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Medisolv Acquires Health Elements AI to Automate Data Abstraction and Expand Clinical Registry Support

by Jasmine Pennic 05/01/2026 Leave a Comment

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Medisolv Acquires Health Elements AI to Automate Data Abstraction and Expand Clinical Registry Support

What You Should Know

  • Medisolv, Inc. has acquired Health Elements AI, a specialist in AI-first software that automates the capture and structuring of clinical data from medical records. Financial details of the acquisition were not disclosed.
  • The acquisition aims to reduce the significant administrative burden of manual chart review, which currently impacts more than 4,000 abstracters supported by Medisolv.
  • Health Elements AI reports a 96 percent accuracy rate, leveraging AI and human oversight to outperform traditional manual abstraction methods.
  • The move expands Medisolv’s reach into clinical registries and specialty initiatives, including those from the American College of Cardiology and the American Heart Association.
  • This acquisition follows Medisolv’s recent purchase of Lilac Software, signaling a broader strategy to modernize data exchange between health systems, payers, and professional associations.

As healthcare quality programs expand across regulatory bodies and value-based care models, organizations are facing a “data crisis” characterized by fragmented and incomplete records. To address this, Medisolv, Inc.—which manages over 140 million patient records for 1,800 healthcare organizations—has acquired Health Elements AI. The integration of AI-driven abstraction technology is designed to move clinical data creation “upstream,” ensuring that information is captured and structured more efficiently for reporting and performance improvement.

For Medisolv, this acquisition is a strategic response to the increasing pressure on healthcare teams to “do more with less”. By automating the synthesis of clinical, non-clinical, and manufacturing data, the company is helping its clients move faster and act on more reliable information, ultimately improving the accuracy of the 500+ quality and safety measures Medisolv currently supports.

Automating the Front Lines of Quality Reporting

Manual chart abstraction is one of the most time-intensive bottlenecks in healthcare quality management. Last year alone, Medisolv-supported abstracters reviewed nearly 3 million cases. By deploying Health Elements AI’s platform, Medisolv can significantly reduce the reliance on these manual processes while actually increasing the volume of usable clinical data.

Health Elements AI differentiates itself through an AI-first approach that maintains a 96 percent accuracy rate by combining automated extraction with human expert monitoring. This ensures that the data used for high-stakes regulatory submissions remains compliant and submission-ready. David Lucey, Jr., CEO of Medisolv, noted that most modern quality challenges are fundamentally “data challenges,” and this acquisition provides the tools to build greater confidence in that underlying information.

Expanding Beyond Traditional CMS Programs

While Medisolv is an established leader in CMS and accreditation reporting, the addition of Health Elements AI significantly broadens its footprint in specialty-driven quality initiatives. The platform supports end-to-end workflows for some of the industry’s most critical clinical registries, including:

  • The American College of Cardiology (ACC)
  • The Society of Thoracic Surgeons (STS)
  • The American Heart Association (AHA)

This expansion allows Medisolv to serve as a comprehensive partner for healthcare organizations, managing quality data across the entire spectrum of care—from Medicare Advantage and payer programs (bolstered by the 2026 Lilac acquisition) to highly specialized clinical registries.

Why This Matters

The acquisition of Health Elements AI addresses the reality that manual data entry cannot scale with the rapid growth of value-based care requirements. This move transforms Medisolv from a reporting tool into an intelligent data infrastructure layer.

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Tagged With: Artificial Intelligence, Healthcare Mergers & Acquisitions

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