The Department of Veterans Affairs is issuing a presolicitation notice for the procurement of technical support services focused on data quality analysis and management. The initiative falls under the Program Contracting Activity Central and the Health Information and Governance office, aimed at enhancing clinical data quality and person identity management. Key tasks include reviewing technical documents, developing enterprise requirements, executing software testing plans, and providing expertise in data quality. The solicitation is set aside for Small Disadvantaged Veteran-Owned Small Businesses (SDVOSBC), with the applicable NAICS code being 541611 and a size standard of $24.5 million. The Request for Quote (RFQ) will be released in approximately one week with a response period of about 10 business days, and interested parties must submit their quotes electronically. This presolicitation serves as a preliminary announcement, with further details available in the attached Performance Work Statement.
The Performance Work Statement (PWS) for the Department of Veterans Affairs (VA) outlines the requirements for the Data Quality Program (DQP) under the Veteran's Health Administration. The contractor will provide technical analysis and functional support for improving the quality of health data related to identity management and clinical data. Key responsibilities include analyzing identity management technology, documenting business and technical requirements, and supporting data governance and stewardship initiatives. Essential deliverables involve performance reports, data quality analytics, and reviews of business documents to ensure compliance with VA standards. The contract spans 11 months with optional extensions, emphasizing contractor personnel's experience and adherence to security protocols to handle protected health information (PHI). The document establishes a framework for enhancing healthcare data quality within the VA system, demonstrating the commitment to improving veterans' health services through effective data management.