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License: MIT DOI

TODO add paper citation

General

This repository contains code to:

  1. Recreate the H2O insights centre statistics based on querying directly the databases
  2. Create visualizations for the PROMIS GLOBAL 10 questionnaire, which the H2O patients have answered doing recruitment and in subsequent times.

Available data

  • The H2O patients have been recruited to the project for one of the four conditions - Diabetes Melitus, Inflamatory Bowel Disease, Breast Cancer, Lung Cancer.
  • The code is intented to run against data from three hospitals available - Erasmus Medical Centre Rotterdam, Medical University of Vienna, Vall d'Hebron University Hospital Barcelona.
  • All data used are mapped to an OMOP CDM database.

Custom observations

There are differences in how the patients are recruited for each disease in the hospitals above and for the analysis we aim to perform here we decided to create an additional observation, with a custom codes to represent the primary disease. The observation_concept_id would still consist of a standard concept 44807982, Participant in research study and the custom concept will represent the value_as_concept_id.

Adding the custom concepts in the vocabulary tables and the observation table as seen below.

Custom Vocabulary

Field Value
vocabulary_id H2O
vocabulary_name H2O recruitment disease
vocabulary_version 2025-12-10
vocabulary_concept_id 0

Custom concepts

Field Concept 1 Concept 2 Concept 3 Concept 4
concept_id 2010000001 2010000002 2010000003 2010000004
concept_name H2O Diabetes H2O Inflammatory Bowel Disease H2O Breast Cancer H2O Lung Cancer
domain_id Observation Observation Observation Observation
vocabulary_id H2O H2O H2O H2O
concept_class_id Undefined Undefined Undefined Undefined
standard_concept NULL NULL NULL NULL
concept_code 0 0 0 0
valid_start_date 2020-10-01 2020-10-01 2020-10-01 2020-10-01
valid_end_date 2099-12-31 2099-12-31 2099-12-31 2099-12-31
invalid_reason NULL NULL NULL NULL

Observation record

Field Value Comment
observation_id auto increment
person_id
observation_concept_id 44807982 Participant in research study
observation_date 2020-10-01 Start of H2O project
value_as_concept_id custom_concept_id
value_source_value custom_concept_name
observation_type_concept_id 32862 Patient filled survey

Sample insert code

Sample code to insert the new records in the Observation table for postgresql can be found in extra/insert_custom.sql

How to use

Single database

All the scripts that need to run to gather the nessasery counts and create the visualizations can be found in code_to_run.R.

Multiple databases

In case the data are split by disease in different databases (case in one of the sites) the code will run in each database and combine the results into one afterwards. This can be done with the code_to_run_multiple_dbs.R.

Combine results

If all results are available in one place they can be combined so the plots can represent the same result for each site. In that case at the end of code_to_run.R there is an additional option to run script visualizations_insights_centre_all.R and visualizations_promis10_all.R for the visualizations.

Plots

Insights centre

  • Person counts stratified by Age and by Gender
  • Disease counts
  • Diabetes therapy counts
  • Diabetes diagnostics
    • Hb1Ac measurement over time. Not yet availale in the insights centre but interesting to add.

PROMIS GLOBAL 10

  • Number of times a questionnaire was answered per question group (general health, quality of life, physical health and mental health)
  • T-scores according to PROMIS Global Health Scoring Manual for physical and mental health
  • Mean and standard error for each answer time for the PROMIS global 10 General Health group
  • Transitions between responses for the PROMIS global 10 General Health group