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

BOSTON--(BUSINESS WIRE)--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.

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 click here.

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 billing 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.

About KAID Health

KAID Health makes care delivery more efficient, effective, and profitable for providers and their payers and Accountable Care Organization partners. Using artificial intelligence and natural language processing, its Whole Chart Analysis platform extracts all relevant data from electronic medical records, including structured data and text. The solution identifies the patient care interventions needed for providers to achieve their clinical, financial, or operational objectives. In parallel, KAID Health extends to payers a comprehensive view of members’ health by combining claims and EMR data. Today, KAID Health’s technology is used by leading providers, health systems, academic medical centers, and payers to automate a variety of workflows, including coding accuracy, quality measurement, prior authorization support, and pre-operative assessment. The company was founded by a veteran team of healthcare information technology and population health innovators. It is based in Boston, MA. To learn more, visit www.kaidhealth.com.