Secure Exchange Solutions to incorporate NLP in medical review
A networked approach that streamlines information exchange as part of the medical review process for claims is incorporating capabilities from a company offering natural language processing capabilities in an effort to facilitate and speed the review process.
Secure Exchange Solutions (SES) is selecting Linguamatics Health as the natural language processing platform that will support efforts to automate claims reviews.
SES is developing SES Spot, which—when used with another offering called SES Fetch—aims to streamline clinical information exchange and automate the review process, which can occur either before or after a claim for medical services is submitted.
Inefficiencies in the review process increase costs in the healthcare system. SES Spot was developed to evaluate clinical information to help control costs for both providers, as well as public or private health plans.
SES Spot now will incorporate Linguamatics’ I2E to provide artificial intelligence to extract information from both free text and codified data in an electronic medical records system. That will enable comparisons of extracted data with guidelines, and it will support the ability to return evidence, recommendations and an audit trail to either fully or partially automate claims approvals.
“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,” says SES CEO Dan Kazzaz.
Complexities involved in gaining prior authorization for services before they are delivered, as well as medical review afterward, result in major inefficiencies that negatively affect cost, patient care and outcomes, says Simon Beaulah, senior director of healthcare at Linguamatics.
“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,” he says. “Significant savings can be achieved by automatically extracting, analyzing and summarizing all the evidence in the medical record related to the claim.”
Challenges in exchanging patient information related to claims for medical services is one of the major factors leading to higher administrative costs in healthcare, and approaches that apply artificial intelligence to the process might both speed adjudication, and save both time and money for all participants.