{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"HealthTech Remedy","title":"SmarterDX's AI for Hospital Revenue Cycle Management with Dr. Michael Gao & Dr. Joshua Geleris","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/b284f847\"></iframe>","width":"100%","height":180,"duration":2901,"description":"Hospitals are a critical, yet incredibly expensive part of our healthcare system. So why are so many operating on razor-thin margins, with some even facing bankruptcy? The answer lies in a massively complex and broken billing system, leading to billions in hospital revenue leakage every year. This episode explores a groundbreaking solution: using AI for hospital revenue cycle management to ensure hospitals are paid accurately for the care they provide. We're joined by Dr. Michael Gao and Dr. Joshua Geleris, the physician co-founders of SmarterDX, a company tackling this crisis head-on.In this deep-dive discussion, the HealthTech Remedy team and the founders of SmarterDX unpack the intricate challenges of hospital finances. We explore the historical complexities of the Diagnosis-Related Group (DRG) system and how tens of thousands of ICD-10 codes create a nightmare for manual coders, leading to frequent errors and costly claim denials. This environment is precisely where physician-led innovation can make a difference. We analyze how SmarterDX's platform leverages clinical documentation improvement AI to find missed diagnoses and justify the care provided, a crucial step to reduce hospital revenue leakage. The discussion covers SmarterDX's two core products: Smarter Prebill, which reviews claims before submission, and Smarter Denials, which provides automated claims denial management by generating evidence-backed appeal letters in minutes. Co-founders Dr. Gao and Dr. Geleris share their founding story, which began when they discovered their own names on lists of attending physicians with missed diagnoses at New York Presbyterian. They explain why the combinatorial complexity of medical coding makes it a perfect problem for AI to solve and how their technology delivers a guaranteed 5-to-1 ROI, adding millions in net new revenue for health systems without requiring new staff. This conversation provides a masterclass in applying AI for hospital revenue cycle...","thumbnail_url":"https://img.transistorcdn.com/Al9s4QJpRCg2VJ2YaV_fo3tDCayXbUO7NTDbnFeSAUQ/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNTVk/OTAwMzQxYWFiZmYy/ZWFlNzFmN2RmOTcx/MDMwNy5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}