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Job request: 15276

Organisation:
Bennett Institute
Workspace:
winter-pressures
ID:
rnj6ajt5imq4kvf5
View repo View project.yaml

This page shows the technical details of what happened when authorised researcher Lisa Hopcroft requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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

Pipeline

Show project.yaml 
version: "3.0"

expectations:
  population_size: 5000

actions:
  # Other data
  # ----------
  # Add actions for other data to this section. Prefix them with a suitable name; place
  # scripts in a similarly named sub-directory of the analysis directory; write outputs
  # to a similarly named sub-directory of the output directory.
  #
  # For example, let's call our other data "metrics". We would prefix our actions
  # "metrics_"; we would place our scripts in analysis/metrics; we would write outputs
  # to output/metrics.

  # Metrics data
  # ------------
  metrics_generate_study_dataset_winter:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
      --index-date-range '2021-12-01 to 2022-03-30 by month' --output-dir=output/metrics
      --output-format=feather
    outputs:
      highly_sensitive:
        extract: output/metrics/input_*.feather

  metrics_generate_study_dataset_summer:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
      --index-date-range '2021-06-01 to 2021-09-30 by month' --output-dir=output/metrics
      --output-format=feather
    outputs:
      highly_sensitive:
        extract: output/metrics/input*.feather

  metrics_generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition
      --output-dir=output/metrics
    needs:
    - metrics_generate_study_dataset_summer
    - metrics_generate_study_dataset_winter
    outputs:
      highly_sensitive:
        measure_csv: output/metrics/measure_*_rate.csv

  metrics_generate_single_metric:
    run: r:latest analysis/metrics/single_metric.R
    needs:
    - metrics_generate_measures
    outputs:
      moderately_sensitive:
        png1: output/metrics/summer_winter_difference_histogram.png
        png2: output/metrics/summer_winter_ratio_histogram.png
        csv1: output/metrics/summer_winter_difference_histogram_data.csv
        csv2: output/metrics/summer_winter_ratio_histogram_data.csv


  # Appointments data
  # -----------------
  appointments_generate_dataset_sql:
    run: >
      sqlrunner:latest
        analysis/appointments/dataset_query.sql
        --output output/appointments/dataset_long.csv.gz
        --dummy-data-file analysis/appointments/dummy_dataset_long.csv.gz
    outputs:
      highly_sensitive:
        dataset: output/appointments/dataset_long.csv.gz

  # appointments_generate_dataset:
  #   run: >
  #     databuilder:v0
  #       generate-dataset
  #       analysis/appointments/dataset_definition.py
  #       --output output/appointments/dataset_wide.arrow
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/appointments/dataset_wide.arrow

  # appointments_get_freq_na_values:
  #   run: >
  #     python:latest
  #       python
  #       -m analysis.appointments.get_freq_na_values
  #   needs: [appointments_generate_dataset]
  #   outputs:
  #     moderately_sensitive:
  #       dataset: output/appointments/freq_na_values.csv

  # appointments_reshape_dataset:
  #   run: >
  #     python:latest
  #       python
  #       -m analysis.appointments.reshape_dataset
  #   needs: [appointments_generate_dataset]
  #   outputs:
  #     highly_sensitive:
  #       dataset: output/appointments/dataset_long.arrow

  appointments_generate_lead_time_measure_by_booked_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_median_lead_time_measure
        --value-col lead_time_in_days
        --index-cols booked_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_median_lead_time_in_days_by_booked_month.csv

  appointments_generate_lead_time_measure_by_start_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_median_lead_time_measure
        --value-col lead_time_in_days
        --index-cols start_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_median_lead_time_in_days_by_start_month.csv

  appointments_generate_num_appointments_measure_by_start_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_num_appointments_measure
        --index-cols start_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_num_appointments_by_start_month.csv

  appointments_generate_num_appointments_measure_by_booked_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_num_appointments_measure
        --index-cols booked_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_num_appointments_by_booked_month.csv

  appointments_generate_num_unique_patients_measure_by_booked_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_num_unique_patients_measure
        --unique-col patient_id
        --index-cols booked_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_num_unique_patients_by_booked_month.csv

  appointments_generate_num_unique_patients_measure_by_start_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_num_unique_patients_measure
        --unique-col patient_id
        --index-cols start_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_num_unique_patients_by_start_month.csv

  appointments_generate_proportion_same_day_lead_time_measure_by_booked_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_proportion_lead_time_measure
        --value-col lead_time_in_days
        --value-threshold 0
        --index-cols booked_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_proportion_lead_time_in_days_within_0days_by_booked_month.csv

  appointments_generate_proportion_same_day_lead_time_measure_by_start_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_proportion_lead_time_measure
        --value-col lead_time_in_days
        --value-threshold 0
        --index-cols start_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_proportion_lead_time_in_days_within_0days_by_start_month.csv


  appointments_generate_proportion_two_day_lead_time_measure_by_booked_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_proportion_lead_time_measure
        --value-col lead_time_in_days
        --value-threshold 2
        --index-cols booked_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_proportion_lead_time_in_days_within_2days_by_booked_month.csv

  appointments_generate_proportion_two_day_lead_time_measure_by_start_month:
    run: >
      python:latest
        python
        -m analysis.appointments.generate_proportion_lead_time_measure
        --value-col lead_time_in_days
        --value-threshold 2
        --index-cols start_month practice
    needs: [appointments_generate_dataset_sql]
    outputs:
      moderately_sensitive:
        measure: output/appointments/measure_proportion_lead_time_in_days_within_2days_by_start_month.csv


  appointments_generate_deciles_charts:
    run: >
      deciles-charts:v0.0.33
        --input-files output/appointments/measure_*.csv
        --output-dir output/appointments
    config:
      show_outer_percentiles: true
    needs:
      - appointments_generate_lead_time_measure_by_booked_month
      - appointments_generate_lead_time_measure_by_start_month
      - appointments_generate_num_appointments_measure_by_start_month
      - appointments_generate_num_appointments_measure_by_booked_month
      - appointments_generate_num_unique_patients_measure_by_start_month
      - appointments_generate_num_unique_patients_measure_by_booked_month
      - appointments_generate_proportion_two_day_lead_time_measure_by_start_month
      - appointments_generate_proportion_two_day_lead_time_measure_by_booked_month
      - appointments_generate_proportion_same_day_lead_time_measure_by_start_month
      - appointments_generate_proportion_same_day_lead_time_measure_by_booked_month
    outputs:
      moderately_sensitive:
        deciles_charts: output/appointments/deciles_chart_*.png
        deciles_tables: output/appointments/deciles_table_*.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 03:14:14

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

Job information

Status
Succeeded
Backend
TPP
Workspace
winter-pressures
Requested by
Lisa Hopcroft
Branch
main
Force run dependencies
No
Git commit hash
5781a47
Requested actions
  • appointments_generate_num_appointments_measure_by_start_month
  • appointments_generate_num_appointments_measure_by_booked_month
  • appointments_generate_num_unique_patients_measure_by_booked_month
  • appointments_generate_num_unique_patients_measure_by_start_month
  • appointments_generate_proportion_same_day_lead_time_measure_by_booked_month
  • appointments_generate_proportion_same_day_lead_time_measure_by_start_month
  • appointments_generate_proportion_two_day_lead_time_measure_by_booked_month
  • appointments_generate_proportion_two_day_lead_time_measure_by_start_month
  • appointments_generate_deciles_charts

Code comparison

Compare the code used in this Job Request