What You Should Know:
Amazon Web Services and Inovalon announced a collaboration to develop AI and ML-based solutions for healthcare organizations to improve patient outcomes and cost-savings.
– The collaborated capabilities are being developed for multiple applications across the broader Inovalon ONE® Platform, the Company’s SaaS-based software platform supporting more than 20,000 customer organizations across the healthcare ecosystem. The initial offerings will focus on risk adjustment, with a particular emphasis on developing natural language processing (NLP) tools to improve risk score accuracy for health plans.
Advanced AI/ML Together with Large Training Datasets
Health plans primarily depend upon medical documentation and medical claims to determine the disease burden, or risk score, of the members of their managed populations. This risk score is then utilized to inform the application of appropriate resources to support members’ health care needs as well as accurate payments and reimbursements. Unfortunately, meaningful disconnects exist between medical documentation and claims data resulting in an incomplete understanding of patient disease status, progression, and care needs, as well as inaccurate payments and reimbursements. As a result, health plans expend significant resources to more accurately understand and substantiate their members’ risks scores.
While Natural Language Processing (NLP) technologies have been applied within the healthcare industry to aid in the capture and analysis of risk score information, the industry’s currently available NLP solutions struggle to tease out key data points from the medical records without an extremely high false positive rate. Further, today’s solutions fail to provide meaningful targeting insight to guide a clinician, medical record reviewer, or auditor to precisely where an area of concern within a patient’s case documentation may lie. The net result is lower accuracy within risk scores, lower understanding of individual patient’s disease status and care needs, higher costs related to accuracy-improving initiatives, and greater risk to health plans with respect to their inadvertent submission of inaccurate risk score data which can lead to potential legal liability and financial penalties.
The NLP/ML powered application being developed collaboratively by Inovalon leverages AWS’s Amazon Comprehend Medical® NLP service to derive insights from unstructured clinical text and map clinical concepts to standardized medical codes like ICD10-CM. The enriched output from Comprehend Medical is combined with a logical scaffolding created from Inovalon’s AI/ML capabilities and deep subject matter expertise. The result is an advanced capability to analyze targeted member medical records to identify those that are highly likely to have meaningful disconnects between the clinical documentation and that of the claims data associated with the patient. Additionally, the solution not only is able to determine the probability of such disconnects being statistical true positives, but also highlight where the evidence which supported a concern resides. The result is a solution that empowers users with powerful insights and enriched patient-level data with greater risk score accuracy to augment claim review efficiency and decrease costs. Inovalon expects the application to be generally available early in 2024.
“Our focus is on the relentless enhancement of the Inovalon ONE Platform so that we can in turn empower our customers to achieve their missions,” said Eron Kelly, President of Inovalon. “This is the first of several collaborations we are doing with AWS to empower our customers to improve healthcare outcomes and economics through the thoughtful and careful use of AI/ML.”
