AutomationX On-Demand

How to Reduce Inefficiencies in Healthcare with ML

A Hyperscience Virtual Case Study

How to Reduce Inefficiencies in Healthcare with ML

Healthcare is an industry built on information, with nearly $250 billion spent on 30 billion healthcare transactions each year.

Whether it's enrolling in health insurance, processing claims, or making changes to an existing policy, healthcare involves internal forms and pages of supporting documentation that vary in layout, quality and complexity.

During open enrollment in particular, organizations are inundated with paperwork, and legacy approaches - usually some combination of outdated data capture tech and manual entry - can’t keep up.

Watch Now

Key learnings


The limitations of legacy processes


Why Machine Learning holds the key to intelligent document processing


How to streamline open enrollment and year-round claims processing


Key questions to ask before adopting an automation solution