Automate the Validation of APCD Data Quality for Payer Submissions

Payers submissions supported

35+

Years of product
deployment & support

09+

Rules deployed per state

150+

States specific APCD
prebuilt rulesets deployed

18

Testing Time
Saved by

55%

Improved Functional
Testing Time by

25%

Saved QA
Cost by

30%

Overall Improvement
of TCO by

20%

APCD Compliance Solutions

Empowering Health Insurance &
State APCDs to Achieve Data Quality

Complies with No Surprises Act APCD

Ensures 100% Data Validation

Low-code easy rule sets

Plug & Play for existing Data Pipelines

High Data Quality across Multiple Dimensions

Error-free Predefined Templates with State-specific Rules

Find and Fix Anomalies and Improve Your APCDs Payer Submissions

  • Pharmacy Claim
  • Data Dental Claim
  • Data Medical Claims
  • Provider Data
  • Data Threshold
  • Compliance Check
  • Member Eligibility Data
  • Data Value Check
  • Data Type Check
  • Data Length Check
  • Member ID Consistency Check

How Datagaps Facilitates Validation of All-Payers Claims Databases?

The payers must submit monthly CSV files for each state about claims and insurance datasets. The files must pass multiple data quality checks for various dimensions and thresholds set by each state. Rejected submissions lead to significant setbacks in terms of timelines, reputation, and potential legal fees. Therefore, a system that is easy to deploy and maintain for multiple states isolates inaccuracies for reconciliation and handles sensitive data within their environment is needed.

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Failure to Submit APCD Data in Compliance with Protocol
can lead to Significant Financial Penalties.

Non-compliance with reporting requirements may result in a $250/day fine, up to a maximum of $25,000 per incident. Each instance of non-compliance is considered a separate occurrence. A single compliance failure can cause huge fines, with yearly caps ranging from 2.5M$ to 10M$.

— Washinton Legistature Documenation

Data Quality

Automate testing of Business Intelligence applications by making use of the metadata available from the BI tools such as Tableau, OBIEE, and Business Objects.

Synthetic Data

Automate testing of Business Intelligence applications by making use of the metadata available from the BI tools such as Tableau, OBIEE, and Business Objects.

ETL Testing

Automate testing of Business Intelligence applications by making use of the metadata available from the BI tools such as Tableau, OBIEE, and Business Objects.

BI Validation

Automate testing of Business Intelligence applications by making use of the metadata available from the BI tools such as Tableau, OBIEE, and Business Objects.
Products

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DataOps Suite

End-to-End Data Testing Automation

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ETL Validator

Automate your Data Reconciliation & ETL/ELT testing

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BI Validator

Automate functional regression & performance testing of BI reports

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DQ Monitor

Monitor quality of data being Ingested or at rest using DQ rules & AI

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Test Data Manager

Maintain data privacy by generating realistic synthetic data using AI

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