Health Data Atlas provides a data platform that utilizes AI and extensive claims data to create accurate healthcare provider affiliations and organizational hierarchies. This solution enables healthcare organizations to efficiently link claims to healthcare entities, facilitating informed decision-making in a complex market landscape.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare organizations face challenges in accurately identifying provider affiliations and organizational hierarchies due to the complexity and fragmentation of healthcare data. This makes it difficult to link claims data to the correct healthcare entities, hindering informed decision-making and strategic planning.
Solution
Health Data Atlas offers a data platform that leverages AI, extensive claims data, and a team of healthcare researchers to create accurate healthcare provider affiliations and organizational hierarchies. The platform enables healthcare organizations to efficiently link claims to healthcare entities, facilitating informed decision-making in a complex market landscape. By simplifying healthcare data, Health Data Atlas provides comprehensive coverage, enabling insightful decision-making across the healthcare industry. The ProviderGraph hierarchies allow users to instantly link claims to Healthcare Organizations (HCOs), facilities, and parent Integrated Delivery Networks (IDNs).
Target Audience
The primary customers are analytics companies, consultants, life sciences organizations, health tech companies, and provider groups that require accurate healthcare data for market intelligence, competitive analysis, clinical trial provider recruitment, provider search, benchmarking, and network expansion.
Features
- Organizational Hierarchy dataset links healthcare entities and facilities.
- Provider Profiles and Affiliations dataset leverages a claims dataset containing over 300M patients.
- AI-driven construction of hierarchies using data from NPPES, CMS, state licenses, IRS 990s, SEC filings, web crawling, and internal research.
- Advanced algorithms aggregate data and calculate affiliation types, including employment, hospital privileges, and facility connections.
- Metrics on providers, including procedures offered and calculated specialty.
- Cleansing processes to correct names, addresses, and ownership information.