KAID Health’s Natural Language Processing Solution Demonstrates Significant Promise in Tracking Persistent Postoperative Opioid Use

KAID Health announced the publication of an important study, “Tracking Persistent Postoperative Opioid Use: A Proof-of-Concept Study Demonstrating a Use Case for Natural Language Processing,” in the journal Regional Anesthesia & Pain Medicine. The study showcases the effectiveness of KAID Health’s NLP solution in detecting prolonged postoperative opioid use, thus addressing a critical issue in patient care and the ongoing opioid epidemic.

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This research solidifies KAID Health’s position as a leader in AI-centric healthcare analytics. Representing the third validation of KAID’s solution in peer-reviewed medical journals, the paper underscores the solution’s efficacy across clinical use cases.

Experts from the University of California San Diego (UCSD) conducted the research, which involved comparing KAID Health’s NLP solution with clinician reviewers to evaluate the solution’s ability to identify opioid usage three months after orthopedic surgery. The prolonged use of opioids following surgery is a common complication and a significant contributor to the opioid crisis. Traditionally, capturing opioid use data from electronic medical records (EMRs) has been labor-intensive, as it often involves extracting information from the free text of medical notes.

“KAID Health’s innovative NLP solution holds the promise of automating the monitoring and measurement of postoperative opioid use, offering tremendous potential to improve patient safety and outcomes,” said Dr. Rodney Gabriel, an author of the paper. He continues, “The study revealed an impressive 90% concordance between the AI model and the clinicians, highlighting the utility of the KAID model in extracting valuable clinical insights from medical charts to enhance patient care.” To read the research, please c*********.

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Importantly, the KAID Health AI models used in this study are not limited to pain control assessment, even though this specific proof-of-concept was looking at that issue. In fact, the platform extracts a comprehensive set of patient information, including medications, conditions, problems, and test results, from both the structured and unstructured sections of the EMR. Employed across various settings, this versatile technology supports critical functions such as b****** and coding, quality measurement, prior authorization chart review, care management, and other clinical workflows.

This groundbreaking research solidifies KAID Health’s position as a leader in AI-centric healthcare analytics. Representing the third validation of KAID’s solution in peer-reviewed medical journals, the published paper further underscores the efficacy and reliability of their technology.

“We are immensely proud of the outcomes of this proof-of-concept study, which demonstrate the power of KAID Health’s NLP solution for improving patient care and addressing the challenges associated with opioid use after surgery,” Kevin Agatstein, CEO at KAID Health, said. “More broadly, our technology’s ability to automate quality and safety data is a significant step towards transforming healthcare delivery.”

Continuing to drive innovation in the healthcare analytics space, KAID Health leverages advanced AI algorithms to empower healthcare providers and enhance patient outcomes. The company remains committed to delivering cutting-edge solutions that optimize healthcare workflows, improve safety, drive provider profitability, and promote the well-being of patients worldwide.

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