Check out our docs to learn about the project and how you can use it.
The Medicare CCLF Connector is a dbt project that maps raw Medicare CCLF claims data to the Tuva Input Layer, which is the first step in running the Tuva Project. This connector expects your CCLF data to be organized into the tables outlined in this CMS data dictionary, which is the most recent format CMS uses to distribute CCLF files.
- BigQuery
- Redshift
- Snowflake
Unlike the Tuva Project, this repo is a dbt project, not a dbt package. Clone or fork this repository to your local machine.
Next you need to import the Tuva Project dbt package into the Medicare CCLF Connector dbt project. For example, using dbt CLI you would cd into the directly where you cloned this project to and run dbt deps to import the latest version of the Tuva Project.
The CCLF file specification does not have a field that can be mapped directly to enrollment_start_date; therefore, we have added a field called bene_member_month. We recommend parsing the monthly enrollment file date from the Beneficiary Demographics filename (e.g., P.A****.ACO.ZC8Y**.Dyymmdd.Thhmmsst) and mapping this date to bene_member_month. The connector will handle the rest of the mapping.
Next you need to tell dbt where your Medicare CCLF source data is located. Do this using the variables input_database and input_schema in the dbt_project.yml file. You also need to configure your profile in the dbt_project.yml.
Now you're ready to run the connector and the Tuva Project. For example, using dbt CLI you would cd to the project root folder in the command line and execute dbt build. Next you're now ready to do claims data analytics!
Have an opinion on the mappings? Notice any bugs when installing and running the project?
If so, we highly encourage and welcome feedback! While we work on a formal process in Github, we can be easily reached on our Slack community.
Join our growing community of healthcare data practitioners on Slack!