Creating a Patient Group

Introduction

Creating a Patient Group

To create a patient group (or subset), go to the Patient Groups page. For this, you need to have loaded a project. Then click on the “Patient Groups” icon from the menu at the top of the page, to the right of the loaded project name.

You’ll arrive at the project’s patient groups page.

A patient group is a subset of a dataset, but it depends on a project. If two projects use the same dataset, they won’t share the same datasets.

An “All patients” group is created by default when creating a project.

To create a patient group, click on the “+” icon on the left side of the screen.

Choose a name, then click “Add”. For this example, we’ll create a group containing patients over 50 years old.

Click on the group you just created: you’ll arrive at the selected group’s page.

On the right side of the screen, you have two tabs:

• Summary: presents the patient group information, which can be modified (particularly the description)
• Code: this tab allows you to modify the code and add or remove patients from a group, which we’ll see in the following paragraphs

Adding Patients to a Group

To add patients to a subset, we use the add_patients_to_subset function.

This function takes these two arguments:

• patients: a numeric vector containing the IDs of patients to add
• subset_id: the ID of the group to which patients will be added (by default the ID of the selected group, modifying this argument is useful in plugins particularly)

When creating a patient group, the code allowing to add all patients to the group is created.

This code will be executed if the user presses the button to execute the code, or if the group is selected from the project (and if it doesn’t already contain patients).

We’ll modify this code to add patients over 50 years old.

Let’s use the code to create a column containing patient ages, from the tutorial on usual OMOP queries.

d$visit_occurrence %>%
    dplyr::left_join(
        d$person %>% dplyr::select(person_id, birth_datetime),
        by = "person_id"
    ) %>%
    dplyr::collect() %>%
    dplyr::mutate(
        age = round(as.numeric(difftime(visit_start_datetime, birth_datetime, units = "days")) / 365.25, 1)
    )

The code editor of the selected group allows testing the code. We’ll extract the IDs of patients with an age greater than 50 years. For now, we’ll comment out the add_patients_to_subset function.

d$visit_occurrence %>%
    dplyr::left_join(
        d$person %>% dplyr::select(person_id, birth_datetime),
        by = "person_id"
    ) %>%
    dplyr::collect() %>%
    dplyr::mutate(
        age = round(as.numeric(difftime(visit_start_datetime, birth_datetime, units = "days")) / 365.25, 1)
    ) %>%
    dplyr::filter(age > 50) %>%
    dplyr::distinct(person_id) %>%
    dplyr::pull()

Our code works, so we can store these IDs in a variable and then integrate it into the add_patients_to_subset function.

patients <-
    d$visit_occurrence %>%
    dplyr::left_join(
        d$person %>% dplyr::select(person_id, birth_datetime),
        by = "person_id"
    ) %>%
    dplyr::collect() %>%
    dplyr::mutate(
        age = round(as.numeric(difftime(visit_start_datetime, birth_datetime, units = "days")) / 365.25, 1)
    ) %>%
    dplyr::filter(age > 50) %>%
    dplyr::distinct(person_id) %>%
    dplyr::pull()

add_patients_to_subset(patients = patients)

A message indicates that the patients have been successfully added to the group.

Note that here we added patients to the group, but it’s also possible to filter:

• On the hospitalization stay, by adding the visit_occurrence column to the patients variable
• On stays in departments, by adding the visit_detail column to the patients variable

Removing Patients from a Group

To remove patients from a group, you need to use the remove_patients_from_subset function, which works like add_patients_to_subset, with the same arguments: patients and subset_id.

We could, for example, after adding all patients to the group, remove those with an age less than or equal to 50 years.

Integration in Plugins

It would be interesting to create an Individual Data plugin allowing patient exclusion with one or more exclusion criteria, created by the user.

We could imagine that this plugin removes patients from the “Included patients” group, and adds them to the “Excluded patients” group.

To do this, it would be enough to use the functions add_patients_to_subset and remove_patients_from_subset from the plugin.

How to retrieve the ID of patient groups? Thanks to the m$subsets variable.

All that’s left is to create the plugin!

Conclusion