Engineering Algorithmic Transparency: A Zero-Knowledge Edge Architecture for U.S. Healthcare Billing

The United States healthcare system suffers from systemic pricing opacity and fragmented data silos, resulting in predatory billing practices and widespread medical debt. While federal initiatives like the Hospital Price Transparency Rule attempt to democratize pricing baselines, consumer-facing auditing tools remain encumbered by centralized "Black Box" Software-as-a-Service (SaaS) models. These traditional models force patients to transmit highly sensitive Protected Health Information (PHI) to third-party servers to audit their itemized bills, creating severe privacy liabilities. This paper introduces the OpenHealth Audit Engine, an open-source architectural framework that shifts computational workloads to the edge. By leveraging WebAssembly (Wasm), in-browser neural Optical Character Recognition (OCR), and an autonomous GitOps data pipeline, this system allows patients to mathematically calculate localized Geographic Practice Cost Indices (GPCI) and commercial variants entirely on their local device. This Zero-Knowledge approach democratizes healthcare economics while mathematically eliminating the risk of centralized PHI data breaches.