Job request: 2932
- Organisation:
- Workspace:
- antipsychotics-prescribing-during-covid-19-master
- ID:
- gtdmqdokvzpeu2ln
This page shows the technical details of what happened when the authorised researcher Millie Green 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
-
- Job identifier:
-
qjnv5vfouaanly7o
Pipeline
Show project.yaml
######################################
# This script defines the project pipeline - it specifys the execution orders for all the code in this
# repo using a series of actions.
######################################
version: '3.0'
expectations:
population_size: 100000
actions:
# Extract data ----
## study population flow chart
generate_study_population_flow_chart_data:
run: cohortextractor:latest generate_cohort --study-definition study_definition_flow_chart --index-date-range "2019-01-01 to 2021-04-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/input_flow_chart_*.feather
## Cohort data
generate_cohort_1:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2019-06-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/input_*.feather
generate_cohort_2:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-07-01 to 2019-12-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/input*.feather
generate_cohort_3:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01 to 2020-06-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/inpu*.feather
generate_cohort_4:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-07-01 to 2020-12-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/inp*.feather
generate_cohort_5:
run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-01-01 to 2021-04-01 by month" --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/in*.feather
## Ethnicity
extract_ethnicity:
run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output/data --output-format=feather
outputs:
highly_sensitive:
cohort: output/data/input_ethnicity.feather
# ## Patient to practice lookup
# patient_practice_lookup:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_practice_count --output-dir=output/data --output-format=feather
# outputs:
# highly_sensitive:
# cohort: output/data/input_practice_count.feather
# Data processing ----
# ## Patient counts
# get_patient_count:
# run: python:latest python analysis/get_patient_counts.py --output-dir=output/data
# needs: [extract_data]
# outputs:
# moderately_sensitive:
# text: output/data/patient_count.json
# ## Practice count
# get_practice_count:
# run: python:latest python analysis/get_practice_count.py --output-dir=output/data
# needs: [patient_practice_lookup]
# outputs:
# moderately_sensitive:
# text: output/data/practice_count.json
## Add ethnicity
join_ethnicity:
run: python:latest python analysis/join_ethnicity.py
needs: [generate_cohort_1, generate_cohort_2, generate_cohort_3, generate_cohort_4, generate_cohort_5, extract_ethnicity]
outputs:
highly_sensitive:
cohort: output/data/i*.feather
## Process data
data_process:
run: r:latest analysis/process_data.R
needs: [generate_study_population_flow_chart_data, join_ethnicity]
outputs:
moderately_sensitive:
data: output/data/data_*.rds
# tables: output/data/custom_measures_*.csv
# ## Generate measures
# generate_measures:
# run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output/data
# needs: [join_ethnicity]
# outputs:
# moderately_sensitive:
# measure_csv: output/data/measure_*.csv
# ### Generate measures, by group
# generate_measures_demographics:
# run: python:latest python analysis/calculate_measures.py
# needs: [join_ethnicity]
# outputs:
# moderately_sensitive:
# measure: output/combined_measure_*.csv
#
# ### Generate measures, by group and demographic
# generate_measures_demographics:
# run: python:latest python analysis/calculate_measures.py
# needs: [join_ethnicity]
# outputs:
# moderately_sensitive:
# measure: output/combined_measure_*.csv
# Results ----
## Calculate numbers for study population flow chart
flow_chart:
run: r:latest -e 'rmarkdown::render("analysis/study_definition_flow_chart.rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
needs: [data_process]
outputs:
moderately_sensitive:
html: output/study_definition_flow_chart.html
## Figures
summary_figures:
run: r:latest analysis/summary_plots.R
needs: [data_process]
outputs:
moderately_sensitive:
plots: output/figures/plot_*.svg
summary_figures_redacted:
run: r:latest analysis/summary_plots_redacted.R
needs: [data_process]
outputs:
moderately_sensitive:
plots: output/figures/plot*.svg
## Table 1
table_1:
run: r:latest analysis/table_1.R
needs: [join_ethnicity]
outputs:
moderately_sensitive:
plots: output/tables/table1.html
# ## Whole population notebook
# generate_notebook:
# run: jupyter:latest jupyter nbconvert /workspace/notebooks/antipsychotic_measures.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
# needs: [generate_measures, get_practice_count, get_patient_count]
# outputs:
# moderately_sensitive:
# notebook: output/antipsychotic_measures.html
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 07:07:18
These timestamps are generated and stored using the UTC timezone on the EMIS backend.
Job information
- Status
-
Succeeded
- Backend
- EMIS
- Requested by
- Millie Green
- Branch
- master
- Force run dependencies
- No
- Git commit hash
- 80fa5e3
- Requested actions
-
-
generate_cohort_4
-
Code comparison
Compare the code used in this Job Request