Claim Denials Management
Streamlining the Claims Process with AI
On average, 24% of claims are denied during the evaluation and payment process, according to the Doctor-Patients Rights Project. Denied claims are large expense for providers and painful for patients who have to pay out-of-pocket or providers who have to write off as losses. Existing claims management processes are highly manual with analysts and rules making choices about which claims to work for resubmission with their limited time.
An AI approach uses machine learning models to streamline the denials management process by finding claims that have a high likelihood of being paid and the highest potential value. By working these claims first, the providers and payers spend the time on those claims that are most likely to be valid and will yield the most value to patients and providers. AI models can also provide reason codes for the denial which streamlines the review process by allowing the investigator to focus on the key issues. Reason codes are also helpful for patients and providers because they can inform them of issues with their claim and help them to fix the claim for reprocessing or change future claims to avoid issues.
The mission at H2O.ai is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. The healthcare industry is a key focus for the company with an initiative to help develop AI healthcare solutions including dedicated, experienced resources for customers, driving healthcare AI events and meetups for healthcare professionals, and membership in Health IT Now, the leading coalition of patient groups, provider organizations, employers, insurers, and other stakeholders. H2O.ai is already working with top healthcare companies including Change Healthcare, Armada Health, Kaiser Permanente, and HCA, and its products include industry leading features for machine learning interpretability required by the healthcare industry for compliance purposes.
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H2O has been the driver for building models at scale. We are talking about billions of claims. You can't do this with standard off the shelf open source techniques.”
Adam Sullivan, Director, Change Healthcare