables/pracglm_submission_rob.html

# ### 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, 4 months ago 25 Jun 2021 07:57:19 UTC
Started: 3 years, 4 months ago 25 Jun 2021 07:58:11 UTC
Finished: 3 years, 4 months ago 26 Jun 2021 04:28:38 UTC
Runtime: 20:30:27

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: 0d347dd
Requested actions: run_model_v2

Code comparison

Compare the code used in this Job Request