The traditional EHR has reached its half-life. It stores data. It meets regulations. But it kills productivity. A new model is needed, one that is based on the actual needs of clinicians and incorporates the latest technologies. Greenway Health decided to engineer their new EHR from the ground-up with AI at its core.
At HIMSS26, I sat down with Richard Atkin, CEO, and Dr. Michael Blackman, Chief Medical Officer at Greenway Health. We discussed the launch of Novare, their new AI-by-design ambulatory EHR platform. The conversation focused on why the industry must stop bolting features onto old tech and start building for the future.
What This Conversation Revealed
- EHRs must move from data repositories to active clinical partners. Atkin noted that current systems were designed to store data and meet regulatory requirements rather than help a clinic improve care delivery.
- The most effective denial is the one that never happens. Dr. Blackman explained that by moving coding decisions “left” in the process and using automated suggestions, practices can stop the cycle of constant rework.
- True AI-by-design makes documentation a byproduct of care. Instead of documentation being an “after event,” the platform uses agentic AI to summarize histories and prompt providers during the visit.
An EHR that is AI-by-design
At HIMSS26 Greenway officially launched Novare.
“Novare is an end-to-end platform for ambulatory practices that brings AI into everything,” Atkin said. “We took a good look in the mirror and concluded that existing EHRs are part of the problem. So we decided to build a brand new platform with AI at its core that would enable physicians to get the information they need at the point of care and to streamline the whole encounter.”
The goal is for Novare to seamlessly integrate into the clinical workflow and to automate the bulk of the manual back-end work that happens after the encounter – like coding, billing, reporting, etc.
What does AI-by-design mean?
“It means thinking about how you would redesign the encounter and everything around it from the ground up,” continued Atkin. “It’s not about trying to automate a fragmented, disconnected system that has grown over the past 20 years. It’s about reimagining the end-to-end workflow and using AI to give physicians more time to deliver care.”
EHRs were originally built to replace paper charts and satisfy regulators, not to help clinics deliver better care. Because they were designed for storage, everything else had to be “bolted on” later. Greenway is using AI-by-design to break from that legacy approach and accelerate innovation.
“The technology has caught up to our vision,” added Dr. Blackman.
Preventing Denials vs Fixing Billing
Dr. Blackman and Atkin used a revenue cycle example to illustrate the power of rethinking the EHR.
With current systems, organizations must wait until after the encounter to fix coding errors or address denials, which is a recipe for financial waste. A proactive system pushes those decisions to the point of care. “The best denial, frankly, is the one you don’t have,” explained Dr. Blackman.
By automating coding suggestions upfront (a feature of Novare), practices spend less time on rework and more time on high-value tasks. This approach ensures the documentation is accurate before the claim even hits the clearinghouse. It turns the revenue cycle into a proactive strategy rather than a defensive one.
Beyond Simple Ambient Recording
Many vendors are focused on just recording the conversation, and turning that recording into documentation. The team at Greenway sees that as a good first step to solving a larger challenge – turning the accumulated health data into proactive care for patients. To do that, Greenway is leveraging agentic AI.
“What our customers told us is that they need to see a longitudinal record, not just automate the encounter,” said Atkin. “That’s what agentic AI enables. That’s what our [Novare] platform is designed to do. We synthesize the information so that the encounter can be more effective.”
“When someone comes in with a simple headache for example,” continued Dr. Blackman. “With a traditional EHR you could flip through the chart and find out when they came in previously with a headache. With ours, the system looks that up and presents it to you – hey this person has been seen for this same condition with the past x, y or z time periods…and here is a summary of those encounters for you.”
In other words, agentic AI becomes a true assistant to the physician which enables better care.
The Bottom Line
Greenway clearly believes that slapping AI onto a 20-year-old, fragmented workflow is like putting a band-aid on a broken leg. You might get a few small wins, but you aren’t going to fix the underlying issue. To actually fix the burnout crisis and put an end to “pajama time,” we need to rethink and redesign EHRs from the ground up. Greenway did that and created a platform where documentation is a natural byproduct of the visit, not an exhausting after-hours chore. One where billing happens seamlessly in the background and where relevant information about the patient is surfaced at the start of the next encounter. It will be interesting to track the adoption of their new Novare platform over the months ahead.
What Healthcare IT Leaders Are Asking
What is the difference between ambient AI and agentic AI?
Ambient AI focuses on the “now” by capturing and transcribing the current conversation between a doctor and patient. Agentic AI goes much further by acting as an intelligent assistant that can search the patient’s entire longitudinal history. It summarizes past encounters, identifies gaps in care, and provides proactive prompts to the physician during the visit, making the encounter far more effective.
How does an AI-native platform reduce clinical burnout?
Burnout is often driven by “pajama time,” where physicians spend hours after work completing charts and searching for information. An AI-native platform makes documentation a byproduct of the visit rather than a separate administrative task. By automating chart prep and summarizing long histories, the technology removes the “hunt” for information, allowing doctors to keep eye contact with their patients and find joy in the practice of medicine again.
Why should RCM leaders care about “moving decisions left”?
Traditional revenue cycle management is reactive, focusing on working and fixing denials after they occur. Moving decisions “left” means using AI to provide automated coding suggestions and documentation checks upfront, while the physician is still with the patient. This prevents errors at the source, leading to fewer denials, less manual rework, and faster payments.
Learn more about Greenway Health at: https://www.greenwayhealth.com/
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