Clinical Documentation Improvement: What It Is, Why It Matters, and How AI Is Reshaping It

The U.S. healthcare industry could save $20 billion a year by replacing manual administrative workflows with electronic ones, according to the latest CAQH Index. The same shift saves 70 minutes per patient visit.

That's the cost of the clipboard era. And for the first time, the technology to end it actually exists.

For two decades, "patient intake software" meant the same thing: take the paper forms, put them on a tablet. The clipboard got a screen, but patients still answered the same questions. Staff still re-keyed the same data, but eligibility still got checked somewhere downstream, usually by phone.

The clipboard didn't go away. It just got a software wrapper.

AI changes the assumption underneath all of it by replacing the workflows the form was built to support.

The clipboard era costs more than most health systems realize

Patient intake is one of the most measured workflows in healthcare and one of the least scrutinized. Most enterprise health systems track no-show rates, registration time, and front-end denials as separate metrics, but they rarely add them up.

When they do, the picture is consistent. The manual pre-visit experience bleeds revenue, staff hours, and patient trust at every step.

CAQH's 70-minutes-per-visit figure is the cumulative cost of staff calling patients to confirm appointments, re-verifying insurance by phone, fielding follow-up questions about pre-visit prep, and re-entering the same data into multiple systems. Multiply that across a health system's daily patient volume, and those minutes turn into a full-time staffing burden that grows with every new clinic and every new payer contract.

The patient side is worse. Patients show up to fill out the same forms they already completed online. They wait while staff verifies what should have been verified the week before. They leave with the impression that the most technologically advanced industry in the world can't remember their address from one visit to the next.

This is the gap modern patient intake software has to close.

What AI patient intake actually does

The shift is a redefinition of what patient intake software is responsible for.

In the clipboard era, intake software's job was to collect information at the front desk. In the AI era, the job is to manage the entire pre-visit experience. From the moment an appointment is scheduled to when the patient walks in already verified, prepared, and registered.

That broader definition matters because it changes what health systems are actually buying. A traditional intake product replaces the form. An AI-powered patient engagement platform replaces the workflow. The first reduces clicks. The second reduces phone calls, no-shows, denied claims, and the staff hours required to chase each one of them down.

In practice, AI-driven patient intake covers four overlapping capabilities:

• Automated, conversational outreach that confirms the appointment, gathers pre-visit information, and answers patient questions in plain language over SMS or voice. No portal, no app, no login.
  
  
• Intelligent referral intake that captures and tracks incoming referrals so patients don't fall through the cracks between schedule and visit.
  
  
• Personalized pre-procedure preparation that delivers the right instructions at the right time and flags patients who haven't completed them.
  
  
• Bi-directional messaging with intelligent triage that escalates urgent issues to a human and resolves the routine ones automatically.

Each of these used to be a separate vendor conversation. Now they're table stakes for a single platform.

Why the AI layer changes the economics

The most underappreciated thing about AI-driven patient intake is that in addition to reducing manual work, it changes which work is worth doing at all.

When pre-visit confirmation, prep, and information capture happen automatically through conversational AI, the marginal cost of engaging each patient drops close to zero. That unlocks workflows that health systems couldn't justify before. Multi-touchpoint reminders for complex procedures. Proactive outreach that meaningfully reduces no-shows. Bowel prep follow-ups for colonoscopies. Pre-op education for orthopedic patients. Behavioral health check-ins before the first visit.

The AI layer also reaches places the clipboard never could. Voice-based agents can capture patient information during inbound and outbound calls (which is still the channel where most patients engage with their health system). The same AI that confirms an appointment can spot a patient who needs to reschedule, triage a clinical question, or hand off to a human when escalation is warranted. Modern call center automation extends intake into a 24/7 capability.

The financial picture changes with it. The clipboard era measured intake as a cost center. The AI era measures it as a lever for access, throughput, denial prevention, and retention. The systems already operating this way are seeing the math play out. At Yale New Haven Health, pre-appointment AI texting drove a 54% reduction in no-show and cancellation rates for breast cancer screening alone.

What enterprise buyers should look for in 2026

The patient intake software market is in the middle of a category shift. The products that win the next decade won't be the products that won the last one.

A few principles separate the AI-era platforms from the legacy ones.

• Platform breadth over form depth. The right question is no longer how good the digital forms are. It's how much of the pre-visit experience the platform actually owns. A vendor that handles intake but not referral management, or messaging but not scheduling coordination, is selling only a piece of the workflow when health systems need the whole thing.
  
  
• Retrieval-based AI, not generative guessing. In healthcare, an AI that hallucinates a medication or a pre-op instruction is a safety event. Enterprise-grade patient intake AI has to be grounded in clinically validated content and deterministic logic.
  
  
• Deep EHR integration as table stakes. Patient data that enters the platform should land in the EHR in the right fields, without staff re-keying. Bi-directional integration with the major EHRs separates platforms that look modern from platforms that actually reduce work.
  
  
• Omnichannel by patient preference. SMS, RCS, voice, and email. Meeting patients on the channel they actually use, not the channel the vendor built first.

Health systems making this transition are replacing the entire pre-visit stack with one platform built for the AI era.

How Commure Engage approaches patient intake

Commure Engage is built for the shift from clipboard to AI. It combines automated patient outreach, conversational AI, referral and intake management, and personalized care pathways into one platform that owns the pre-visit experience end to end.

Engage uses retrieval-based AI grounded in over 500 clinically validated care pathways, integrates bi-directionally with all major EHRs, and reaches patients through SMS, RCS, voice, and email without requiring an app or portal login. Health systems using Engage resolve 80%+ of patient inquiries automatically through conversational workflows, increase outreach capacity by 6.5x, and cut no-shows by 54%.

The clipboard era is ending. The platforms replacing it are already in production.

See how Commure Engage is rebuilding patient intake for the AI era

We're excited to announce that Commure Ambient AI offers complete, end-to-end integration with Cerner, bringing ambient documentation directly into the workflows clinicians already rely on, with no context switching, no copy-paste, and no duplicate charting.

Documentation that meets clinicians where they work

Clinicians have spent too long absorbing the cost of fragmented documentation tools, toggling between systems, retyping notes, and losing precious face time with patients to administrative work. Commure Ambient closes that gap inside Cerner.

With this integration, patient context flows automatically from Cerner into Commure Ambient, and finished notes sync back exactly where they belong (into DynDoc components or PowerNote). Clinicians can then review, finalize, and sign directly in PowerChart.

A connected workflow, from waiting room to signed note

The integration is built around the way clinicians actually work:

• Select Patient — Choose from ambulatory appointments, the patient list, or walk-ins.
• Pre-Chart — View patient context and pre-visit summaries inside a DynDoc template or the Commure app.
• Record Visit — Ambient capture is tied to the specific encounter, with real-time transcription.
• Review Note — AI-generated, structured notes ready for provider review and edits.
• EHR Sync — Draft sections flow automatically into DynDoc components or PowerNote.
• Sign in Cerner — Finalize and sign directly in PowerChart, with no duplicate entry.

Personalized for every clinician, optimized for every care setting

Commure Ambient adapts to how each provider documents, at both the speciality and individual provider level. Teams can configure output by care setting, save edited notes as reusable templates, and control how prior notes carry forward across orthopaedics, psychiatry, internal medicine, GI, OB/GYN, cardiology, and more.

Whether you're documenting in inpatient and hospitalist settings, the emergency department, or ambulatory, Commure Ambient is purpose-built for the full hospital environment.

Trusted at scale

Commure Ambient is already in use at more than 2,000 sites of care and 135 of the largest health systems in the country, including HCA and Tenet. This Cerner integration extends that reach, bringing complete ambient AI documentation to even more clinicians, with the depth of integration that real clinical workflows demand.

Ready to see Commure Ambient in your Cerner environment?

Ask any nurse what they spend their shift doing, and documentation will land somewhere near the top of the list. A 2025 study published in JMIR Nursing found that nurses spend an average of 31% of a 12-hour shift documenting in flowsheets alone, and that's before accounting for narrative notes, handoffs, or the charting that spills over after a shift ends.

That number tells us something important: nursing documentation isn't a smaller version of physician documentation. It's a fundamentally different workflow challenge. And as ambient AI adoption moves from providers to nurses, the vendors, health systems, and clinical leaders who recognize that difference are the ones who will thrive.

We sat down with Kelum Fecht, Enterprise Sales Director at Commure and a nurse by training, to talk about what makes nursing documentation distinct, where ambient AI can move the needle, and what it actually takes to build a solution that works.

Documentation doesn't clock in and out

When a physician sees a patient, the documentation work is concentrated around a 20- to 30-minute encounter with some pre- and post-charting on either side. Nursing doesn't work that way.

"In a 12-hour shift, that burden is there constantly," Kelum told us. A nurse might be caring for up to nine patients at once, returning to each one repeatedly, fielding interruptions, and capturing information across hundreds of small interactions. The frequency is higher, the conversations are more varied, and the documentation lives in flowsheets, which Kelum describes as "an Excel spreadsheet with dropdowns, radial buttons, and free text", rather than narrative notes.

That structural difference is why bolting nursing onto an existing physician ambient AI tool doesn't work. And the cost of getting it wrong shows up in places that don't always make it into the ROI deck.

"When a nurse should be checking out at 7 p.m. after a 12-hour shift, if they're not done with documentation, they're often spending another 30 minutes to an hour after handoff going back in to make sure everything's charted, and that overtime is real dollars for healthcare organizations."

This documentation bottleneck quickly becomes a retention, safety, and margin problem all at once.

Why ambient AI for nursing and why now

Health systems have tried to solve nursing documentation before. Workstations on wheels, bedside computers, mobile devices; each one promised to bring documentation closer to the point of care, but none of them addressed the underlying tension.

"Patient comes first, patient first always. So even the nurses that are most routine at being able to pull up their computer, their workstation on wheels, or whatever technology platform they have, there is still always that burden of how do I document while I'm taking care of a patient."

Ambient AI is the first technology with a credible answer: capture the conversation, generate the documentation, and let the nurse keep their eyes on the patient. The biggest immediate wins, Kelum believes, are in shift handoffs (where critical context routinely gets lost between nurses) and in admission and shift assessments (where the structure of the interaction maps cleanly to what Ambient AI can capture).

There's also a second-order benefit that mirrors what we've seen on the physician side: when clinicians narrate their care out loud, patients get more information, and nurses surface details that would otherwise stay locked in their heads.

When we asked Kelum how ambient AI changes what it means to be a nurse over the next three to five years, his answer reframed the question:

"It doesn't change anything because it makes nursing what it's always meant to be. What we as nurses always learn is to care for the patient, understand the patient, and be an advisor to the patient. Ambient AI can only strengthen that because enabling nurses to spend more one-on-one time having conversations and having eye contact during their care, that's what nursing was a hundred years ago, before EMRs and all this technology was thrown in front of us."

The integration problem most vendors haven't solved

Generating a note from a recorded conversation has become table stakes. What hasn't is generating the right documentation in the right place inside the EHR, especially for nursing.

"Generating a note is easy. Generating a high-quality note is challenging."

Physician notes can often be written back through a handful of API fields. Nursing flowsheets are a different beast: structured grids, discrete data elements, and EHR-specific quirks. Any vendor serious about nursing ambient AI has to engineer for all of them and engineer it deeply enough that the integration holds up across shift changes, edge cases, and the realities of a 12-hour day.

That's why we're co-developing Commure's ambient AI for nursing alongside health systems rather than shipping a finished product and asking nurses to adapt. The workflows that matter are best designed with nurses at the table, not after the fact.

Beyond documentation

The same ambient layer that captures a conversation can power smart prompts, what we at Commure call CareCues (such as a reminder to follow up on a wound check), surface relevant orders a nurse hasn't seen yet (such as an MRI scheduled for a patient she's caring for), and automate communication between care team members who today rely on chasing each other down.

The throughline is the same one that drew Kelum to this work in the first place: give nurses back the time and attention that documentation has been quietly taking from them, and let them do the job they trained for.

Want to see what ambient AI for nursing looks like in your environment? Book a demo with the Commure Ambient AI team.

Clinical documentation is changing quickly, and Ambient AI is a big reason why. It is helping providers reduce manual work, ease documentation burden, and move through visits more efficiently. But even as that shift accelerates, one reality remains true: a sizable percentage of providers still rely on dictation, and for many of them, that workflow is deeply ingrained in how they practice medicine. 

Documentation should support how providers actually work

This is why I think the future of documentation has to account for how providers actually work today. Some clinicians are ready to fully embrace ambient workflows. Others want to dictate. Many will want both, depending on the visit, the setting, or simply personal preference. A modern documentation platform should support that full range.

The real opportunity is not choosing between dictation and ambient but bringing them together in a way that creates a more comprehensive experience. A provider might record a patient visit and let Ambient AI generate the first version of the note, then use dictation to add findings, make edits, or refine details for that encounter. In another case, a provider may skip recording altogether and dictate the note from start to finish. Both workflows should be supported in a comprehensive platform.

Having this flexibility matters because adoption does not happen in a vacuum. For some providers, moving from long-standing dictation habits to fully ambient documentation feels natural. For others, it feels like too much change all at once. Giving them access to dictation within the same broader platform lowers that barrier and lets organizations support more clinicians without forcing a one-size-fits-all transition.

AI can make dictation more valuable

This is also where AI starts to make documentation meaningfully better, even within dictation workflows. The value goes well beyond transcription. While a provider is dictating, AI can help choose the appropriate note template, automatically pull in relevant patient demographics, medical history, and lab data, reducing the amount of manual work needed to build a complete note. That saves time and helps the provider focus on the clinical thinking behind the encounter rather than the mechanics of documentation.

Over time, AI can help improve what is being documented, correct mistakes in real time, and connect providers to deeper intelligence while they work. For instance, a clinician could pause during dictation and ask an AI assistant a question about the patient’s history, get reminded of key details from a complex treatment course, or surface information that might otherwise require digging through the chart. In the right workflow, AI can also support clinical decision-making by helping providers quickly access evidence-based treatment recommendations in real time. The system could also help catch missing elements, identify documentation gaps, or prompt providers to include details that affect compliance, coding, and reimbursement.

 When dictation sits inside a connected AI platform, it becomes part of a smarter documentation ecosystem that can work alongside ambient capture, AI assistants, and downstream workflows in a way that standalone tools cannot.

The goal is a more complete path forward

I do think the industry will continue moving toward broader AI adoption in documentation. Over time, more providers will shift toward ambient workflows because they open the door to much more advanced capabilities. But that future will come faster if we acknowledge where clinicians are today and give them the tools that fit into real practice patterns right now.

The goal should be simple: give every provider a documentation experience that works for their specialty, their setting, and their workflow. When you do that, you are building a more complete path forward for clinical documentation. This is exactly what we offer at Commure by rolling out dictation directly inside our Ambient AI solution.

Oncology documentation is uniquely complex compared to other ambulatory specialties. Every visit draws on months or years of prior treatments, imaging, pathology, lab results, and evolving clinical decisions. Oncologists must synthesize dense patient histories, manage long treatment arcs, and coordinate across multidisciplinary teams, all while maintaining meaningful patient connections.

As oncology practices look to reduce the administrative burden of clinical documentation without sacrificing clinical rigor, Ambient AI is emerging as a critical foundation for modern cancer care. However, off-the-shelf AI documentation solutions aren’t set up to support the complexities of oncology.

Commure’s Ambient AI is already being used across a growing set of oncology environments, from community clinics to national enterprises, including practices within the US Oncology Network, Cardinal Health, City of Hope, and dozens of multi-specialty IDNs such as HCA Healthcare and TriHealth. 

Meeting the Complexity of Oncology Documentation

Ambient AI solutions have rapidly gained traction to help alleviate the administrative documentation burden facing oncologists, but not all solutions are ready for the complex oncology environment. Generic templates miss oncology-specific nuance and struggle to provide the same accuracy and conciseness of classic dictation.

Commure Ambient AI is built specifically for the realities of oncology care, where documentation depends on longitudinal context, precision, and preparation. It captures the full clinical dialogue, translating it into structured, consistent documentation that supports continuity across the entire cancer care journey.

The platform integrates with major EHRs and connects oncology data with Ontada McKesson and Onco EMR, enabling intelligent documentation that provides a seamless provider and patient experience.

Key oncology capabilities include:

• Flexible automation for all levels of complexity: Supports both fully autonomous Ambient AI and the human-assisted Ambient experience, allowing practices to match documentation support to visit complexity and clinician preference.
  
  
• Sub-specialty specific templates: Designed for medical, hematology, radiation, and surgical oncology workflows, these templates capture staging, treatment planning, toxicity assessments, response evaluations, and survivorship care.
  
  
• Ambient CareCues grounded in oncology best practices: Context-aware prompts that surface documentation gaps, lab interpretations, and follow-up needs at the point of care, grounded in clinical guidelines and shown only when relevant.
  
  
• Previsit Summaries: Generates concise, oncology-specific summaries ahead of the encounter, surfacing relevant history, treatment milestones, recent labs and imaging, and other key clinical context to help clinicians prepare more efficiently.
  
  
• Clinical Intelligence layer: Maintains a working memory of the patient’s oncology history, enabling Ambient AI to generate more informed, consistent documentation as care evolves.
  
  
• Autonomous Coding (in development): Automatically translates oncology documentation into accurate, compliant codes by accounting for staging, treatment complexity, toxicity grading, and longitudinal care context.

Together, these capabilities support clinicians before the visit with assembled patient context, during the visit with captured conversations, and after the visit with complete, consistent notes that carry forward across the patient’s care journey.

Proven Momentum Across Oncology

As oncology practices continue to evolve, Ambient AI is becoming a foundational layer that helps clinicians focus less on documentation and more on delivering high-quality, compassionate cancer care. It underscores a broader shift within oncology toward intelligent automation that supports clinicians without disrupting care delivery.

Ready to see what Commure Ambient AI would look like in your oncology workflows?
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Schedule a Demo

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

Outside of the office, I’m an avid traveler with a goal to visit every state in the US (I’ve checked 10 states off the list so far!). I’m also a big motorsports fan and a self-proclaimed foodie who loves exploring new restaurants.

Photography is another passion of mine. I love capturing the essence of the places I visit. My ultimate goal is to curate a "travel wall" in my home, filled with physical prints of the moments and landscapes I’ve encountered on the road. It keeps me inspired and reminds me how big the world really is.

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

I’ve always been fascinated by how technology can be a lever to improve lives. I was definitely the "tech kid"; I actually built my first website back in 2012 using an early website builder. Even then, I knew I wanted to build tools that solved problems, though I didn’t yet realize those tools would eventually help clinicians and patients.

Describe a day in the life of your role.

As a Tech Lead, my role is a blend of high-level strategy and deep technical execution. I lead product roadmaps for major features, but I’m still very much "in the trenches" with my team.

On any given day, I might be "heads-down" tackling a complex feature or architecting base frameworks that allow other engineers to scale their work. I also spend a significant amount of time reviewing code and collaborating on technical designs with other teams. The goal is always the same: build cleaner, faster, and more intuitive software so that our users can spend less time on software and more time doing what they do best, providing care.

What made you decide to join Commure?

Commure sits at the perfect intersection of cutting-edge tech and meaningful impact. The realization that the code we write directly improves a patient’s experience is a massive daily motivator.

I was also drawn to the culture of extreme ownership. At Commure, engineers don’t just "write code"—they own the entire feature. We collaborate directly with Product, Operations, and Design to ensure we are building the best possible product for the healthcare industry.

How would you describe the Commure company culture?

Commure moves at an incredible pace. We are focused on getting things done the right way, as quickly as possible. What makes that work is our blameless culture. In a high-velocity environment, mistakes can happen, but at Commure, those moments are treated as collective learning opportunities rather than failures.

It’s also an incredible place for career growth. The hands-on experience here is unparalleled. I’m constantly learning, not just from our brilliant engineering team, but from leaders across the company who are absolute experts in their respective fields.

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

Just soak it in! Healthcare is an incredibly complex domain with layers of regulation and intricate workflows. My best advice is to never be afraid to ask "why." No question is too small, and curiosity is the fastest way to get up to speed in an environment that moves as fast as ours.

What has been your greatest accomplishment so far at Commure?

Watching the evolution of Athelas Air has been incredibly rewarding. We’ve scaled from a single customer to over 75 practices across 20+ states.

I’m also particularly proud of our work on the Commure Prescriptions engine. Many thought it was impossible to go live so quickly, given the regulatory hurdles, especially for controlled substances. However, by deeply immersing ourselves in the compliance requirements and leveraging our existing internal systems, we built a robust, successful product in record time. Seeing it live and in the hands of clinicians today is a huge win for the team.
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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

At the HIMSS session, “Expanding Patient Access and Reducing Costs with Interoperable AI Agents,” featuring Optimus Health Care and Commure, one theme emerged clearly: healthcare organizations are reaching a breaking point with administrative capacity.

Patient demand continues to rise, but staffing levels for call centers have struggled to keep pace, with a 35% annual turnover rate. The result is familiar across the industry: missed calls, long hold times, and administrative teams overwhelmed by routine requests.

The session explored how a new generation of AI-powered agents can scale call center capacity and improve access to care. Rather than simply routing calls or providing static chatbot responses, Commure’s Call Center Agents, part of Commure Engage, are designed to actively manage patient interactions, resolve common requests, and escalate complex situations when human attention is required. The goal is to improve patient access and experience without expanding staff.

Call Center Agents in Action

The session opened with a live demonstration of how Call Center Agents manage inbound patient calls in real time. The AI agent answers immediately, identifies the patient’s need, and guides the interaction to resolution—handling appointment scheduling, patient intake, department routing, and common questions through natural, conversational responses.

Rather than replacing staff, the agent resolves routine requests upfront, allowing teams to focus on cases that require human judgment and coordination. It can also respond to emotional cues, acknowledging frustration or discomfort, and is configurable to reflect each organization’s workflows and preferences.

The result is straightforward: calls are answered instantly, routine needs are handled without delay, and staff remain available for more complex patient interactions.

Optimus Health Care’s Perspective

For Optimus, improving patient access and operational efficiency has been a major priority. Gary Avery, Senior Director at Optimus, described the challenges many organizations face in managing high volumes of inbound patient communication.

“If patients are unhappy with long wait times and high abandonment rates, it pushes them to find another service provider.”

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Research data supports this, with 60% of patients abandoning their call after more than one minute on hold, meaning answers regarding their health or next steps on care get delayed. Often, patients must make multiple calls to address a single issue.

As Gary explained, traditional call center models often struggle to keep up with peak demand. When call volume spikes, staff members are forced into a reactive posture, handling repetitive inquiries while more complex patient needs compete for attention.

AI agents offer a different model. By automating routine interactions, organizations can maintain responsiveness even during peak demand.

While earlier on in their deployment of Agents, Optimus will measure success by looking at improvements in:

• Patient satisfaction scores and feedback
• Call abandonment rates
• Scheduling and fill rates

“In order for us to continue our mission as an FQHC, we absolutely have to have patients come through our doors.”

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Gary emphasized that successful AI deployment requires early involvement from a broad group of stakeholders—including front office registrars, practice managers, clinical teams, IT teams, and operational leadership—to ensure the solution reflects real workflows, incorporates staff needs, and minimizes implementation issues.

The Impact of Call Center Agents

The operational impact of AI agents becomes particularly clear when applied at scale.

Across customer deployments using Commure Agents, organizations have observed significant improvements in how patient calls are handled. Agents provide 24/7 coverage, ensuring calls are answered even outside normal office hours. 

For healthcare organizations managing large call volumes, this can translate into meaningful operational efficiency. Observed customer performance indicate:

• 800 labor hours saved per 10,000 calls handled
• $240,000 in annual labor savings at same volume
• 30-80% of inbound calls can be resolved without staff intervention, depending on workflow design 

A New Layer of Healthcare Operations

The session underscored an emerging shift in how healthcare organizations think about AI. For years, much of the focus has been on clinical documentation or analytics. But AI agents represent something different: operational intelligence applied directly to the front door of care delivery. By answering calls, resolving routine requests, and routing patients efficiently, agents can extend the capacity of administrative teams while improving the patient experience.

For organizations struggling with patient access and administrative workload, the emergence of AI agents may represent one of the most practical tools available today to solve one of healthcare’s most persistent operational challenges.

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

‍Gautam Pradeep, Senior Software Engineer (BS Computer Science & Master's in Management Science & Engineering): I cared about healthcare, and I had worked in this field before. Everyone I spoke to about Commure emphasized how the culture fuels you to learn, grow, and become a stronger version of yourself every day. I was motivated by a challenge and was excited to dive deep into the field. I was also very excited about an in-person culture as my first full-time job.

Sabina Aliev, Senior Manager, Implementation (Master's in Community Health and Preventive Research): I knew I wanted to work in healthcare as I’d seen the inefficiencies in the system firsthand, and those were the problems I wanted to help solve. What drew me to Commure was that the vision felt bigger. It wasn’t about fixing one narrow issue, but building an ecosystem to tackle healthcare inefficiencies from multiple angles. That felt ambitious in the right way. Ownership was also a big factor. I kept hearing that you’re not boxed into one function. You collaborate across teams, shape product and process, and actually own things end to end. It felt like a place where I could have a real impact pretty quickly.

Luke Pattan, Vice President, GTM Ops (Master's in Business Administration): I chose Commure because of the opportunity to have a much broader impact in healthcare through software. In my previous roles at companies like Capsule and Charlie Health, impact was often constrained by human capacity—whether that was filling prescriptions or delivering therapy sessions. With software, you can scale improvements across thousands of providers and patients simultaneously. Commure stood out as a company where those scaling dynamics were already taking hold. It felt like a chance to apply my background while operating in a much higher-leverage environment.

How did Stanford prepare you for working at Commure?

Gautam: I was used to the idea of wearing many hats and taking on whatever roles I needed to. Whether that was a heads-down engineer, talking to customers, or interviewing fellow potential colleagues. Stanford has a strong culture of building well-rounded people. I think being able to tackle challenges across the stack and becoming comfortable being thrown into unfamiliar territories is an advantageous skill.

Sabina: Stanford taught me to look at problems from all sides. We were constantly asking: What are we actually trying to solve? Who are the stakeholders? What incentives are driving behavior? What are the second-order effects? I learned to think in systems, not in silos, and to get comfortable with messy, multifaceted problems. I also did my thesis in partnership with Omada Health, which gave me early exposure to how technology can solve real healthcare challenges. That connection between systems thinking and real-world innovation stuck with me.

Luke: Stanford prepared me by immersing me in the intensity and ambition of Silicon Valley. It gave me firsthand exposure to world-class operators, engineers, and investors, many of whom reflect the same mindset you see at Commure. The GSB ethos – “change lives, change organizations, change the world” – maps closely to what Commure is trying to achieve in healthcare. I also developed a strong foundation in managing and scaling teams, which has been directly applicable. Just as importantly, it taught me how to operate in fast-paced, high-expectation environments with a bunch of people who’re way smarter than you!

What is something you are really proud of accomplishing?

Gautam: I built out a new feature that unlocked a lot of market potential for Scribe that allows clinics with multiple doctors and multiple MAs, PAs, and medical scribes to integrate the app into their workflows collaboratively. It took a lot of scoping, cross-team communication, and speed – without compromising quality. Have seen a lot of doctors use it and enjoy the flexibility it has provided to their workflow 

Sabina: The discovery work I’ve done onsite with clients and the early testing has helped shape our product. Spending time in the field, observing workflows, and gathering real provider feedback has allowed me to surface needs in a tangible way. Features like macros, CareCues, and carry forward all came from listening closely to customers and bringing those insights back to our product and engineering team. 

Luke: I’m particularly proud of the team we’ve built within GTM Operations. Watching early-career team members take on larger responsibilities and grow into leaders has been incredibly fulfilling. I’ve also operationalized and up-leveled key functions like RevOps and Enablement, and built a Marketing function (including branding, events, and digital growth) from scratch. Seeing those systems drive quota and team performance has been a major milestone. It’s been exciting to build something foundational that the company can continue to scale on.

What’s something you love about your team that has nothing to do with work?

Gautam: They are all so down-to-earth and kind. I have 1:1 relationships with each team member. Coming in with that looming dread of parting ways with all your college friends, I genuinely felt welcomed and a strong sense of community.

Sabina: Honestly, everyone just really cares. People get genuinely excited about the impact we’re having on providers, and that energy is contagious. The team is just full of really good humans. Everyone is helpful, low ego, and easy to talk to.

Luke: One thing I love is how strong the New York City presence is on the team. It brings a unique energy – people are driven, scrappy, and know how to work hard. There’s also a shared appreciation for enjoying time together outside of work, whether that’s dinners or nights out. That balance of intensity and camaraderie makes the team special. It creates a culture that’s both high-performing and genuinely fun.

‍What would you tell another Stanford student considering Commure today?

‍Gautam: If you like to learn, work hard, and make a real-world impact - come join. Many companies like to flaunt that they are impactful, but seeing doctors get hours of their day back to be with their families makes all the work worth it. It’s one thing to hear about social impact from inside the company or an elite school. It’s another thing to hear it directly from the real people bearing the fruits of your labor.

Sabina: If you care about healthcare and want real ownership early on, this is a great place to be. You won’t be stuck in a tiny corner of a big machine. You’ll be close to the product, the customers, and the decisions. It’s fast-paced and sometimes messy, but you’ll learn a lot, quickly. If that excites you more than having everything perfectly structured, it’s a really fun place to grow.

Luke: I’d tell them that Commure is a place where performance and impact truly matter. It’s a no-nonsense environment where success comes from delivering real results for customers. If you’re excited by hard work, it’s an incredible place to grow quickly. You’ll be pushed outside your comfort zone, but that’s where opportunity lies. For someone who wants to build, learn fast, and make a tangible impact, it’s a great fit.