GenHealth.ai Blog

Read about the latest Generative Healthcare AI news, product updates, and more from the GenHealth team


Blog Posts

CMS finalized sweeping changes to the DMEPOS Competitive Bidding Program, launching nationwide competition in 2028 with tighter pricing, annual accreditation, and new product categories. With margins shrinking and scale increasing, DME providers must act now—streamlining operations, automating workflows, and building national fulfillment capabilities to remain competitive and survive the next round.
GenHealth.ai and Guidehealth achieved up to a 60% reduction in Utilization Management workload using GenHealth’s AI-native platform, leading to $1.2M in annual savings. The system automates clinical data extraction and policy evaluations, improving efficiency, compliance, and decision consistency above 90%.
Health plans face a January 2026 deadline to meet CMS’s new prior authorization mandates. GenHealth outlines a faster, more affordable alternative using FHIR DocumentReference + Binaries and AI—achieving >95% accuracy, 10x lower costs, and real-time turnaround without relying on outdated Da Vinci standards.
At GenHealth we apply a novel approach to predicting medical expenses and medical loss ratio by using our Large Medical Model (LMM) which is trained on 140M patients across the US.
Health plans can boost their financial reimbursement by improving quality measures, which directly impact Medicare Advantage star ratings and result in higher rebates from the government. GenHealth.ai's
This guide outlines the integration of GenHealth's UM/PA application with FHIR servers to meet CMS's 0057f regulations for prior authorization and utilization management. It provides detailed diagrams and explanations for implementing Da Vinci-compliant APIs, covering CRD, DTR, and PAS workflows to help health plans achieve faster turnaround times and improved transparency in the prior authorization process.
GenHealth introduces the Large Medical Model (LMM), a GPT trained on 140M patient records, improving cost prediction by 14.1% over top models, enhancing healthcare analytics
GenHealth.ai has been recognized on the Gartner Hype Cycle for Healthcare Data, Analytics, and AI, 2024. This highlights our commitment to pushing the boundaries of what’s possible through the use of generative AI and a deep understanding of industry needs.
GenHealth now has the ability to create the most accurate synthetic patient histories for patients with any combination of conditions, procedures, demographics, medications, etc.
Generative AI based analytics for healthcare can save a tremendous amount of time lowering the time from question to answer to seconds instead of weeks.
Mastering cost prediction is vital for healthcare. GenHealth.ai’s model achieves an 84.5% Normalized Mean Average Error, surpassing industry standards. Detailed analysis ensures accurate, fair predictions, helping healthcare organizations optimize resources and improve patient care.
We compare state regulations on prior authorization (PA) timeframes and requirements, highlighting differences in standard and urgent requests, electronic submission mandates, and Gold Card exemptions
How GenHealth can use it’s Large Medical Model (LMM) to inform clinicians as they are making care related decisions outside of a clinical encounter.
Using GenHealth’s G-Mode application, health plans and providers can better predict and take action on quality gaps to improve patient outcomes and increase revenue
GenHealth launches the future of prior auth automation with an AI chatbot that understands medical policies and rules from health insurance companies across the US.
GenHealth.ai has developed the world's first prior authorization and medical policy form database, aiming to streamline the complex and burdensome processes in healthcare such as claims adjudication and prior authorization utilizing advanced AI and ETL processes
The proposed rule aims to streamline prior authorization in healthcare by integrating technical and operational changes to enhance health information exchange, reporting, and interoperability.
With generative AI based analytic models, there are many open questions in the industry about efficacy performance, and use cases. This space is just starting to be explored.
It is not an either / or, instead LLMs and LMMs can work together. Both have short comings and optimal use cases. Using them together gets you the best of both worlds.
Introducing the GenHealth Embeddings API: Identify relationships for any medical concept like similar episodes of care, patient matches, providers search, etc
Get up to speed on Generative AI in Healthcare and understand the art of the possible
Learn more about our expertise in Healthcare policy. From working with the health systems which are regulated to the people that write the regs, GenHealth is deep in the industry.
See what GenHealth.ai is building using our 13M seed funding round
We are starting with a Beta product to get early feedback from researchers, industry, doctors, and app developers. Send a note to hello@genhealth.ai to get access!
Reinforcement learning with human feedback (RLHF) is a powerful technique in LLMs. However, RHLF can be counter productive in the case of large medical model (LMM) transformers trained on raw medical event data
The field of AI has made significant advancements in recent years, and the most talked-about models are LLMs, but there are now healthcare specific approaches that leverage transformers.
Learn about why we started GenHealth.ai and how generative healthcare AI will transform the industry.