Tuesday, June 9, 2026

< + > Integration Into the Workflow Is Key to Ambient Scribe Success

The first year that Central Oklahoma Family Medical Center deployed the Sunoh.ai ambient transcription software, it was getting very little use and therefore wasn’t achieving their goals for installing it. To address this lack of adoption, Liz Massey, Executive Vice President of Clinical Operations, was put in charge of integrating it into their practice. In a recent interview with Massey, she explains what her team did and how Sunoh.ai  has transformed the organization. One doctor even said it “gave her back her life.”

Central Oklahoma Family Medical Center has 22 locations serving 30,000 patients, mostly offering primary care but also having multiple specialties. The burden of writing clinical notes was leading to burn-out. One key step taken by the center, when choosing Sunoh.ai, was to define their goals: to capture the quality measures needed for regulatory and financial purposes, to increase the percentage of records closed within 24 hours of a visit, to reduce the time spent on documentation after-hours, and to increase the number of patient visits.

They preferred Sunoh.ai over other ambient solutions because it integrated well with their EHR. But as Massey and her team discovered, integrating the solution into the doctors’ everyday practice was crucial too.

In order to address this, they sat with doctors doing role-plays and offering suggestions on how to do things differently next time with a patient in order to make the most of the ambient scribe. They also set up a chat on Microsoft Teams that included the onboard consultant from Sunoh.ai to make sure clinicians got all their questions answered and knew how to best utilize the tool. Eventually, some doctors started answering other doctors’ questions, becoming physician champions “whether they realized it or not.”

In the third year of using Sunoh.ai over 14,000 records were created using Sunoh.ai, and they are on pace for even higher this year. Primary care physicians were the first to be introduced to it and caught on really quickly. But they have rolled the tool out as well to specialties, who have more complex visits.

Massey recommends that doctors record the interviews on a tablet instead of a desktop or laptop, so that the device is less intrusive. While patients can see the device, they seem to forget that it’s there.

Check out our interview with Central Oklahoma Family Medical Center about their experience adopting the Sunoh.ai medical scribe in their organization.

Learn more about Central Oklahoma Family Medical Center: https://www.cofmc.com/

Learn more about eCW: https://www.eclinicalworks.com/

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< + > The Emerging Role of AI Platforms in Healthcare Delivery: What Healthcare Leaders Need to Know

The following is a guest article by Ashutosh Kavathekar, Global Head – Healthcare at Apexon

The healthcare industry crossed a threshold this year. A recent Elsevier report shows that more than 40% of clinicians in India are now using AI technologies in their work, a significant increase from 12% the previous year. This adoption rate surpasses both the global average of 48% and rates in the US (36%) and the UK (34%).

With the launch of ChatGPT Health by OpenAI and Claude for Healthcare by Anthropic in January 2026, artificial intelligence moved from the background of healthcare operations to the front door of patient engagement. These are not incremental product releases. They introduce consumer-facing AI health assistants designed with enterprise-grade security, clinical oversight, and direct access to personal health data.

For healthcare organizations, the implications are immediate. AI is no longer limited to back-office automation or isolated innovation pilots. It is rapidly becoming the primary way patients interpret their health, prepare for clinical encounters, and navigate an increasingly complex healthcare system.

What This Upgrade Means for Healthcare Organizations

The Rise of the AI-Prepared Patient

Patients have already turned to general-purpose AI to ask health questions, interpret lab results, and explore treatment options. What changes now is scale and credibility. Purpose-built healthcare versions allow AI to synthesize insights directly from structured health records, claims data, and longitudinal histories.

Clinicians will increasingly see patients arrive with AI-generated summaries, interpretations of recent tests, and focused questions. This reshapes the exam room dynamic. Used well, it can streamline history-taking and elevate clinical conversations. Used poorly, it risks confusion, misinterpretation, and unrealistic expectations.

Health systems must prepare clinicians to engage confidently with AI-informed patients—leveraging AI-generated insights without surrendering clinical judgment or increasing liability. This is as much a training and change-management challenge as it is a technology one.

Administrative Tasks are Being Automated

Both ChatGPT Health and Claude for Healthcare take aim at one of healthcare’s largest cost drivers: administrative complexity. From benefits navigation and prior authorizations to claims and coding workflows, AI is increasingly capable of automating work that has long depended on manual effort and specialized expertise.

As a result, AI-assisted administrative workflows are quickly becoming table stakes rather than differentiators. Organizations that continue to rely on manual, exception-heavy revenue cycle processes will face growing and hard-to-reverse cost disadvantages. The question for payers and providers is no longer whether AI can reduce administrative burden, but how quickly it can be deployed at scale without compromising compliance or clinician trust.

Data Privacy and Trust are Critical

A defining feature of these platforms is their focus on data governance, including HIPAA-ready infrastructure, strict data separation, and clear policies that prevent health conversations from being used to train models. Users retain control and can revoke data access at any time.

This reshapes trust. Patients may come to view external AI platforms as more transparent and controllable than traditional provider portals—a warning signal for healthcare organizations. Compliance alone is no longer sufficient. Trust must be visible and patient-facing, or organizations risk losing credibility at their own digital front doors.

AI Disrupting Patient Portals and Systems 

The most significant strategic implication of these launches is platform displacement. As patients increasingly turn to AI assistants for health guidance, traditional patient portals, care navigation apps, and call centers risk being bypassed. In this shift, Electronic Health Records (EHRs) face the danger of being relegated to back-end systems of record, rather than evolving as platforms that enable meaningful patient engagement.

For technology leaders, this moment presents a defining choice: lead by orchestrating AI-driven experiences, or risk becoming a commoditized data layer within someone else’s platform. This decision will shape digital strategy for years to come.

Embedding AI Throughout the Operating Model – Role of Healthcare Providers

Responding effectively requires more than deploying tools or running pilots. AI must be treated as a shared enterprise layer, integrated across clinical, financial, and operational workflows. Governance models must satisfy compliance teams while earning the trust of clinicians who rely on the outputs in real time.

Incremental automation is not enough. Organizations must redesign workflows so AI prepares context before encounters, supports clinicians during interactions, and reduces cognitive load rather than adding alerts and noise. Tech leaders who engage experienced service providers accelerate time-to-value by 6-12 months, avoiding fragmented pilots and compliance pitfalls.This is not a technology decision. It is an operating model decision that requires executive ownership, clinical alignment, and sustained investment beyond innovation budgets. Architecture decisions, workflow integration, and governance models made in the first twelve months will determine whether AI reduces friction or simply adds another layer of complexity.

AI’s Role in Chronic and Long-Term Care

In long-term care and chronic disease management, AI assistants will evolve into persistent care companions. By continuously synthesizing EHR data, remote monitoring signals, medication adherence, and patient-reported outcomes, AI can surface early risk indicators and prompt timely interventions.

This enables earlier detection of deterioration, fewer avoidable hospitalizations, and better outcomes—without linear increases in staffing. For payers, this bends cost curves through prevention. For providers, it enables more personalized, proactive care at scale.

At the same time, EHR systems themselves will be modernized. Historically optimized for documentation and billing, they will evolve into AI-enabled platforms that surface next-best actions, flag reimbursement risks, and highlight operational bottlenecks in real time. The EHR transitions from a passive system of record into an active participant in care delivery.

The Choice Ahead

With the launch of ChatGPT Health and Claude for Healthcare, AI has moved from the margins of healthcare IT to its center. It will define how patients engage with care and how clinicians deliver it.

Participation is inevitable. Leadership is not. Organizations that act now will shape the future of care. Those that wait will inherit it.



< + > Trusted by Leading Cancer Centers to Solve Oncology’s Information Overload, Triomics Raises $22 Million to Accelerate Adoption

Led by Battery Ventures, the Round Will Scale Triomics’ AI Platform Across Cancer Centers Nationwide and Deepen Life Sciences Partnerships

Triomics, an oncology AI company helping cancer centers operationalize complex clinical information, today announced it has raised $22 million in Series B financing led by Battery Ventures, with participation from existing investors Nexus Venture Partners, Lightspeed, and Y Combinator, alongside strategic backers Oncology Ventures and Precision Health Informatics, a wholly-owned subsidiary of Texas Oncology. This round brings Triomics’ total funding raised to date to more than $36 million.

The new capital will be used to accelerate adoption across health systems, oncology networks, and life sciences organizations; grow Triomics’ AI/engineering and forward-deployed teams; and advance the company’s AI agents for clinical care and research. Triomics is already working with leading cancer centers like Memorial Sloan Kettering Cancer Center (MSK), MD Anderson, Yale Cancer Center, and its partner Smilow Cancer Hospital, and Mount Sinai Tisch Cancer Center, as well as some of the nation’s largest community oncology practices, such as Texas Oncology.

“Oncology faces an information burden at a scale legacy systems were never designed to handle, and that burden can stand in the way of better outcomes,” said Sarim Khan, Co-Founder and CEO at Triomics. “Clinicians, research coordinators, and medical assistants are working against records that have become too large and too dynamic to process manually. We built Triomics to turn that complexity into usable intelligence inside the workflow, purpose-built for oncology. This financing allows us to bring that infrastructure to many more cancer centers and improve care for cancer patients.”

Beyond provider workflows, Triomics has built a broader oncology network that helps life sciences organizations with their critical clinical-trial operations. The company believes the combination of deep provider workflow integration across cancer centers, combined with oncology-specific AI infrastructure, creates a durable foundation for the next generation of care and research applications.

Transforming Oncology’s Data Overload into Actionable Intelligence

Cancer care is no longer constrained by a lack of information; it’s limited by the ability to use the data that already exists. A single patient history can span hundreds of narrative-heavy clinic notes, pathology and radiology reports, biomarker results, outside records, prior treatments, and ever-evolving trial criteria and guidelines. Yet the workflows required to make that information usable have remained overwhelmingly manual.

“Oncology is the hardest place to build AI, yet the most important,” said Hrituraj Singh, Co-Founder and CTO at Triomics. “Getting a model to reason reliably across thousands of pages of notes, pathology, imaging, and evolving trial criteria, and show its work, is what separates a demo from software that clinicians actually use. We’ve spent four years building that foundation and this round lets us push even further.”

Founded in 2021 by Khan and Singh, Triomics is building a platform that uses AI agents to read the full longitudinal patient record and convert unstructured information into structured, explainable outputs. Then, it delivers those insights directly into clinical and operational workflows. Unlike lightweight summarization tools, every output is source-backed and verifiable inside the clinician’s workflow. The platform supports proactive clinical trial matching, pre-visit chart review and preparation, and oncology data abstraction for registry, quality improvement, and operational use cases.

Cancer centers rely on Triomics to expand trial access, reduce the burden of manual chart review, improve visit preparation, and generate higher‑quality structured data for research and operations. Published results show that users of the company’s product have increased trial matches by 40% and trial enrollments by more than 30%, while also reducing chart review times by 67%. The platform has received peer-review validation in Nature Digital Medicine and was presented at ASCO, underscoring growing demand for AI that can operate reliably on the full patient record.

“We are excited to partner with Triomics, our selected solution for oncology clinical trial matching, to extend our collaboration to an AI-enabled method for cancer registry abstraction and reporting. This activity is labor-intensive, subjective, and challenging to complete in a timely manner. Our goal is to produce autonomous chart abstraction of clinical registry quality that can be rapidly reviewed and finalized for reporting by human registrars to comply with mandatory state, federal, and professional society reporting obligations,” said Lee Schwamm, MD, Chief Digital Health Officer at Yale New Haven Health System, and Associate Dean, Digital Strategy & Transformation at Yale School of Medicine.

“Triomics built what oncology has always needed: AI infrastructure that actually works on the full patient record,” said Brandon Gleklen, Principal at Battery Ventures, who is joining the Triomics Board of Directors. “We are live at some of the top cancer centers and demonstrating measurable outcomes—faster enrollment, less manual chart review—and the same underlying AI infrastructure already powers multiple distinct workflows with no redundant integrations. That kind of platform leverage, inside a customer base this strong, is rare at this stage.”

About Triomics

Triomics is an oncology AI company building the infrastructure that turns complex, longitudinal cancer records into structured, explainable intelligence. The company’s platform supports patient trial matching, pre-visit chart prep, and oncology data abstraction, helping care teams, research teams, and health systems act faster on the information already in the chart. Headquartered in New York, Triomics is backed by Battery Ventures, Lightspeed, Nexus Venture Partners, Y Combinator, and Oncology Ventures. For more information, visit triomics.com.

Originally announced May 28th, 2026



Monday, June 8, 2026

< + > The Role of Technology in Addressing Health Equity, Accessibility, and Digital Literacy Among Diverse Patient Populations

When we talk about improving healthcare, there are many, many different avenues and aspects to work on. Despite the method, the goal is always to make sure people have safe and reliable access to healthcare that they can understand. And more often than not, technology plays a huge role. To get a better understanding of this topic, we reached out to our brilliant Healthcare IT Today Community to ask — what role does technology play in addressing health equity, accessibility, and digital literacy among diverse patient populations? The following are their answers.

Payam Zamani, MD, Founder and CEO at MY DR NOW
Technology should not add complexity to healthcare, it should remove it.

The biggest issue in primary care today is access, and that disproportionately affects underserved populations. If patients cannot get care when they need it, nothing else matters. Technology plays a critical role, but only when it is used to expand access, simplify the experience, and meet patients where they are.

That means designing care around how people actually live. Not everyone can navigate complex digital tools, take time off work, or travel long distances. An effective model uses technology to support multiple access points, whether that is in the clinic, virtually, or in the home, so patients can receive care in a way that works for them.

Equity is not achieved through more tools alone. It is achieved through better access, with technology serving to enable it. When technology is applied correctly, it removes barriers, builds trust, and ensures that high-quality primary care is available to everyone—not just those who can navigate the system.

Morris Panner, President at Intelerad, A GE HealthCare Company
Technology can either widen healthcare gaps or help close them. The difference comes down to how intentionally it’s designed and implemented. The biggest barrier for many patients isn’t access to care itself but access to the information needed to participate in their care. Imaging results, diagnostic reports, and follow-up instructions are often scattered across systems that aren’t designed with patients in mind, but health technology can simplify that experience and improve equity.

Platforms that unify imaging data and care records make it easier for providers to share results across facilities and teams, which reduces delays and ensures patients aren’t asked to repeat tests simply because data wasn’t accessible.

Usability is equally important. Systems should support multilingual access, mobile-friendly design, and clear explanations of clinical information so patients with different levels of digital literacy can understand what their results mean. Technology should remove friction from the care journey. Data that flows smoothly between providers — offering patients easy access to information they can understand — naturally makes healthcare more equitable.

Cameron Behar, Co-Founder and CTO at Sprinter Health
For decades, healthcare has operated on a necessary compromise: standardization in exchange for scale. Stock messages, uniform workflows, and averaged assumptions about patient needs, constraints, and preferences worked for most, but not all. Accounting for an individual’s unique circumstances was too slow and expensive. But the promise of modern AI isn’t just automation; it’s the end of that tradeoff.

Given clear goals and the right primitives, agentic systems can reason through novel patient situations without a specific feature having been built for them. They can learn context directly from patients through conversation, sidestepping the digital literacy barriers that traditional interfaces impose, and incorporate that context into care workflows in real time. The populations with the most complex, nonstandard circumstances no longer have to wait for their needs to make the product roadmap. Contextual intelligence offers the opportunity to turn good intentions around equity into operational reality.

Chris Santas, General Manager, Price Transparency and Search at MacroHealth
Can you imagine buying products on Amazon without knowing the prices? That is how most care is purchased today in the U.S. A patient goes to a clinic, a doctor’s office, or a hospital, and may check reviews, but there are usually few options to see the price of the care they’re about to receive. That’s changing. Health IT solutions are using mandated healthcare price-transparency data from health systems not only to optimize costs for health plans but also to share that data directly with patients. Healthcare is expensive. And any window into understanding the cost of care before making a healthcare decision improves the patient experience while also forcing the industry to adopt more streamlined, affordable pricing.

Jeanne Cohen, CEO at Motive Medical Intelligence
After 20 years of value-based care, it’s time to deliver on its promise, and technology and innovation are aiding progress. Patient experience and cost efficiency are not competing priorities — they are the same goal. By equipping clinicians with real-time, data-driven insights and a shared, standardized view of what ‘appropriateness care’ looks like, we can reduce unnecessary variation, eliminate waste, and ensure patients get the right care at the right time. That’s what patients feel: fewer delays, clearer communication, and care that actually makes sense — along with the confidence to take a more active role in their health. Technology is the catalyst, but the outcome is a system that is simpler to navigate, more consistent, and truly centered on the patient.

Karin Hayes, Senior Vice President, Analytics Products and Services at OptimizeRx
As healthcare becomes increasingly digital, disparities in digital literacy, device access, and connectivity risk leaving certain populations behind, creating a gap between what treatments are available and what patients can access. Nowhere is this more true than in accessing life-saving therapies.

For life sciences marketers, effective strategies to address these disparities go beyond broad assumptions to understand how specific patient populations engage with health information, what motivates them to act, what barriers they face, and the channels they prefer. This allows organizations to deliver more targeted, actionable communication through the patient journey. Technology is accelerating this shift and helping life sciences organizations close critical gaps in care.

For example, predictive analytics can anticipate future patient milestones to activate more personalized communications across both clinical workflows and digital channels. These timely, relevant communications can motivate patients to act sooner and help ensure prescribers are informed and prepared to treat. This coordinated approach drives more meaningful patient action, strengthens clinical readiness, and ultimately leads to improved engagement and better outcomes across diverse populations.

Eric Makovskey, EVP, Solutions at Tendo
One of the biggest barriers to equitable care is that health systems often lack visibility into where access challenges exist across different patient populations. Technology can help close that gap by bringing together data that highlights disparities in access, engagement, and outcomes. When organizations can identify where patients face barriers—whether related to geography, language, or socioeconomic factors—they can take more targeted action to improve access and support. The goal is not just to digitize healthcare, but to ensure that technology helps health systems reach patients more effectively and deliver care in ways that are accessible and inclusive.

Gokul Mohan, CEO at CareHarmony
Technology has a real opportunity to improve health equity, but only if it’s designed with the realities of diverse patient populations in mind. One of the biggest risks is relying on a one-size-fits-all approach, where digital tools assume every patient has the same access, preferences, or level of support. That kind of “cookie-cutter” care can actually widen gaps instead of closing them.

One of the most important roles technology plays is enabling more personalized, context-aware care. By incorporating social determinants of health alongside clinical and claims data, organizations can better understand the full picture of each patient. This allows care teams to tailor interventions based on individual needs, whether that means adjusting outreach methods, addressing barriers like transportation or food access, or aligning care plans with a patient’s environment and resources.

At the same time, technology alone isn’t enough. The most effective models combine data-driven insights with human care teams and flexible communication channels, so patients can engage in ways that work for them. This shift away from standardized care toward more tailored, patient-specific support is what ultimately drives more equitable outcomes. When done well, technology helps deliver the right care, in the right way, for each individual patient.

Lauren Barca, VP of Quality at 86Borders
Technology does its part in expanding access to care, especially for those patients who are harder to reach, but it can’t do it on its own. Many patients face challenges that go beyond healthcare, including transportation, housing, and language barriers. Supporting equity requires more than deploying new tools. Solutions need to be simple and easy to use, and they need to account for different levels of digital comfort. Technology can help identify needs and connect patients to resources, but real progress depends on meeting people where they are and making sure no one is left trying to figure it out alone.

Chandra Osborn, Chief Experience Officer at AdhereHealth
Technology can help close equity gaps, but only if it’s designed around how people actually live, not just how healthcare systems operate.

Forward-looking health IT solutions are using AI and behavioral insights to tailor communication based on language, preferences, and access to technology. That means meeting patients on the channels they’re comfortable with, simplifying complex health information, and identifying when someone may need more personalized support.

Importantly, technology should help care teams focus their attention where it’s needed most. By identifying patients who may be struggling – whether due to social barriers, affordability issues, or digital literacy challenges – health IT can ensure that human support is directed to the people who need it most.

Raj Ramaswamy, Chief Technology Officer at Buzz Health
Technology improves health equity when it surfaces actionable prescription options at the moment decisions are made—especially for patients navigating cost barriers, coverage confusion, or pharmacy variability. Advancing health equity isn’t just about access to care—it’s about access to understanding. Technology must simplify complexity, meet patients where they are, and empower them to make informed decisions about their health.

Jake McCarley, Co-Founder & CEO at Alluvium
Technology addresses health equity by providing enterprise intelligence that surfaces disparities in wait times, referral completion, and access patterns across patient populations, so leaders are no longer flying blind and can identify and address gaps proactively. Multi-channel access ensures all patients have equal opportunity to schedule care regardless of digital literacy, whether through web, mobile, or call centers, all seeing the same unified real-time availability across the entire network, including underserved geographic regions. The ability to allow for 24/7 scheduling removes barriers for shift workers and those unable to book during traditional business hours, while language customization options adapt to diverse community needs.

Casey Williams, Senior Vice President – Engagement, Analytics, and Payment Applications at RevSpring
Technology plays an important role in advancing health equity by helping healthcare organizations better understand the financial needs of diverse patient populations. By using data and analytics to personalize outreach, payment options, and financial assistance, healthcare staff can make conversations about cost of care more empathetic and aligned with each patient’s circumstances in an important step to address affordability barriers. Digital engagement tools that support multiple communication and payment channels, from text to phone to traditional methods, also help ensure accessibility for patients with varying levels of digital literacy. Ultimately, the goal is to use technology to meet patients where they are and make it easier to access and navigate care.

Dr. Joshua Tamayo-Sarver, MD, PhD, FACEP, FAMIA, Vice President of Innovation at Vituity & Inflect Health
Healthcare faces enormous cost pressure and persistent inefficiencies. While standardization is essential for improving efficiency, healthcare is also deeply personal. As systems become more standardized, many patients feel unseen or dehumanized, especially those from less-represented demographics or perspectives. When patients feel unseen, trust erodes. At the same time, rigid standardization on the supply side often forces patients to absorb the complexity of navigating the system, adapting themselves to how healthcare delivers services rather than the other way around. This creates a powerful opportunity for technology.

Technology can act as an intermediary between individual clinicians and an inflexible healthcare system. We’re seeing early examples through ambient and agentic tools for documentation, workflow, and administrative tasks. By lifting this burden from frontline staff, clinicians are free to focus on the person in front of them.

There is also promise to translate a patient’s context, concerns, and goals into the system while helping patients manage scheduling, insurance approvals, medication management, and denials. The beauty of today’s technology advances is that we can have a very bespoke experience and delivery mechanism for the patient on one side, with a very standardized experience for the health system on the other side.

As Maya Angelou noted, “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” The goal is to return the focus of healthcare to the very human interaction of one person caring for another, while the technology puts in the hard work to make sure all the million other important things happen effortlessly in the background.

What great points to consider here! Huge thank you to everyone who took the time out of their day to submit a quote to us! And thank you to all of you for taking the time out of your day to read this article! We could not do this without all of your support.

What role do you think technology plays in addressing health equity, accessibility, and digital literacy among diverse patient populations? Let us know over on social media, we’d love to hear from all of you!



< + > Buy or Sell: Conference Edition – Healthcare IT Today Podcast Episode 194

For the 194th episode of the Healthcare IT Today Podcast, we are back with another episode of everyone’s favorite game – buy or sell! In case you’ve forgotten or this is your first buy or sell episode, we set out a list of hot topics and trends in healthcare to discuss whether we believe the topic or trend is true/is going to happen (aka, we ‘buy’ it), or if we think it is not true/will not happen (aka, we ‘sell’ it). For this episode, we are doing a special conference edition, focusing on the trends we’ve heard from all of the different conferences we’ve both attended recently!

Here’s a preview of the topics and trends we discuss in this episode:

  • Health IT budgets are shrinking.
  • Vendor consolidation is still a high priority for CIOs.
  • Value-based care is the key to rural health’s success and survival.
  • Healthcare AI will not replace people.

Now, without further ado, we’re excited to share with you the next episode of the Healthcare IT Today podcast.

We publish a new Healthcare IT Today podcast every ~2 weeks. Thanks to our friends at Healthcare Now Radio, you’ll be able to listen to the latest episodes of Healthcare IT Today on their radio station for the first two weeks. Then, we’ll be publishing each episode as a podcast and YouTube video here after it finishes on the radio.

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If you work in Healthcare IT, we’d love to hear where you agree and/or disagree with the perspectives we shared. Feel free to share your thoughts and perspectives in the comments of this post, in the YouTube comments, with @Colin_Hung or @techguy on Twitter, or privately on our Contact Us page. Let us know what you think of the podcast and if you have any ideas for future episodes.

Thanks so much for listening!

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< + > How Small Practices are Putting AI to Work

The following is a guest article by Chris Knotts, CEO at PEAKE Technology Partners, an Omega Systems Company

The conversation around AI in healthcare is changing. What was once seen as overhyped is now being evaluated in more practical terms.

According to athenahealth’s 2025 Physician Sentiment Survey, fewer physicians now view AI as overhyped, and fewer believe it will make healthcare more complicated. The focus is shifting toward where AI can deliver value within existing workflows.

In larger health systems, that shift is already translating into action. These organizations have the scale, data, and resources to invest in AI and are beginning to see measurable impact across operations and care delivery. UnitedHealthcare’s recent launch of an AI chatbot for round-the-clock care navigation is one example of the customer-facing AI tools now operational at that scale.

Adoption is Early, but Direction is Clear

For small and mid-sized physician practices, AI adoption is more limited, but activity is increasing. Interest is high, and many practices are already experimenting with tools like ChatGPT and Claude to support documentation, communication, and internal workflows. The challenge now is moving from experimentation to practical, everyday use.

Much of that path runs through the EMR. Most small and mid-sized practices rely on a single electronic medical record (EMR) system to manage scheduling, documentation, and billing – the operational backbone of the business. As a result, AI evaluation often starts there: what is the EMR vendor introducing, and how can new capabilities be layered into systems already in use rather than built from scratch?

Where AI is Delivering Value in Healthcare Today

Practical AI adoption for today’s healthcare practices is largely concentrated in a few areas.

Clinical documentation is one of the clearest examples. AI-based scribing tools can listen during patient visits, transcribe conversations, and generate structured notes directly within the EMR. That reduces the time providers spend on documentation and allows them to stay focused during the visit.

The impact is operational as much as clinical. When documentation is handled more efficiently, providers can often see additional patients during the day. Even a small increase in patient volume can have a measurable impact on revenue in a private practice setting. Seeing just one or two more patients per day can translate into thousands of dollars in additional revenue.

This matters in an environment where practices are operating as small businesses, often competing within the constraints of their local healthcare economy. Reimbursement rates, payer mix, and cost structures vary significantly by region. Recent data from the Medical Group Management Association reflects that pressure, with nearly half of medical group leaders reporting declining operating margins year over year. In that context, even modest gains in efficiency can make a difference.

Administrative workflows are another area where AI is starting to make a difference. Many practices continue to rely heavily on phone-based communication. Patient calls to schedule appointments, ask questions, and follow up on care create consistent pressure on front desk staff.

AI voice tools focused on call handling and intake are beginning to address that demand. They route calls more efficiently, automate common interactions, and reduce the volume of routine requests that require staff involvement. In some cases, this allows practices to manage higher patient volume without adding headcount or to ease pressure on existing staff.

These improvements are incremental, but they have a direct impact on patient experience and practice revenue.

A Growing Set of Options and Questions

As use cases become clearer, the number of available solutions has grown quickly. Healthcare AI spending reached approximately $1.4 billion in 2025, nearly tripling year-over-year, fueling a rapid influx of new tools entering the market. 

For small and mid-sized practices, evaluating those options can be difficult. Most do not have the internal resources to compare vendors, assess long-term viability, or fully understand how a tool will integrate into their existing systems.

This creates friction in the decision-making process and can lead to missed opportunities to serve more patients.

Practices are working to determine which tools will improve operations and which may introduce unnecessary complexity or risk. Data privacy and security remain a central concern. Research shows that nearly 70% of healthcare leaders say these issues are a major barrier to AI adoption.

At the same time, the EMR continues to shape what is possible. As EMR vendors introduce their own AI capabilities, many practices are starting there. This approach simplifies adoption, but it also makes vendor security and risk management more important over time.

Balancing Efficiency with Risk

Each new AI tool introduced into a clinical environment raises questions about how patient data is handled, where it’s stored, and how it integrates with existing systems. In a healthcare setting, those questions carry real weight. According to IBM, healthcare continues to experience the highest cost of data breaches of any industry, reflecting both the sensitivity and value of the data involved.

Recent events have reinforced that risk. The cyberattack on Change Healthcare disrupted claims processing across the country, impacting providers of all sizes and highlighting how vulnerabilities in third-party systems can quickly cascade into operational and financial challenges for smaller practices.

AI adds another layer to that risk. Many of the tools entering the market rely on access to clinical data and integrate directly with core systems like the EMR. For smaller practices, that creates a practical challenge. The same tools that promise efficiency can also introduce new exposures if they are not properly evaluated, particularly when AI vendors are early in their development or lack a proven track record in healthcare.

Where IT Partners Fit In

As the pace of AI development continues to increase (workforce access to AI tools has expanded by 50% in just one year, according to Deloitte’s State of AI in the Enterprise 2026 report), healthcare practices need a trusted guide to help them capture the value responsibly. That’s where IT partners like Managed Service Providers (MSPs) and Managed Security Service Providers (MSSPs) play a key role.

IT support has traditionally focused on reactively maintaining digital systems and resolving issues. That remains important, but practices now need an IT partner who can chart AI adoption in the context of their growth goals. IT and security are no longer just back-office functions, but a key part of helping physician practices operate without disruption.

Selecting and implementing AI tools requires strategic context. MSPs and MSSPs can help practices evaluate AI vendors, understand tradeoffs, and reduce the risk to each individual practice.

This includes assessing how a solution fits into the existing environment, identifying potential security concerns, and helping prioritize which use cases to pursue. In a crowded market, that guidance helps practices move forward with greater clarity.

For small and mid-size practices, the strategic use of AI has a chance to revolutionize patient care, while improving margins and opening up expansion opportunities. Without the right support, many practices will struggle to fully realize the potential of AI.

About Chris Knotts

Chris Knotts is the Founder and CEO at PEAKE Technology Partners, now part of the Omega Systems family of companies. Together, PEAKE and Omega deliver integrated IT and security solutions to healthcare organizations across the Northeast, helping multi-site medical practices navigate EHR management, AI-driven tools, and HIPAA and HITECH compliance. Drawing on his background as a technology innovator and business leader, Chris has built a reputation for helping healthcare organizations use technology to expand access to quality care, strengthen culture, streamline workflows, and support the financial health of their practices. In addition to its managed services, PEAKE helps healthcare organizations evaluate and adopt emerging AI technologies through its PEAKE AI Lab, where tools are vetted for real-world EHR integration, rapid staff adoption, and proven success in medical practice environments.



Sunday, June 7, 2026

< + > Bonus Features – June 7, 2026 – 34% of patients would let an AI assistant read their entire medical record, 74% of clinicians worry relying on AI too much will erode their skills, plus 27 more stories

Welcome to the weekly edition of Healthcare IT Today Bonus Features. This article will be a weekly roundup of interesting stories, product announcements, new hires, partnerships, research studies, awards, sales, and more. Because there’s so much happening out there in healthcare IT that we aren’t able to cover in our full articles, we still want to make sure you’re informed of all the latest news, announcements, and stories happening to help you better do your job.

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If you have news that you’d like us to consider for a future edition of Healthcare IT Today Bonus Features, please submit them on this page. Please include any relevant links and let us know if news is under embargo. Note that submissions received after the close of business on Thursday may not be included in Bonus Features until the following week.



< + > Integration Into the Workflow Is Key to Ambient Scribe Success

The first year that Central Oklahoma Family Medical Center deployed the Sunoh.ai ambient transcription software, it was getting very littl...