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QUICKSTART.md

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🏁 Quickstart

There are 3 main ways to use the Tuva Project in your healthcare data warehouse.

  • All Data Marts
  • Single Data Mart
  • Terminology Only

Installing the dbt package

Pre-requisite: In order to run the Tuva Project you need dbt installed and healthcare data loaded inside a data warehouse that we support. See the README for details.

  1. Add the Tuva Project to your packages.yml, or create a packages.yml if you do not already have one. This should be created in the root of your dbt project. 
    packages:
  - package: tuva-health/the_tuva_project
    version: [">=0.5.0","<1.0.0"]
  2. Import the package. 
    dbt deps

All Data Marts

The main difference between running a single data mart and all data marts is the mapping. To run all data marts you need to map to the entire Claims Data Model. Stay tuned for details on the Clinical Data Model.

The process of mapping an entire data model can be tricky. If you need help mapping your data, feel free to post in #buildersask on Slack.

  1. Map to the input layer: Map your data to the Claims Data Model. The package expects you to have the following models in your dbt project: eligibility, medical_claim, and pharmacy_claim. These will be referenced by the Core staging layer to run the Tuva Project.
  2. Set the variables: You need to enable all models related to the type of healthcare data being used. Do this by adding the data source type variable to your dbt_project.yml file and set the value to "true". Example: 
      vars:
    claims_enabled: true
  3. Run the package to create all the models. 
    dbt build --select the_tuva_project

Other Variables

The Tuva Project relies on variables to set default behavior for the data marts. These defaults can be found in the package's dbt_project.yml. You can change these values here or set them in the dbt_project.yml of your project.

  • tuva_last_run: The date and timestamp of the dbt run that will populate the tuva_last_run column in all models. Default timezone is UTC.
  • cms_hcc_payment_year: The payment year for the CMS HCC mart. Defaults to the current year.
  • cms_hcc_model_version: The risk model used for the CMS HCC mart.
  • quality_measures_period_end: The reporting date used to calculate the performance periods for Quality Measures. Defaults to the current date.
  • snapshots_enabled: Some data marts use the dbt snapshot feature. These are disabled by default. To enable them add this variable and set the value to true (snapshots_enabled: true).

Alternatively, you can set these in the CLI. Example:

dbt build --select the_tuva_project --vars '{cms_hcc_payment_year: 2020}'

Connectors

If your data source is a standard format that we have a connector for, you can use a connector to map your data. A connector is just a dbt package that maps a standard data format to the Claims Data Model. We currently have connectors for the following standard data formats:

Single Data Mart

Every data mart in the Tuva Project can be run individually. To run a single data mart complete the following steps.

  1. Map to staging: Each data mart has its own staging layer. The staging layer is the set of models you need to create in order to run the data mart. You can find this in the staging folder under the data mart.
  2. Set the variables: You need to enable the data mart you want to run. Do this by adding the variable for that data mart to your dbt_project.yml file and set the value to "true". Example: 
      vars:
    cms_chronic_conditions_enabled: true
  3. Run the package to build the marts you enabled. 
    dbt build --select the_tuva_project

See integration_tests for more data mart variable examples.

Terminology Only

You can disable the data marts and just load the terminology seeds by completing the following steps.

  1. Add the variable tuva_marts_enabled to your dbt_project.yml file and set the value to "false". 
       vars:
     tuva_marts_enabled: false
  2. Run the package to build the seeds. 
     dbt seed

Alternatively, you can load all the terminology sets via SQL directly to your database. Check out the SQL for doing this here.

Tutorial

We created this demo project to make it easy for people to explore the Tuva Project, even if you don't have access to healthcare data.

The demo includes:

  • A 1,000 patient synthetic claims dataset based on Medicare claims data.
  • All the data marts in the Tuva project.
  • All the terminology sets in the Tuva Project.