Tag: Healthcare
All the articles with the tag "Healthcare".
-
Building a data quality dashboard on top of Tuva's DQI mart
Tuva's DQI mart produces fill rates and anomaly flags for every input field in a claims dataset. Here's how to surface that in a Streamlit dashboard with meaningful visualizations.
-
Feature engineering from claims data for a Random Forest classifier
Healthcare claims have dozens of potential features for patient risk models. Here's how to select and validate features from a Tuva Project dataset for a Random Forest classifier predicting HCC gaps.
-
From raw claims to RAF: what the data pipeline actually looks like
The path from a raw Medicare claim file to a patient's Risk Adjustment Factor score involves five distinct transformation layers. This is what each layer does and where the dbt models fit in.
-
HCC suspecting explained from a data engineering perspective
HCC suspecting is about identifying conditions documented in prior years that haven't appeared in claims yet this year. This is what the data pipeline looks like and what the Tuva mart actually produces.
-
Predicting patient risk with scikit-learn on top of HCC suspecting data
A Random Forest classifier on Tuva's hcc_suspecting__summary table, using age, sex, paid amount, and condition count to predict which patients have above-median HCC gaps.
-
Running the Tuva Project on DuckDB — what breaks and how to fix it
Tuva 0.17.2 on DuckDB 1.10 with dbt 1.11 produces three distinct failure modes. This is what actually broke and how each one was fixed.
-
What 167k synthetic Medicare claims taught me about US healthcare data
Running the Tuva Project on 167k synthetic Medicare claims reveals the structural complexity of US healthcare data — before you've dealt with a single real data quality issue.
-
What is the Tuva Project and why should data engineers care
The Tuva Project is an open-source dbt package that transforms raw healthcare claims into analytics-ready mart tables covering HEDIS, HCC, CCSR, readmissions, and data quality. This is what it actually does and why it matters.