Flat Data for Clinical Workflows

This page provides guidance on how to make sense of the Particle Flat output, how to link the different data models together, and provides examples of how to filter the data down to exactly what you need for your clinical workflow.

What does the Flat Output Look Like?

The Flat output is a flat structure that is much easier to ingest and persist as compared to FHIR R4. The output of the Flat API is formatted in JSON and will consist of the datasets that you specify in the parameters of the GET /flat/{id}/collect-data[parameters] request. Each dataset will consist of a list of dataset entries. Below is an example of the Labs and Encounters datasets in a Flat output. Each Lab entry or Encounter entry will have all of the fields shown in the dataset schema in the section above.

{
    "LABS": [
        {
            "field_1": "value_1",
            "field_2": "value_2",
            "field_n": "value_n"
        },
        {
            "field_1": "value_1",
            "field_2": "value_2",
            "field_n": "value_n"
        }
    ],
    "ENCOUNTERS": [
        {
            "field_1": "value_1",
            "field_2": "value_2",
            "field_n": "value_n"
        },
        {
            "field_1": "value_1",
            "field_2": "value_2",
            "field_n": "value_n"
        }
    ]
}

Supported Flat Data Sets

Below are a list of all data sets supported in Flat

How to Link the Data Models

To gain additional clinical context with the Flat datasets, each dataset contains a primary key(s) and/or foreign key(s) that allow you to link the various tables together. For example, if you were interested in which encounter a diagnosis was made, you can link the Problem entry to an Encounter entry. To do this, link the Problem.EncounterID to the Encounter.EncounterID.

For additional information on which keys are compatible, we have included an entity relationship diagram here: