Reading Between the Lines: Intelligent Solutions for Unstructured Healthcare Data

By Alan Vitale and Don Searing

Healthcare payers struggle with unstructured data (clinical notes, faxes, handwritten forms), which makes up over 80% of healthcare information. This data, unlike organized claims data, slows operations, hides crucial insights, and leads to poor experiences for both providers and members.

Legacy systems can’t efficiently process this unstructured content. Manual review of documents like medical records, handwritten notes, and faxed claims is slow and often misses vital information, hindering critical processes like grievance handling and clinical reviews.

The answer lies in combining intelligent automation with human expertise. Technologies like Intelligent Content Processing (ICP)—which reads, identifies, extracts, and routes documents—and Natural Language Processing (NLP)—which interprets text context and meaning, including sentiment and clinical terminology—are key. These tools streamline data intake and unlock insights. However, they’re most effective when paired with human teams to manage exceptions, validate data, and provide essential context.

This human-tech partnership significantly improves efficiency. For example, automating grievance intake means documents are scanned, analyzed by NLP for urgency and type, and then automatically routed with key information extracted. This leads to:

• Reduced manual handling

• Faster turnaround times for grievances and appeals

• Improved audit readiness

• Enhanced member and provider satisfaction

• Access to previously hidden data for better analytics and planning.

Ultimately, by leveraging AI with human oversight, unstructured data transforms from a burden into a strategic asset, leading to more efficient, precise, and empathetic healthcare operations.

Read the full article on Health IT Answers.