Commure Up Close: Max Turns Clinical Needs Into Deliverables

“There was a lot of worry that patients would not accept being recorded [with Ambient AI]. However, after many conversations with leaders across the country, we generally see the opposite. Patients are usually on board and acceptance rates are 95% or higher.” - Donald Lazure, PA, Enterprise Clinical Strategy Lead

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In this installment of Commure Uncharted, in-house clinical SME, Donald Lazure, PA, speaks from personal experience on bringing AI into the exam room without losing patient trust and what’s driving adoption amongst providers. 

Q: Let’s start with data privacy and security. Providers are hearing concerns about AI from patients, including potential HIPAA violations, breaches, and unclear vendor data handling practices. How should providers address these concerns? 

Donald Lazure:
As a provider, you lean on your organization and IT team to vet this. They need to dig into where the data is stored, onshore or offshore, what type of cloud is used, and the overall architecture.

The other piece is authorization and access, who should see the data and at what level. Any AI platform should let you tailor authorization to individuals and roles. A medical assistant may need a different view of PHI than a PA or an MD. Your office IT staff may not need PHI at all. This allows people to work at the top of their license while protecting privacy.

In Epic, for certain psychiatric notes, there is an extra security step to confirm you actually want to open that record, in case you mis-click. All this being said, these are valid concerns that people have, and they definitely need to be evaluated and vetted when bringing on an AI healthcare tool.

Q: Some patients may feel uneasy about being recorded during a visit. Should they be apprehensive, and how do you ease those concerns?

Donald Lazure:
I have been in the ambient AI space for a few years now. Early on, there was a lot of worry that patients would not accept being recorded. Across a couple of companies I’ve worked for and many conversations with leaders across the country, we generally see the opposite. Patients are usually on board and acceptance rates are 95% or higher, which has been a pleasant surprise.

Should there be some caution? Yes. Technology should be vetted and used appropriately. Large language models are being fine-tuned for healthcare with guardrails so they do not reach out to the entire web. Hallucination rates have come down, and models are better at contextualizing the conversation and the information collected. Patients also see AI more in daily life now that ChatGPT is widespread, so it feels like a normal technology advancement. I do not see this as a major stumbling block on the patient side, and I am happy about that.

Q: What does it look like when ambient AI fits well into provider workflows?

Donald Lazure:
The North Star is you walk into a room and speak, the system knows who is there, picks up voices, maybe even notices facial expressions or hand motions, and can act on what is said. We are not there yet, but we are a lot further along that path than I would have guessed five years ago.

A good integration lets the clinician care for the patient better by bringing the right information to the forefront. It adds clinical insight and context from past history without making you dig through the EHR, health information exchanges, lab portals, and everything else.

It also helps with decision-making. It can surface evidence-based guidelines and flag things like a medication that should be changed because of a QT prolongation on the last EKG or a drug interaction in the medication list. That kind of cue is better before the order is placed, so you do not have to undo work. And then everything needs to land in the EHR cleanly. The EHR is still the record of truth, so the ambient capture should flow in appropriately and simply, without extra steps and clicks.

Q: From your conversations with other providers, what tells you these AI tools are working—and what red flags make people pause?

Donald Lazure:
The strongest acceptance comes from clinicians who actually use ambient technology regularly. They report amazing satisfaction, reduced cognitive load, reduced burnout, and, depending on the level of integration, faster completion of encounters.

On the revenue cycle side, you generally see an uptick in what gets captured because clinicians are now documenting the full scope of work. Notes are more robust, so you are appropriately billing for what happened, whereas very short notes limited what you could code.

Where people hesitate when it comes to adopting ambient AI tools is integration. If it writes a great note, but I have to copy and paste sections into different parts of the EHR, then edit in multiple fields, it slows me down. If it does not bring additional care cues or past medical context to the forefront and only captures the moment in the room, there is still a lot of work to get it into the EHR. When integrations are not up to par, adoption drops because it feels like a slowdown.

Q: What needs to change in the EHR and vendor ecosystem to unlock real progress with AI?

Donald Lazure:
As EHRs roll out their own AI tools, I worry that limiting interoperability with software vendors will choke off R&D. Sometimes, there is a deal with a smaller company. Other times, the EHR builds it. They do not have the time and energy to match what startups in places like Silicon Valley and Boston are putting into health AI. I would hate to see innovation slowed because startups do not get the opportunity to plug in.

We also need to move away from point solutions. That is a big part of Commure’s premise: support the patient journey end-to-end, from first contact through discharge and financial clearance, with pieces that work together. Otherwise, you end up with small tools that do not talk to each other, and care gets piecemeal.

I would like to see stronger interoperability across startups, health systems, and existing tools. Give us a common code structure and a shared platform so these systems can speak to each other in context. Then everyone can do their best work in their lane and still connect across the choices a healthcare organization makes.

Q: “Change management” gets used everywhere. In healthcare, what does it mean, and how can it help health systems adopt AI with confidence?

Donald Lazure:
Change management can be individual, departmental, organizational, or even global. At the global level, it is asking why we keep doing things the way we do today. Why does the EHR have to be the record of truth? Could we capture everything in a database and query it with generative AI? Do we really need discrete fields, APIs, and HL7 feeds forever? Maybe each patient could have their own database. In a far-off future, that could even be something like a chip under your skin that you scan so the system can query it. That is way down the road, but it would be beautiful.

At the user level, I see this with some surgeons. They run from case to case and try to squeeze in clinic patients in between. They do not want to spend five or ten minutes learning something in the current EHR that might save them hours later. They just want to get it done the way they always have. A practical driver of change is seeing colleagues in the same specialty adopt a tool, get out of the office on time, and enjoy their work more. Getting a few key people to pilot and then show results to their peers goes a long way.

At the organizational level, change management is hard because you need IT resources and upfront spend on services and configuration. You make adjustments now and hope to see ROI later. That return is not always money. It can be better patient care and improved staff satisfaction. Those benefits matter, but they are harder to measure, which is part of why change management is difficult.

Q: As pressure mounts to justify AI investments, health systems are taking a harder look at where ambient AI can drive measurable value. Where should they focus?

Donald Lazure:
It is often a long-term gain. It is rarely one line item or one role you no longer hire. What you do see is happier end users, less cognitive burden, reduced burnout, and better retention. That is a hard ROI to pin down because you do not know when someone would have left. I have seen it quoted that hiring and ramping a new physician can cost around a million dollars to reach full productivity. That is a big number, but proving it out takes years.

You can measure revenue tied to more complete documentation. Compare providers using ambient to their own prior period, or to colleagues who are not using ambient, and look at captured revenue. That requires pulling data from the clinic, the revenue cycle team, and finance, which makes the analysis harder because it spans multiple stages of the patient journey.

There are time metrics like minutes spent creating a note, but those can be misleading. If a provider leaves the EHR open in a note field while multitasking, the time capture is not accurate. It is common to leave a note open, which is why those metrics can be tricky for ROI.

Q: Ten years from now, if we have a very advanced AI doctor, what role will humans play in care?

Donald Lazure:
It all depends on how patients receive this new technology. We could automate AI in certain instances, like low-level urgent care or for people who cannot make it to an appointment. But the clinician-patient relationship is meant to be ongoing. There is empathy, understanding, and education that we perform as humans. AI is getting better in that respect, and there are studies that say AI can score higher on empathy. So we will see. A lot comes down to patient acceptance. In a future state, one clinician might manage a few different agents that see patients, while the clinician provides oversight across multiple patients at once, which could be a realistic next step.

You likely had several options — why did you choose Commure?

Prachi Shah, Head of Product (MS Computer Science): I’ve long been passionate about the intersection of healthcare and technology, where innovation can drive meaningful change. Prior to Commure, I founded a startup that applied VR to brain surgery planning and worked at Google Health on AI-driven disease diagnosis. Yet the most significant impact of my career has been at Commure. The company’s speed, deep customer focus, and commitment to solving critical healthcare challenges have enabled me to help turn ambitious ideas into solutions that meaningfully support both clinicians and patients.

Shreyas Basavaraj, Technical Operations Manager (MS Engineering Design ‘22): I came across Athelas (Commure) when I watched a Y-Combinator Interview with Tanay Tandon and Garry Tan. It was such a powerful run-down of everything they were trying to do (back then). I was so inspired to see Tanay’s journey as an entrepreneur over the years that I immediately applied & really hoped I would get a call back!

Vincent Chang, Software Engineer (BS & MS Materials Science ‘22): Coming out of Epic, I knew the healthcare industry was incredibly complicated and that I wanted to continue to work to attempt to make it an easier space to navigate. Commure’s goal of simplifying the healthcare space aligned with my goals.

How did CMU prepare you for working at Commure?

Prachi: Carnegie Mellon prepared me by giving me both technical depth and a builder’s mindset. The rigorous computer science program taught me how to break down complex problems and design scalable systems, while the collaborative, entrepreneurial environment encouraged me to take ownership and move fast. Those lessons translate directly to Commure, where we’re solving some of the hardest problems in healthcare.

Shreyas: CMU prepared me through challenging technical and product-development courses, fast-paced deadlines, and collaboration with peers from diverse backgrounds—engineers, designers, and business leaders. Working across disciplines taught me how to navigate different perspectives, drive cross-functional conversations, and align on solutions. This experience strengthened my communication and problem-solving skills, which I now apply daily when working with customers, engineers, and product and operations leaders at Commure.

Vincent: CMU pushed me to be a good problem solver and taught me how to tackle any problems that came my way. Working at Commure feels similar in many ways. The day-to-day tasks are an ever-changing list of challenges, but what makes the work here rewarding is knowing that these challenges are faced by real users.

What excited you most about our mission or team when you were deciding where to go?

Prachi: What excited me most was the caliber of the team. From the very beginning, it was clear that Commure had assembled some of the brightest, most driven people I’d ever worked with. Everyone here is deeply committed to solving hard problems in healthcare, and the level of collaboration is unlike anywhere else. I knew that joining this team would push me to grow and allow us to achieve things that wouldn’t be possible alone. 

Shreyas: I was immediately drawn to the team's audacious goal of revolutionizing the legacy healthcare industry. Seeing such a forward-thinking vision championed by a young and energetic team was incredibly motivating.

Vincent: Commure’s emphasis on speed was very enticing to me when I was deciding on where to go next. I wanted more direct customer impact and I wanted to be able to solve the small problems as they came up. I also wanted quick decisions and quick solutions, rather than getting bogged down with never-ending discussions on theoretical issues.

How did you weigh Commure against more “traditional” post-grad options (e.g. big tech)?

Prachi: I actually worked in big tech, at Google, and enjoyed my time there, but decided that working at start-ups is a better fit for me. I thrive in smaller, high-growth environments, where you wear multiple hats, every day is different, and you do whatever it takes to get things done.

Shreyas: I’d worked for 4 years in MNCs (Oracle Health, KPMG) and as I came to grad school, I was really interested in exploring startups in the Bay Area, as it’s possibly the best tech ecosystem in the world. I really wanted to work in lean organizations to be able to own, grow, and take on big projects. 

Vincent: Coming out of ‘big tech’ at Epic, Commure was exactly what I was looking for. I wanted a faster-paced environment and Commure’s value of speed above all else really resonated with me. I had been on trips shadowing healthcare users and seeing issues, but being unable to fix them with any urgency was disheartening.

What is something you are really proud of accomplishing?

Prachi: I’m proud of our entire product portfolio! Our revenue cycle product processes 10 billion dollars worth of claims yearly. Our Ambient product supports 10 million appoints yearly, which is 1% of all appointments in the US. Our Strongline product protects over 250,000 nurses from duress events and our patient experience product produces 100 million yearly patient touchpoints. Such scale and impact coming from one startup is something we should be extremely proud of.

Shreyas: I am really proud to have led the scaling of ops for a core RCM offering, Automated Patient Eligibility. This involved wearing a lot of hats flying out to meet customers to understand their pain points, growing comfortable with the ambiguity, and building infrastructure to support a growing team.

Vincent: I’m most proud of being able to solve customer issues quickly. A notable example is being able to push fixes out overnight during a two-day onsite trip and seeing users immediately using the new feature the next day.

What would you tell another CMU student considering Commure today?

Prachi: There are a lot of different products you could be working on. Why work on ad optimization when you can save lives?

Shreyas: Pick Commure if you want to take on ownership of solving problems from the ground up from Day 1. You will meet incredible talent who inspire you, make good friends, and get to be part of making healthcare better!

Vincent: No matter where you start working, there will be a learning curve transitioning from academia to the workforce. Commure is a great place to start because you’ll get a lot of opportunities to grow fast and exhibit your skills early, all while tackling real-world problems.

Interested in a career building the next generation of healthcare technology powered by AI? We are always looking for talented people across our departments.

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1% of all US Physician appointments now run on Commure Ambient AI. That's over 20 million annualized encounters. This is proof that when a targeted, well-designed healthcare automation solution delivers both clinical and financial value, adoption stops being an AI experiment and becomes an operational necessity.

Below are the lessons we’ve learned along the way working with small clinics that have enabled Commure to power the largest health systems in America.

Commure’s Journey: Focusing Where the Bulk of Care Is Delivered 

The majority of patient encounters happen outside of large medical centers and academic institutions. Independent practices, community hospitals, rural health systems, and outpatient clinics handle most preventive, chronic, and follow-up care.

These organizations typically run on tighter operational margins with staffing models leaving less room for redundancy and technology resources often limited. That means the cost of inefficiency is higher, both in time and in dollars. In a small rural clinic, shaving five minutes off every appointment could mean one or two extra patients seen each day.

These care environments are also where innovation cycles run fastest. With leaner teams and less bureaucracy, independent practices and community hospitals create a tighter feedback loop between clinicians, staff, and technology. For Commure, this has meant the opportunity to co-develop solutions in real-world settings, refining them quickly, and then scaling those proven gains into larger enterprises.

Developing with Rapid Feedback Loops in Clinic Settings 

From the outset, Commure focused deployments in care environments where speed, adaptability, and clear ROI are critical. These organizations need solutions that can integrate into existing workflows without a six-month change management program.

For automation to succeed here, it must:

• Work within current EHR systems without costly rip-and-replace projects.
  
  
• Support both clinical and billing workflows to ensure every improvement in care delivery is matched by strong revenue cycle performance.
  
  
• Deploy in weeks, not quarters, to generate early wins and keep leadership and staff engaged.

Commure CTO, Dhruv Parthasarathy, highlighted this approach at the most recent Commure Nexus event: “These small practices enable us to do cutting-edge work. They're almost like development labs and research settings for us; they co-develop, they want to take risks, they have really interesting use cases, and they move really, really fast. So we perfect everything with them, and then take that same technology up to the biggest health systems and EHRs in the world.”

By leaning into our agile and scrappy Silicon Valley roots, Commure is laying the groundwork for broader, system-wide adoption by proving value first in faster-moving, operationally-lean settings.

Growth Accelerators: Factors Driving Adoption

The rapid adoption of Commure Ambient AI and our integrated revenue cycle automation is driven by four main factors:

1. Clinician satisfaction:
   Clinicians see immediate benefits: less time spent charting, fewer clicks, and more time with patients. In some deployments, charting time has dropped by over 80%, with providers also capturing more billable work through accurate documentation.
   
   
2. Integrated clinical and financial impact
   Tight coupling between documentation and revenue cycle automation means fewer missed charges, cleaner claims, and faster payment. That combination supports both patient care quality and financial stewardship.
   
   
3. Peer-to-peer influence
   Healthcare communities talk. When a practice or hospital in a region starts seeing results, others take notice. Word-of-mouth adoption, especially among clinicians, has been a strong driver of growth.
   
   
4. Forward-deployed engineering
   Our engineering teams work side-by-side with clinicians and administrative staff during implementation. This hands-on approach ensures rapid customization to workflows, faster issue resolution, and continuous product refinement based on real-world feedback, accelerating time to value and deepening user trust.

Implications for Healthcare Leadership Across the Ecosystem

The success of healthcare automation solutions in high-volume, operationally lean settings has significant implications for health system leaders across the industry:

• Scalability is proven in smaller settings first. If it works in a clinic with minimal IT resources, it will work in a fully staffed enterprise IT department.
  
  
• Reliability comes from daily use and direct feedback. Clinicians stress-test these solutions in the real world, and their input goes straight to engineers to drive rapid improvements.
  
  
• Adaptability drives ROI. Automation solutions tailored to clinical realities will outperform top-down initiatives that disrupt established workflows.
  

For large health systems, these lessons offer a roadmap: start in high-impact, high-volume areas, then expand across the enterprise.

Building Toward System-Wide Transformation

The future of healthcare automation will be defined by solutions that work across the spectrum of care settings. Commure’s experience shows that success in the most resource-constrained environments is the strongest proof point for enterprise-scale readiness.

By continuing to design solutions that integrate seamlessly, deliver measurable outcomes, and align with the operational realities of different organizations, we’re building a foundation for system-wide transformation.

Whether you’re leading a rural clinic network, community hospital, or large health system, the path forward is clear: choose healthcare automation solutions that meet your clinical teams where they work, support your financial performance, and scale without friction.

If you are ready to rapidly build, deploy, and customize solutions that solve your most pressing challenges, we are ready to collaborate.

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In the latest KLAS First Look, Commure Ambient AI earned a strong 93.3 overall performance score, with 100% of customers saying they would buy it again*. KLAS spoke with health system leaders and doctors to understand how Commure Ambient AI performs in everyday clinical workflows. The interviews point to less time spent on documentation, stronger note quality, and a better experience for providers.

Commure serves over 100 enterprises (1% of all US physician appointments) that report more than $500M in annual net patient revenue across 60+ EHRs. If you are exploring ambient AI and want a solution that includes end-to-end RCM automation, read what stood out in the KLAS research: where the product is strongest, how it integrates, and which features teams actually adopt. Want all of the details? Download the full report here.

Performance at a glance
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• 93.3 overall performance score with 100% saying they would buy again and 100% including the solution in long-term plans*
  
  
• Key performance indicators: buyers gave high marks where it matters with an A+ for executive involvement, A for supporting integration goals, A- for needed functionality and ease of use, and A+ for likely to recommend*

“Commure offers an ambient scribe product to assist in medical documentation to decrease the overall provider burden that documentation usually creates. Commure Ambient AI is a true ambient scribe instead of traditional dictation software. A lot of people say they have an AI scribe, but in reality, it is a fancy dictation system, whereas Commure Ambient AI is truly in the background.” —CEO/president

Strengths customers call out
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• White-glove support & responsiveness: hands-on help pre-, mid-, and post-launch; quick access to the right people to resolve issues
  
  
• Continuous improvement: rapid iteration and willingness to tailor to real-world workflows rather than “set it and forget it”
  
  
• Seamless integrations: alignment with health system goals and existing tech stacks

“The technical support is a key strength for Commure, and that support is available during the onboarding and launch processes and immediately after. The vendor makes their people very readily available to assist with any issues that come up. What sets the vendor apart is their pre-, mid-, and post-launch support.” —CEO/president

“The key strengths of Commure are that they are always at the tip of the spear when it comes to new technology and improving and that they listen to how the solution is being used and adjust for that. They don’t just leave Commure Ambient AI by itself and hope for the best.” —Physician

Adoption of key functionalities
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Organizations interviewed reported strong uptake of capabilities that matter in daily practice, including:

• Improved collection and decreased denial rates: Built in automated coding and denials copilot resubmission tools
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• Forward-deployed engineers: On-site or virtual engineers that accelerate custom integrations and real-time problem-solving
  
  
• AI Studio: Ability to manage personalization and templates
  
  
• Multiple recordings: Ability to have multiple recordings with intelligent start/stop functionality per encounter
  
  
• Multilingual support services: Multispeaker conversational support across 60+ languages, with advanced dialect and accent handling

“I think [Commure Ambient AI] has improved the quality of life for all our providers, and it has made everybody really happy. I think it will continue with what it can do. The biggest thing is that documentation is the worst part of the job. So the fact that the tool has made that part easier and has actually improved people’s experience with documentation is huge.” —CEO/president‍

Read the full KLAS First Look report for yourself
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Ready to see all the details? Download the KLAS First Look to view the full KPI grades, the strengths and improvement areas in customers’ own words, and a clear snapshot of which features teams are actually adopting.

You will also get respondent profiles, integration and onboarding notes, and practical lessons you can use in your evaluation. Grab the report to decide if Commure Ambient AI fits your workflows
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Download the Full KLAS First Look

*Report based on limited data

Tell us a little bit about yourself—what do you like to do outside of work?

I was born and raised in San Diego, so naturally, I try to take advantage of the sunshine every chance I get. I’m a proud dad to two boys, Cooper (3) and Stetson (1), and happily married to my wife, Kennedi. Most of my free time revolves around family adventures, whether that’s navigating the zoo with my kids, chasing them around the park, or just enjoying the outdoors. When I do manage to sneak away, you’ll usually find me on the golf course or in the ocean.

As a kid, what did you want to be when you grew up?

I always knew I wanted to do something in public service. Early on, I dreamed of working in law enforcement, inspired by my dad, who served as a San Diego Police officer for 35 years. Watching the way he served his community, especially in family and community services, made a big impression on me. Over time, my interests shifted toward counseling, and I pursued a degree in Marriage and Family Therapy. Eventually, the business world pulled me in, and while it wasn’t the path I originally imagined, it’s one I’m grateful for. It’s led me to where I am today, and I wouldn’t change that for anything.

Describe a day in the life of your role.

As part of the Launch and Implementation team, I lead the West Region. My day is a balancing act between managing the needs of my own clients and supporting the broader implementation team. A lot of my time goes into unblocking bottlenecks, fine-tuning processes, and thinking about how we can scale both our product and our approach.

I try to structure my days like a sandwich, starting and ending with internal meetings or project work, with the middle of the day focused squarely on clients. I’ve learned that time spent addressing a client’s needs is just as important as time spent preparing for those conversations. Beyond client work, I carve out time to mentor and develop my team, because I believe investing in their growth pays dividends across the entire organization.

What made you decide to join Commure?

After leaving Uber in 2020, I dove into the startup world, supporting early-stage SaaS companies and even working as an independent consultant. I loved the hustle and grit of building something from the ground up, but after my second son, Stetson, was born, I started looking for a balance of stability, growth, and impact.

A former Uber colleague, Manus Burns, introduced me to Commure, and it checked every box. I was drawn to the opportunity to build scalable systems in a high-growth environment, but what keeps me here is the culture of hustle, the customer-first mentality, and the real-world impact we make. At the end of the day, what we build helps clients and directly affects patient care. That sense of purpose is powerful.

How would you describe the Commure company culture?

Fast-paced, collaborative, and energizing. No two days are ever the same, and it’s hard to find anyone here who isn’t smiling. The team is deeply aligned, and it feels like there’s one heartbeat driving us forward together.

I often describe it like stepping onto a treadmill that’s already running. If you’re not ready, it can hit you hard at first. But once you find your rhythm, the energy is contagious. What I appreciate most is that success here is shared; it’s never about the individual, it’s about what we accomplish as a team.

What advice would you give someone on their first day at Commure?

Always ask “why.” Why do we do things a certain way? Why does it matter? Why does the client care? The most successful people here are the most resourceful, those who know how to seek out context, filter information, and apply it when it matters.

I tell new team members not to overwhelm themselves by trying to master everything at once. Instead, bucket information by where it lives in the customer journey or product space. Recognize what’s important now, and set aside the rest until it becomes relevant. That approach not only keeps you sane but also ensures you’re focused on what actually drives value in the moment.

What has been your greatest accomplishment so far at Commure?

Without a doubt, building a team and watching them grow. In a high-growth environment, it’s easy to get consumed by metrics and results, but I try to pause and appreciate the people behind the work. Seeing team members develop new skills, grow in confidence, and achieve their career goals has been incredibly rewarding.

On the client side, my biggest accomplishment has been helping practices turn things around when they’re struggling. We work with clients who trust us with what I like to call the “second heartbeat” of their practice (the first being patient care), the second being their revenue cycle. Taking a client from “we might have to close our doors” to “our revenue is up, and we’re spending less time worrying about rejections,” for example, is an incredible feeling. That’s the kind of impact I want to keep making.

Interested in a career building the next generation of healthcare technology powered by AI? We are always looking for talented people across our departments.

Explore Career Opportunities

Healthcare is undergoing structural transformation. According to Commure CEO Tanay Tandon, the most consequential role of artificial intelligence today lies in concrete changes to how health systems operate versus speculative applications.

“Artificial intelligence is going to play a bigger role than people even realize in transforming the operating model and margin profile of health systems,” shared Tanay Tandon, CEO of Commure.

Across clinical and administrative domains, AI is already influencing the time clinicians spend with patients, the cost structures of provider organizations, and the quality of the patient experience.

Returning Time to Physicians by Eliminating Redundant Work

Commure’s approach begins with one of the most frequently cited burdens on clinicians: documentation. With Commure Ambient AI, health systems are reducing the need for manual note entry by capturing and structuring conversations in real time. The result is a measurable return of time to providers and staff.

“One of the most beautiful things we get to do is give physicians their time back—whether that’s at the end of the day or during the patient encounter,” Tandon shared. “A couple of hours a day, per physician. That translates into millions of dollars of productivity for a system.”

This regained time directly impacts both the financial and human aspects of clinical practice, supporting not only efficiency but also the physician-patient relationship.

Reducing Operational Waste in Revenue Cycle Functions

A second area of impact is revenue cycle management (RCM). Administrative processes, particularly those involving claims and denials, have historically required extensive manual labor. With tools like Commure RCM, health systems can now apply large language models to accelerate and simplify these functions.

“A single claim denial today might require five different people to touch it,” said Tandon. “With large language models, that can become one person reviewing the output. That’s not a five-year or ten-year vision—that’s an 18 month vision.”

By automating repetitive processes and reallocating staff time, health systems may significantly lower their cost to collect from insurance companies.

“The exciting thing there is, if we reduce the cost to collect using LLMs as part of the Commure RCM solution, we can put those dollars back on the table for health systems to serve their patients and their communities.”

Improving Patient Experience with 24/7 AI Guidance

Patients, too, face persistent friction in their healthcare interactions—particularly around scheduling, preparation, and information access. Commure Engage offers intelligent assistance to guide patients through their care journeys, regardless of time of day.

“In some cases, your LLM has the information ready to go, pulled from the EMR. It can respond via text or through a phone call with a natural-sounding voice that’s incredibly helpful to the patient and can guide them through their care journey,” said Tandon.

This continuous availability reduces no-shows and ensures patients arrive informed and prepared. As a result, care encounters become more productive for clinicians and less stressful for patients.

The Cumulative Effect: Toward a More Rational System

What unites these disparate use cases is their cumulative impact. Together they represent a meaningful shift in how health systems manage resources. Time regained for providers becomes capacity for additional patients. Dollars saved on collections may be reinvested in staffing or care delivery. Patients better supported between visits are more likely to return, adhere to care plans, and avoid preventable complications.

None of these improvements require speculative technologies or future-state projections. They are available now, contingent only on careful implementation and a willingness to reconsider legacy workflows. As Tandon’s remarks suggest, the opportunity for transformation lies not in replacing clinical expertise, but in removing the noise that obstructs it.

In short, the application of AI in healthcare operations need not be radical to be consequential. It need only be precise, pragmatic, and anchored in the actual workings of care.

Welcome to Commure Uncharted, a Q&A series where we sit down with healthcare industry thought leaders to discuss what the future of AI in healthcare could look like.

This installment, we are joined by Commure’s Chief Medical Officer, Dr. Jamie Colbert, MD, MBA, who still sees patients and works with clinicians and clients on how AI fits into care. Jamie discusses privacy and the sanctity of the exam room, explains when AI tools can help versus when a person needs to be in the loop, and shares what actually builds trust in busy workflows. He also offers a realistic take on accountability and bias and sets expectations for the next five years.

Q: Looking five years ahead, where do you see AI in healthcare? Will doctors still be face-to-face with patients?

Dr. Colbert:
It’s important to remember that AI is still in its infancy. ChatGPT has only been available for less than three years, so it is hard to predict exactly where things are going. Today, most organizations are not comfortable putting patients in front of AI without a human in the loop for anything high stakes. By high stakes, I mean clinical decisions about how to treat a patient or how to handle a symptom or concern related to their health.

However, I do expect the field to evolve. It may not be very far down the road before we feel confident that AI is drawing on the right body of evidence, providing high-quality recommendations, and handling cognitive tasks that today belong to people with 10 or 15 years of specialized training.

That being said, I do not expect AI to completely replace physicians. AI will replace many aspects of healthcare, but there will still be a need for someone to sit with you, hold your hand, and lay a stethoscope on you. There is a science of medicine, and there is an art of medicine. The humanistic component is essential. It is health care because there is care in it. In the near term, say five years, I do not see a point where we feel cared for entirely by AI.

Q: What are the most common concerns you’re hearing from patients about AI in healthcare?

Dr. Colbert:
There are a few broad categories of concern. First, there is the issue of privacy and what happens to patient information after it is shared with AI. If a large language model owned by a big tech company like Google or OpenAI is involved, what happens to the data that is recorded to generate a note or to power a chatbot? Who has access to it? Could it be used to develop new products? Could someone trace it back to them? Patients worry that the exam room is no longer a sacred space and that their words could show up elsewhere.

Another category is trust in the technology itself and whether AI can provide accurate answers. Is it trustworthy? Is it drawing on appropriate resources? Was it trained on up-to-date datasets, clinical evidence, and studies?

A third category is concern about losing the human connection. Patients value and trust their providers. They worry hospitals and health systems will try to replace that connection with technology, so they no longer have a friendly face when they are not feeling well. There is no substitute for someone holding your hand when you are in pain or uncomfortable. Even if the AI has the correct answers, being alone in a sterile room without a person to offer comfort and reassurance would feel like a loss.

However, on the whole, I find that the overwhelming majority of patients are excited about the potential of AI to help improve their healthcare experience. While they may have concerns, they are on the whole hopeful that AI will be a net benefit to them. 

Q: Do patients trust AI more when it works behind the scenes versus when it interacts with them directly?

Dr. Colbert:
It depends on how the AI is used. When AI works behind the scenes to help physicians stay current and summarize treatment options, the patient is still interacting with their doctor, and the role of the AI is more in the background. In my experience, this tends to be acceptable to nearly all patients. 

Direct interaction varies by task. For something algorithmic like scheduling, many patients are fine with an agent because it is a discrete task that gets them an appointment. When the interaction moves into clinical territory, like what to do next for pain or shortness of breath, the threshold for trust is higher, and some patients will want a person who can answer questions and handle more complex situations.

Q: What’s driving clinician hesitancy around utilizing AI tools in daily workflows?

Dr. Colbert:
A couple of reasons come to mind. Firstly, physicians have been misled in the past by technology that promised efficiency and ended up adding work. Many tools translated to more clicks and more administrative tasks, so there is skepticism about whether AI is really helping or just a shiny object that generates buzz, versus something that will truly make their jobs better and more efficient.

Trust is another issue. For a complex case that might take two or three hours of literature review, AI could summarize the research so a provider spends 20 minutes instead. That can be valuable, but clinicians need to feel confident that the model used the right studies, is current, and did not miss important evidence. The same questions apply to ambient AI. If it listens to a 20-minute conversation and condenses it into 250 to 300 words, it has to be accurate. It also has to make judgment calls about what stays in the note and what gets left out, and providers need to trust how those decisions are made.

There is also the transparency challenge. AI can sometimes feel like a black box, and a physician may not know exactly which sources the AI used to generate its response. Citation is getting better, but there are still questions.

Q: How much of the hesitation around AI comes from technical limitations versus a general fear of change and disruption?

Dr. Colbert:
They are both equally important. It depends on who you speak with and what they worry about, but each is a real barrier to broader adoption. We have not solved the workforce questions yet: where AI fits in the workflow, what changes we make to daily routines, and how those changes make physicians happier and more productive. Providers also look at the outputs that define their work, which vary by role and setting. They want tools that help increase productivity and revenue where relevant, while still letting them enjoy what they do and helping patients feel more cared for.

On the technical side, the models are still evolving. The way to address that is to keep watching them, testing them, and continuing to really poke at them. We need to understand the limitations and the biases, and make sure we do not have blinders on that cause us to miss issues that come from relying too heavily on AI. That ongoing scrutiny surfaces problems and blind spots, and over time it gives us a path to address them as the tools improve.

Q: If AI makes a mistake in a clinical setting, how should health systems think about accountability?

Dr. Colbert:
When a physician has a treatment relationship with a patient, the doctor is ultimately responsible for the care. Physicians who use AI should continue to own the information shared with patients, the visit documentation, and any AI output that directly affects care. That is why there still needs to be a human in the loop for anything that interfaces with patients. The physician is still the one who signs their name and is the one who can be sued if something goes wrong.

Q: How should health systems address potential bias when using AI?

Dr. Colbert:
One approach is to consult other sources and use AI as one tool rather than fully relying on it when there are concerns about bias. Bias can show up in many ways. If a model is more oriented to patients of a certain race or demographic, and the patient in front of you does not fit that profile, you can try to tweak the AI by introducing the patient’s unique characteristics.

If the patient has a disability, for example, make sure the system accounts for the special considerations that come with that. My hope is that as these models improve, we will better account for potential biases by acknowledging differences between patients and steering the output toward recommendations that match what makes that individual patient special, instead of generic defaults.

Q: What is one myth or fear about healthcare AI you wish we could put to rest for good?

Dr. Colbert:
The myth that AI is replacing doctors. Right now, that is not the reality, and patients/doctors should not worry about it. I am not seeing any widescale attempt to fully replace clinicians with AI. Patients should think of AI as tools that help deliver better care so they have a better experience and achieve better outcomes.

At Commure, we believe technology should empower clinicians, freeing them from the keyboard so they can focus on patients. That’s why we built Commure Ambient AI to go beyond basic note-taking and support every step of the patient journey.

As a trusted MEDITECH Alliance member since March 2025, we offer a deeply integrated, secure, and rapidly deployable solution that enhances Expanse workflows without disrupting how clinicians operate.

With our Expanse integration, notes flow seamlessly into patient records, no copy-paste required. And whether it's used in the ED, inpatient, or ambulatory settings, Commure Ambient AI delivers accurate, structured documentation in a fraction of the time, helping clinicians spend more moments where they matter most: with patients.

Workflow Highlights

1. Deep API Integration with Expanse EHR: Sync notes directly into Expanse workflows.
2. Autonomous Coding: AI generates CPT and ICD-10 codes from notes, reducing denials.
3. Rapid Patient Intake: Upload histories, generate summaries, and push them into the EHR.
4. Multi-Modal Functionality: Turn audio, images, and documents into structured clinical notes.
5. Multi-language Support: Translate multi-speaker conversations in 60+ languages.
6. Scalable, Modular Options: From self-service to specialist support, sized for any organization.
7. Enterprise-Grade Security: HIPAA-compliant encryption, role-based access, & 24/7 monitoring.
8. SSO & SCIM Provisioning: Integrate with existing authentication systems for secure access.

With Commure Ambient AI + MEDITECH Expanse, organizations can streamline every stage of the documentation journey, from intake to billing, while protecting clinician time and improving patient care.

Our Most Popular Features:

Clinical Nudges & Care Cues
‍Inline prompts help clinicians address compliance-related gaps (e.g., missing MDM statements, MIPS guidelines) or quality/HCC coding cues (e.g., “Provider should Monitor, Evaluate, Assess, or Treat the patient’s Type II Diabetes Mellitus with Neuropathy”).

Autonomous Coding
‍AI suggests appropriate CPT and ICD-10 codes based on encounter content. Alerts users to documentation gaps that could lead to undercoding or denials.

ED & Hospitalist Notetaking
‍Pre-visit summaries, note carry-forward, ambient note generation, dictation, discharge summaries, and patient assignment lists.

Some of our happy MEDITECH customers include:

How does the MEDITECH Expanse-Commure Ambient AI Integration Work?

Customers can leverage the MEDITECH Expanse Integration via Commure Ambient - available on mobile, web, and chrome extension as well directly embedded within the MEDITECH Expanse Now mobile app.

In Expanse, Clinicians begin by opening a PDOC template directly on their workstation. This initial step requires them to navigate through template options and select the appropriate documentation format for their specific encounter type. Once the template is selected, they proceed to capture the patient visit using Commure's Ambient AI technology. If there are 2 or more documents leveraged in the encounter, a third step involves choosing an existing PDOC template within the AI application itself. Finally once the note is generated, the last step enables editing the note, prior to syncing it to Expanse via APIs. In this step, the generated note appears with a distinctive Yellow Flag indicator in Expanse, allowing providers to review the AI drafted note before finalizing the documentation.

The Expanse Now mobile workflow takes a more straightforward approach. This pathway optimizes for speed over visibility and enables clinicians to maintain their existing Expanse Now workflows. Clinicians record their patient visit directly within the Expanse Now application environment, eliminating some of the desktop navigation requirements. The AI-generated note and recording automatically upload to Expanse via integration, without requiring preview or manual confirmation steps.

This trade-off delivers faster hand-offs between documentation and clinical care. While some clinicians prefer the streamlined approach, others prefer the opportunity to review and refine their documentation before it becomes part of a permanent medical record.

Integration Pathways

We offer a number of ways to connect with and integrate notes from Commure Ambient AI to MEDITECH Expanse.

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HL7 (Backend Integration)

• This pathway operates entirely behind the scenes, requiring no clinician-facing interface. Notes transcribed by Scribe flow into Expanse IDM and appear in the “Documents” tab of Expanse.

• HL7 is ideal for acute-care and ambulatory settings but is not suited to fast-paced ED workflows. The single-block structure preserves rich clinical sections while making structured data available..

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v2 API (Early-Access)

• The current v2 API requires that a PDOC document already exist, so a clinician must open or create that document before launching Scribe. It supports four primary sections—HPI, PE, ROS, and AP—though additional subsections can be mapped inside each.

• Because this interface is in early access, it requires MEDITECH approval, adherence to a deployment guide, and Expanse version 2.1.70 or 2.2.58.

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Colossus Selenium (Front-End Automation)

• Instead of an API, this option automates the Expanse UI through Selenium, mimicking a user typing directly into PDOC template fields. It enables far deeper, custom write-back than the v2 API but obliges the clinician to launch Scribe inside the EHR.

• Note that Colossus Selenium is unavailable for on-prem Expanse installations.

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Colossus DOM Injection (Chrome Extension)

• Similar to Selenium but faster, DOM Injection writes structured content straight into the browser’s Document Object Model. This method achieves the same field-level write-back as with Selenium.

• As with Selenium, it substantially surpasses API depth while remaining limited to cloud-hosted Expanse environments.

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MDS (Batch Upload Service)

• MDS functions as a back-end batch uploader that needs no user interaction with Expanse.

• While it reliably covers gaps the other methods cannot, uploads are slower and carry higher operational cost, making MDS the “last-mile” contingency for exceptional cases.

Development Roadmap

The V3 Expanse-Commure development roadmap maintains the familiar single-tap patient assignment, while improving the overall clinician experience. This ensures that the transition to the new API enhances rather than disrupts established workflows.

The core improvement centers on visit capture efficiency: clinicians will capture patient visits in the Commure App once, with the AI note uploading seamlessly through V3 endpoints. This eliminates redundant data entry and reduces the opportunity for transcription errors.

The most significant advancement will be full write-back capability to structured fields within Expanse, eliminating the copy-paste workflows. This enhancement will allow AI-generated content to populate discrete data fields automatically, from vital signs to assessment categories.

Additionally, V3 APIs will feature intelligent handling of edge cases, automatically resolving scenarios involving zero, one, or multiple existing documents per encounter. This automation eliminates the manual decision-making currently required in complex documentation scenarios.

V3 Rollout will follow a phased pilot approach, ensuring smooth adoption and maximum efficiency for MEDITECH + Commure users.

Note: While these V3 API enhancements represent our development roadmap, we have not finalized V3 upgrades at this time. Current integrations operate on the proven v2 API framework.

Concluding Thoughts

The Commure Ambient AI + MEDITECH Expanse integration is a bridge between clinicians and the data they need, exactly when they need it. By embedding Ambient AI capabilities directly into MEDITECH workflows, providers can eliminate manual note entry, streamline patient intake, accelerate coding, and maintain clinical accuracy without sacrificing face‑time with patients.

Looking ahead, our V3 API roadmap promises even deeper integration with full structured‑field write‑back, intelligent document handling, and faster, frictionless visit capture—all while maintaining the familiar workflows that clinicians already trust. Our continuous innovation ensures that no matter how care delivery evolves, Commure and MEDITECH customers will remain on the leading edge of efficiency, accuracy, and patient‑centered care.

With Commure Ambient AI and MEDITECH Expanse together, you’re not just transforming documentation, you’re transforming every step of the patient journey. Reach out to learn more.

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