STTR Phase I: CLEAR: Reducing Claims Denials in Healthcare Through Blockchain and Machine Learning

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to create transparency around the business logic used by stakeholders in the healthcare system to make transactional decisions as well as create alignment around the current status of healthcare transactions that are part of the work in process. To most people who interact with the healthcare system, it functions more or less as a "black box" with decisions that sometimes defy logic and common sense. Our goal is to use Blockchain and Machine Learning technology to convert this "black box" into a "glass box." The commercial impact of this project could be an up to 25% reduction in claims processing costs for healthcare providers by the elimination of redundant work, re-work and errors. This STTR Phase 1 project proposes two innovations: 1) claims transaction and reason codes managed through a Blockchain so that Providers and Payers can confidently know the accurate status of a claim, and 2) sophisticated statistical and deep learning algorithms for predicting the likelihood of a claim denial with natural language processing of associated notes and appeals. Our product is a mathematically driven software service that utilizes and innovates with multiple technologies: Blockchain distributed ledgers, smart contracts and tokens, and prediction, recommendation, forecasting, non-linear optimization and natural language processing engines within a privacy-preserving data management system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.