HealthShare Clean Data as a Solution

The health data required for analytics, machine learning, and artificial intelligence algorithms is complex, decentralized, diverse, and difficult to gather. It may be structured, or unstructured. It’s hard to link data across health information systems to the same patient.

Even the same data elements may be identified and stored differently in different systems. When you do reach across systems and locations to aggregate the data, it often creates a dirty mess, not a usable database.

This lack of comprehensive, normalized, and clean data for the target population is holding back your progress and that of the entire healthcare industry.