Unbiased Data Validation
Inaccurate provider data is a significant obstacle to widespread and equitable access to healthcare in the United States. Innovative technologies can solve healthcare data challenges but how do you know that technology is performing as well as it claims to?
By subjecting our data to impartial analysis we’re holding our proprietary solutions accountable and providing transparency in the industry.
The Erdős Institute performed a blind independent review of Veda’s AI-powered data curation engine, Vectyr, and found highly accurate provider directory data with certain accuracy scores exceeding 90 percent for critical information like addresses, locations, and phone numbers.
How does Veda provide such accurate data?
Veda’s team of data scientists uses supervised learning systems to create optimal provider data profiles and unsupervised learning for grouping data.
The white paper proves: Automation is an effective and necessary approach to supporting health plan members who rely on provider directories to find care.
Reinforcing Commitment to Accountable AI-Powered Solutions in Healthcare
By facilitating accurate provider directory data, as mandated by the No Surprises Act, validation of Veda’s proprietary curation and machine learning methodologies represents a pivotal milestone in Veda’s journey towards fostering greater transparency and accountability in payer data solutions.
As skepticism surrounds AI tools in healthcare, validation from the Erdős Institute underscores Veda’s commitment to leading the market with ethical and reliable solutions,” said Meghan Gaffney, Co-Founder and CEO of Veda. While outdated methods for maintaining accuracy and compliance continue to fail, Veda is proof positive that automation is an effective and necessary approach to supporting health plan members who rely on provider directories to find care.
A rigorous analysis by Erdős not only demonstrates Veda’s commitment to AI excellence but also sheds light on the prevalent issue of ‘ghost networks,’ or inaccurate provider directories. Yale Law and Policy Review found between forty-five and fifty-two percent of provider directory listings had errors, with some individual plans having error rates as high as ninety-eight percent.
WHAT WE DO
Velocity
ROSTER AUTOMATION
Standardize and verify unstructured data with unprecedented speed and accuracy.
Vectyr
PROFILE SEARCH
The most up-to-date, comprehensive, and accurate data source of healthcare providers, groups, and facilities on the market.
Quantym
DIRECTORY ANALYSIS
Review and refresh your network directory to identify areas that affect your quality metrics.