Addressing Improper Payments in Government Healthcare through Blockchain and Generative AI

Abstract

Clinical patient data must be transformed into financial claim formats for submission to state Medicaid agencies and the federal Centers for Medicare and Medicaid Services (CMS). This is achieved through a process called electronic data interchange (EDI), which is specified in regulation and has standards for data definition that are maintained by the American National Standards Institute/Accredited Standards Committee X12. This standard and the data exchange process is the financial gas and protocols that enable healthcare payment by the government. Claims payments made by the U.S. Government for Medicare, the Children’s Health Insurance Program, and Medicaid exceed $1T annually. Of this, and despite the validations enforced by EDI transmission, improper payments in Medicare and Medicaid exceeds $100B each year. We analyze the current state of the art in EDI, and provide a design-oriented technical brief of how blockchain and large language models could address improper payments.

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