Improving Data Operations Efficiency through GenAI-Powered Process Automation

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The Situation

Pharmaceutical companies are mandated to cease all forms of engagement with debarred healthcare professionals (HCPs) in the U.S. Compliance entails identifying and flagging HCPs from lists periodically released by government agencies. These agencies also issue exclusion notices that call out HCPs who
might be confused with debarred HCPs due to similar names and/or other identifying information.

A top 10 pharma company was looking to improve debarred HCP identification (ID) by enhancing processes to ensure efficiency and adherence to the highest standards of regulatory compliance.

The prior method resulted in the loss of opportunities to engage with HCPs who weren’t actually debarred because:

  • It manually identified probable debarred HCP IDs, leading to flagging of all IDs with partial matches.
  • There was difficulty in extracting data from the exclusion notices, which would have helped with exclusion criteria for HCP IDs. The manual, tedious process of getting information from exclusion notices often led to errors and the need for oversight.

Trinity’s Solution

Trinity AI recognized these issues as data operations efficiency challenges. An innovative approach using GenAI, sentence transformer models and a structured methodology for data extraction, cleaning, enrichment and matching can maintain strict compliance, optimize opportunities to engage with HCPs and minimize risk:

Extraction of Programmatic Data, followed by Data Cleaning and Preprocessing, followed by Data Enrichment Through GenAI, resulting in the Identification of HCPs

Project Outcomes

20% increase
in exact
matches

68% reduction
in potential
matches

Improved time
and resource
efficiencies

Reduced
non-compliance
risk

Won company-wide
GenAI innovation
award

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