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KMWorld 2024, Washington, DC - November 18 - 21 

Improving the medical review process through collaboration and AI

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A health information service provider has chosen a natural language processing (NLP) text analytics solution to help fix bottlenecks in the medical review process.

Secure Exchange Solutions (SES) has  selected Linguamatics Health as the NLP platform for SES SPOT, a solution that when combined with SES Fetch streamlines clinical information exchange and automates the review process. SES SPOT evaluates clinical information to help control costs and improve outcomes so that patients receive the appropriate care more rapidly.

Linguamatics I2E will provide artificial intelligence (AI) to extract information from both free text and codified data in an electronic medical record; to compare extracted data with guidelines; and to return evidence, recommendations and an audit trail to automate or semi-automate approval of claims.

Tom McGraw, SES senior VP of product and government business, says, “After an exhaustive review of 17 vendors, SES selected Linguamatics as the NLP engine most effective at identifying and extracting key clinical criteria and for providing a reasoning layer to make a recommendation.”

SES CEO Dan Kazzaz adds, “Combining Linguamatics NLP technology with other SES components will deliver the solutions needed to help relieve the pressure on both public and private healthcare systems caused by shifts in population demographics.”

Simon Beaulah, senior director, healthcare at Linguamatics, explains, “The complexity of prior authorization and medical review means that there are major inefficiencies in these processes that impact cost, patient care and outcomes. SES and Linguamatics are tackling this challenge with AI approaches that streamline identification of clinical factors and provide recommendations and evidence to speed medical review. Significant savings can be achieved by automatically extracting, analyzing and summarizing all the evidence in the medical record related to the claim.”

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