< + > Epic UGM 2026 – Judy Faulkner Keynote and Cool Stuff Ahead

It’s that time of the year again.  It’s the annual journey that Epic users make to Verona, WI to hear from Judy Faulkner and the team at Epic at their user conference called UGM.  If you’ve never been to the Epic campus it’s quite the experience, and the whole campus is transformed into a massive conference center where Epic users, Epic staff, and some of the vendors that support them connect and learn.  Plus, they invite a few media people like myself to take part.

This is my third time attending Epic’s UGM and it’s amazing how quickly a conference becomes familiar.  Plus, with Epic doing a mid-year event where they made a bunch of their AI announcements, there weren’t as many surprises as in past years.  Not to mention, many of the biggest things are progressions on efforts they’ve already started.

This is best illustrated by Judy starting off her presentation sharing that at last year’s UGM, Epic mentioned 167 major projects.  She shared that 84 of those projects were completed on time, 7 are completed or will soon be completed with a Special Update (SU) and 76 are in progress as planned and on track.  Judy is particularly proud that they deliver what they promise.  Of course, when you look at that number of projects, you can understand why we shouldn’t expect a bunch of surprising announcements.

I think one of the big things that attendees were watching for at this year’s UGM is who would be on stage with Judy after Sumit Rana’s departure.  Seems like the answer to that question was Seth Howard who led the Cool Stuff Ahead section of the event.  There was plenty of talk at the event about these changes and some of the other executive departures beyond Sumit.  I don’t think customers were concerned about the changes, but they are definitely interested to see who will fill the holes since Sumit had started to become the face of Epic and Seth Hain had become the face of their AI efforts.  No doubt this will be an ongoing story until (if?) Judy decides to retire.

Now let’s take a look at some of the big announcements they made at this year’s Epic UGM.

Cosmos Curiosity – This felt like one of the biggest announcements to me and the one we didn’t already know about.  Sure, it’s basically an extension of what they were doing with Cosmos, but seeing how it can be used for research and how it could be integrated into the clinician’s workflow was really interesting.  I’m curious to see how this is really used by clinicians.  Do probabilities really impact their care choices?  Can they use it to motivate patients?  I have lots of questions, but the idea of using all the Cosmos data to predict outcomes for a population of patients or an individual patient is really interesting and exciting.

Ergo – Healthcare Intelligence in Epic (Coming in Nov 2026) – I found this to be the most confusing announcement that was made at Epic UGM.  Although, Judy led with it, so she obviously saw it as really important.  I had to talk to a number of Epic people to really understand what it is.  Assuming I’ve understood correctly, Ergo is the new clinician interface that flexes to the needs of the clinician in that moment including input from things like the ambient clinical voice tools.  Plus, it leverages the various skills of tools like Art, Emmie, Penny, and Cosmos to filter up the information that clinician needs for that specific patient in that moment.

Here’s a high level overview of it:

• Visit Topics – Art and Emmie help curate topics for the visit
• Summarization – Art synthesizes key details from the chart
• Ask Art – Users ask Art about the chart
• Penny – Brings in billing and RCM details
• Insights from Cosmos – Art brings real-world evidence to the point of care

In many ways I see Ergo as the next iteration of the clinician interface.  Another way to look at it is packaging all of the various AI tools that they’ve been creating into one interface.  Not sure why it needs a product name, but it is a cool new interface and one we knew would be possible thanks to AI.  We all knew that different specialties and/or users (ie. doctors vs nurses) needed different information.  EHR’s had often allowed that user to change their preferences on what was shown.  Ergo is doing this, but dynamically on the fly.  Pretty cool to consider.  Will take a bit of time to perfect it though I think.

Chart with Art – One of the big announcements at last year’s Epic UGM was Epic’s decision to do their own AI medical Scribe/Ambient Clinical Voice tool.  This was such a big deal that they even did a mid-year Cool Stuff Ahead event talking about the first user.  The keynote session was short on all the details of Chart with Art.  I’m sure there were some breakouts that dove deeper.  A few details they did offer was that 70 Specialties Live and they’re live with doctors, nurses (10 organizations live), pharmcists, behavioral health.  Plus, they’re working on the integration with the visual documenation of dermatology and dentists.

Another big announcement related to Chart with Art is that Epic now offers a voice recognition or dictation solution.  Many of their customers still wanted to be able to dictate something outside of the visit that’s captured ambiently.  This new solution from Epic allows a healthcare organization to be able to stop using a product like Dragon.  2 other related features announced was Ask Art which didn’t have many details.  Plus, they announced an Evidence in Art which ties in to Drug Facts, Organizational Protocols, and also Clinical Guidelines from UpToDate.  Plus, they’re working on adding peer reviewed journals in the future.

Epic and Claude’s Glasswing and Mythos – Epic announced on stage that they have been one of the companies that Claude allowed access to their highly talked about generative AI solution for security.  If you’re in the security space, then you’ve probably heard about Glasswing and Mythos.  If you haven’t, do a search and read about it.  Claude saw it as so powerful at breaching software that it has chosen not to release it to the public (yet?) and just offered it to a limited number of companies.  Purportedly to allow those companies to leverage those tools to secure their software.  It’s great that Epic got access to it.  I’m sure they don’t want to share what it found, but it’s fair to say that they’re likely more secure thanks to what it found.

The presenter that shared the news about Glasswing and Mythos also highlighted that the number of security patches that are being issued across software in general has been really accelerating.  Then, he asked the question, “If a vendor isn’t shipping security patches, why aren’t they?”  Definitely a powerful idea to ponder.  He also highlighted how the hosted version of Epic is able to be patched and secured in 7 days versus much longer for other systems.  I’m probably missing a little context with these numbers, but it was a clear message that they feel Epic’s own hosted version gets secured better than others.

Epic Options –  Judy highlighted all of the names of the various interfaces to access Epic.  It’s always fun to see how excited she gets naming products.  I think it may be her favorite part of her job.  Sonnet (desktop), Canto (tablet), Haiku (phone), Limerick (watch), and if they ever do a ring (mostly a joke) it will be called Chirp.

Epic Embracng Smaller Organizations – We all know that for the longest time you had to be a large organization to even be able to buy Epic.  One of their biggest efforts to get smaller organizations on Epic was Community Connect.  That’s still an important initiative for Epic and was the preferred approach according to Judy.  However, Epic is also working on a number of new options for smaller organizations: Orchard (small healthcare organizations), Garden Plot (cooperative use for specialties), Flower Pot (for the very small – Coming Soon), Inpatient Garden Plot (small hospitals – Coming Soon).  Judy seems pretty committed to getting healthcare organizations of all sizes on Epic.

Epic Research – I’m slightly biased to what’s happening at Epicresearch.org and what Judy announced because my host at Epic for UGM leads that effort.  Judy encouraged everyone to sign up for alerts on it.  It’s free and will notify you of new research.  It was interesting to hear how much more they’re able to do with better data and AI tools.

Even bigger than the research, Epic also talked about new Data Tracker that provide ongoing monitoring for the follwing areas:

• BMI Trends
• GLP-1 Trends
• Communicable Diseases
• Vector-Borne Illnesses
• Fentanyl & Opiate Toxicology
• Telehealth Utilization
• Cancer Incidence

I was also really impressed by Epic using their data to do Health Alerts.  It’s cool to see Epic doing outbreak detection & monitoring with all of the data in various Epic systems.  Since launching in April, 13 alerts have been published.  The one for cyclosporiasis was one week earlier than CDC according to Epic.  This will be an interesting Public Health effort to watch.

Epic ERP – The move into the ERP space is progressing as expected.  It’s call EpicOps and is starting with Workforce, Supply Chain, and Financials.  We already covered most of what was shared at UGM in our interview about the Epic ERP earlier this year.  What was interesting to me was that they already had a good number of companies using it or implementing it.  This to me is a decade long effort, but it would be a mistake to underestimate what they can do.  It won’t really disrupt the ERP today, but it’s going to knock off pieces of the ERP.

RCM AI – I always find the announcmeents around RCM (Revenue Cycle Management) interesting because there’s a whole industry of companies that are focused on this.  I’ve asked them many times whether these announcements from Epic impact them.  The consensus seems to be that in the short term it may cause a little slow down, but the complexity of RCM is something that they think Epic won’t fully take on.  Especially since it often requires a mixture of software and services.  That said, Epic did share some interesting details about their AI efforts related to RCM:

• Professional Coding Assistant – 360+ Live – More than 40 groups reduced coding denials by 20% or more
• Denial Appeals Assistant – 330+ Live – Appeals created 23% faster for medical necessity denials
• Medical Necessity Insights – 180+ Live – 12,500 hours saved in prior auth submission

They also mentioned a number of other features coming including: CDI Nudges, Automated Claim Edit Resolution, and AR Valuation.

Autonomous Coding (Penny) is available now for radiology and emergency medicine.  Working on surgery and pathology in the future.  Based on the AI’s confidence it will auto-code or if it’s low confidence it will mark it as needing review.

Agent Factory – We’d already heard quite a bit about agent factory before UGM, so most of this wasn’t a surprise.  We also have an interview with Derek De Young who presented Epic’s agent factory on stage where we dive into a lot more detail about it.  So, watch for that interview coming out in the next few weeks.  Although, I found it interesting how he framed the keys to agent factory being: Integrated, Personalized, and Continuously Improved.  It was also really impressive to see the 129 features (78 more in development) of Art, Emmie, and Penny that are available in agent factory.  It’s going to open up a lot of opportunities for ambitious organizations.  Plus, I was fascinated with how Epic is using agent factory to solve some problems too.  More on that to come in our interview.

Clinical Trial Management System – Looks like Epic’s CTMS is going to be claled Forward.  It’s an end-to-end study management built directly into Epic and is coming in November for early adopters.  I think this was announced last year and was mostly just an update on timeline.

Organ Donations in MyChart – This was highlighted last year as well.  Although, the numbers are pretty astounding.  300,00 people have signed up through MyChart as an organ donor.  MyChart is now the #1 source of new organ donor registrations in the US.

MyChart Central – This was largely an update on what was announced last year.  MyChart Central is now live in 50 states.  MyChart Central Device Data and Emmie in MyChart Central are coming soon which differs from today where you can just login to MyChart instances for different organizations.  Some other patient focused features included Incoming Voice AI & Voice AI Referral Scheduling which will be available in 2027.  Smarter Check-In with a pre-visit assistant and dynamic topic curation is coming in 2027.  Epic is also considering ways to improve adherence and outcomes in the future.

Intelligent Exam Room – They didn’t offer too many details on this, but the demo did show how the TV for the patients could be used by the patient for entertaininment, education, etc, but the doctor could also pull up MyChart in the exam room as well.  I wonder if it will be a unique format that shows specifc information to the patient and doctor or if it will basically be Ergo that’s dynamically pulling info during the visit.  Seems like Ergo should be able to accomplish this.  It reminds me of the demos that eClinicalWorks has shown at their user events with a shared screen between patient and doctor.  15 years ago I remember writing about doctors sharing their EHR screen with patients with really good results.  This is the next iteration of that idea.

Integrated eFax – All of the eFax companies likely woke up for this slide.  Their eFax is available in Hello World and they’re working on fax referrals being automatically populated.

Epic Savvy – Coming in the future.  It will allow organizations to collect payments without a payment gateway.  That includes payments via bank which will save on credit card fees.  It will be interesting to compare these to other payment processors.  My guess is that Epic will have a really good rate.

Pulse AI Adoption and AI Feature Cost – Looing at how AI is being used and how much it will cost.  Plus, an Inventory and Outcomes and Evaluation tool to look at if the AI is creating value and doing what it should.  This actually may have been the topic of the conference.  Everyone loves all the new AI, but they’re also wondering how they’re going to afford it all.  That includes not just the cost of the AI itself, but also the work to implement and integrate it into their workflows.

Epic did talk about AI Responsibility in the keynote.  They shared that with great power comes great responsibility to do the following:

• Apply the right Guardrails
• Evaluate Responses
• Monitor Outcomes
• Manage Costs

Epic Usage, Support and Implementation – These topics have been a big one for Judy for quite a while.  Especially when it comes to customers that aren’t using the various pieces of Epic.  They already have a number of programs including honor roll where you can earn a discount on the product if you’re using it, but Judy also highlighted the executive package which highlights the various opportunities for an organization to better utilize Epic.  Sounds like these packets were a bit overwhelming and so they’re revising it with a page that has that organization’s top opportunities.  This packet is designed to help organizations save lifes, make money, and work more efficiently.

Even more interesting was Judy’s stated desire to do what she called “Helping You Do More with Less.”  Here are the suite of support that they’ve put together for organizations:

• Technical services
• Implementation services
• Ongoing services
  • Level up
  • Guides
  • Rangers (Epic staff you hire) – like Boost, but long term

The new one is Rangers which is where an organization pays for an Epic staff to be permanently dedicated to them and onsite.  Judy said they’ve been doing something kind of like this with their Boost program where an Epic employee needs to move (generally for personal reasons) and would still like to work for Epic, but technically can’t because Epic requires you to be in the office in Madison (or they did announce some international offices).  This feels like a nice way to get around the must work in the office rule to me.  Although, I also feel like Judy also saw that Epic received 340,000 applicants for jobs at Epic.  No doubt, there were more people in that group that would be qualified to work at Epic and could help out Epic customers.  It will be interesting to see how this program is accepted by customers and how it grows.

Analyst build assistant – This assistant kind of reminds me of the tool that Rhapsody created for integration experts, but this is an AI tool for Epic analysts.  Seems like this is just a view into what they’re starting since they mentioned the assistant would eventually actually be able to actually do stuff the analyst would normally do.  Accelerating the work of Epic Analysts is a worthy goal since they can be hard to find and aren’t cheap.

Here are a number of other announcements and items mentioned:

• Diagnostic Image Exchange allows health systems to share diagnosticquality images—including CTs, X-rays, MRIs, and more and is availale now.
• Growth in Integrations – Payer, Diagnostics, Devices, Specialty Societies, Surgical Implant Manufacturers, and Life Sciences
• Real-Time Patient Flow Insights is coming soon to free up beds and decrease length of stay.
• New Underpayment Recovery Automation
• Medicaid Application Assistant – Knows the state specific Medicaid application fields and automatically populates the state Medicaid portal with a patient’s information.  Also, reminds patients of redetermination when needed.

It’s always interesting when Carl Dvorak hops on stage to talk about Epic’s international growth.  Although, this quote from Sue Sheridan, CEO at Patients for Patient Safety US, was actually one of the most insightful things he shared “Clinicians adopt AI at the speed of trust.  Patients adopt it at the speed of desperation.”  I’ll be chewing on that one for a while.

I also love that Judy always ends her talk with “Have fun and learn a lot.”  That’s a good mantra for a lot of things in life.

That’s my roundup from Epic UGM.  I probably missed a few things, but hopefully it gives you a good overview of what was shared.  Let us know what you think of these announcements on social media.

< + > Millions of Americans are Asking AI for Medical Help, Bad Data is Standing in the Way

The following is a guest article by Matthew Blosl, CEO at DexCare, a Leading Patient Navigation Platform for Health Systems

It’s 10 p.m. A patient in rural America logs onto her hospital’s web portal and sees test results outside the normal range, with no explanation of what they mean. Her doctor’s office won’t open for another 12 hours, and the nearest urgent care center is 45 minutes away. She’s left with a long, anxious night and no way to get answers.

This gap—no access and no next step—is what AI is beginning to fill. Companies like OpenAI and Anthropic have introduced tools to help patients better understand their health and support clinicians in delivering care more efficiently.

Some experts, rightly so, remain cautious and point to AI’s tendency to hallucinate as a risk to patient safety. But for many patients, the more immediate problem is simple access to healthcare. The ability to see a doctor that day. And to understand test results when the email pings their inbox. And when over 37% of Americans live in healthcare deserts—with no access to essential medical services—AI is connecting patients to care in ways the current system can’t.

Today, ChatGPT answers healthcare questions for 230 million people worldwide each week. Patients get answers in seconds, without needing a copay, waiting for a callback, or scheduling an appointment.

Not surprisingly, most ChatGPT healthcare queries happen after traditional office hours. And with wait times for primary care appointments now measured in weeks or months— sometimes longer for certain specialties—patients are increasingly willing to seek help elsewhere, even if that help is imperfect.

Benefits are showing up in the exam room, too.

The technology helps patients arrive at their appointments more prepared, leading to deeper in-office conversations. As David Liebovitz of Northwestern University explains, AI chatbots can synthesize a patient’s history, surface potential concerns, and provide more context-aware insights that can improve decision-making. That’s progress from the era of ‘Doctor Google,’ where you’d type symptoms into search and brace for the worst. Could this headache really be a tumor?

However, enthusiasm and caution often travel together.

“The stakes are exceptionally high in healthcare,” notes Dr. Peter Bonis, Chief Medical Officer at Wolters Kluwer Health. “Whether these applications prove safe and effective over time is still uncertain.” He’s right. And it’s too early to know the technology’s long-term impact or limitations. But we need something to shake up our healthcare system. To force change.

As Medicare expands to cover nearly one-fifth of Americans, while the supply of physicians dwindles, seeing a doctor is only going to get harder. For AI to move from a chatbot in your pocket to the transformative technology that dominates news headlines, health systems must tackle a problem in plain sight.

The culprit is bad data.

Healthcare produces nearly one-third of the world’s data, yet much of it remains siloed and disconnected within health systems. The result? Information that patients need is often invisible, partly right, or flat-out wrong. One in three patients who book a doctor’s visit online encounters inaccurate information. And one in five can’t find the right provider at all. The consequences are felt everywhere. Doctors with open appointments go unfilled. Patients who could have been seen end up in the ER. AI, handed the same broken data, reaches the same dead end.

This data chasm stands between AI’s promise and what it can deliver.

AI can now tap directly into live healthcare data, but connectivity was never really the problem. If the data on the other end is fragmented, buried across too many systems, and inaccurate, then AI inherits those flaws, creating a faster, more confident path to the wrong answer. What AI ultimately needs is data worth trusting. Data that tells a system which doctor is available, who is the right fit, and how to get a patient to that doctor.

When the data is right, AI can do more than just answer questions after hours. It can match patients to the right doctor, surface the right history, and handle the work that clogs the system. As a result, routine appointments become earlier diagnoses and more precise treatment. And a country running short on doctors gets a little more out of the ones it has.

For the patient staring at test results at 10 p.m., AI is already in the room. What’s missing is the data foundation beneath it.

< + > This Week’s Health IT Jobs – August 19, 2026

It can be very overwhelming scrolling through job board after job board in search of a position that fits your wants and needs. Let us take that stress away by finding a mix of great health IT jobs for you! We hope you enjoy this look at some of the health IT jobs we saw healthcare organizations trying to fill this week.

Here’s a quick look at some of the health IT jobs we found:

• Government Provider Operations Analyst – Teladoc Health
• Health Info Management Manager – Resolute Baptist Hospital
• Community Health Worker – Sorogi Health
• IT Leadership Operations & Executive Coordination Lead – Fresenius Medical Care
• Patient Access Lead – Cone Health
• Clinical Director, PHP/IOP Network – ForwardCare
• Pharmacy Support Analyst – Cardinal Health
• Specialist – HIMS – Mayo Clinic
• Senior Manager IT, Master Data Management – AmeriHealth Caritas
• Revenue Cycle Analyst – Healthcare – Behavioral Health Group (BHG)
• Behavioral Health Quality Assurance Analyst – America’s Community Council (ACC)
• Managed Care Contract Analyst I – Boston Children’s Hospital
• Coding Rep I – Cincinnati Children’s
• Clinical Documentation Specialist (Remote) – IHA
• VP of IT – eMed
• Healthcare Compliance Officer – Multi-Site Medical Group, MSO, ACO – Primary PartnerCare
• Director of IT Infrastructure & Security – AdvancedHEALTH
• Clinical Product Marketing Manager – Healthie
• Community Outreach Worker – Sevita
• Sr. Director, IT Business Partner to Finance, Planning, & Analysis – Medtronic

If none of these jobs fit your needs, be sure to check out our previous health IT job listings.

Do you have an open health IT position that you are looking to fill? Contact us here with a link to the open position and we’ll be happy to feature it in next week’s article at no charge!

*Note: These jobs are listed by Healthcare IT Today as a free service to the community. Healthcare IT Today does not endorse or vouch for the company or the job posting. We encourage anyone applying to these jobs to do their own due diligence.

< + > Stop Waiting for Interoperability: PocketHealth Uses Agentic AI to Automate Operations Across Systems

Healthcare has spent billions trying to force disparate systems to talk to each other through custom APIs and shared data standards. Yet administrative staff still spend their days copying data manually across disjointed software screens. What if solving interoperability does not require complex data integration at all?

Healthcare IT Today sat down with Rishi Nayyar, CEO of PocketHealth, at their offices to discuss how agentic AI is transforming health system operations. PocketHealth is pioneering a fresh approach to operational automation with its new agentic operations platform, Conductor, which tackles longitudinal workflows across disconnected systems.

Key Takeaways

• Agentic AI offers a direct workaround to traditional interoperability bottlenecks. Rather than waiting for universal standards or API adoption, intelligent agents can work across the entire system at the interface layer, not just the parts a vendor exposes through an API.
• EHRs are built for data consistency, not dynamic process orchestration. Electronic health records excel at serving as systems of record, but managing complex, longitudinal operational workflows that span service lines and systems requires a dedicated automation layer.
• Delaying operational automation leads to immediate patient drop-off. Modern health care consumers expect instant communication and rapid response. Organizations clinging to manual phone queues, fax forms and people-powered processes will lose patients to faster peers.

Solving Interoperability Through Interface Automation

For decades, health care technology leaders viewed interoperability as a pure data standards challenge. Nayyar and his team at PocketHealth recognized that human staff currently serve as the makeshift bridge between systems that do not talk to each other. By applying agentic AI to navigate software screens, PocketHealth bypasses traditional integration hurdles entirely.

Nayyar pointed out that intelligent software can replicate these exact human workflows across graphical user interfaces. “Agentic AI can do the Interoperability work that humans are doing now,” Nayyar explained. “Right now, if you have two systems that don’t speak to each other, a human plays that role [the bridge]. I look at a work list, then I open up MEDITECH or Cerner, and then I do X, Y, Z task based on the work list. What are you leveraging? You’re leveraging the GUI, the graphical user interface. Agentic AI can do the exact same thing.”

Separating Systems of Record from Process Orchestration

Healthcare organizations expect their EHRs to have comprehensive operational workflows. According to Nayyar, however, expecting an EHR to orchestrate complex care journeys across departments is unrealistic. Organizations are left waiting for the next release for the needed functionality or when it arrives, it does not exactly match the organization’s workflow.

Nayyar believes that EHRs should stick with what they excel at: “An EHR or a PACS system, they are systems of record. Meaning they are meant to be consistent storers of the ground truth. A very valuable role. You need that in a health system. But those are point in time views. The ‘work to be done’ orchestration and longitudinal work is a completely different problem space.”

Thus the need for separate and dedicated coordination layer to automate the cross-departmental workflows while using the EHR’s data stores.

The Operational Risk of Delaying AI Adoption

For Nayyar, hesitating to automate administrative tasks carries measurable risk for health systems. Patient expectations have shifted dramatically toward instant access and digital convenience. Staying attached to legacy operational methods will slowly erode patient and staff confidence which leads to organizational decline.

In other words, organizations that rely on human-powered processes only will get left behind.

Nayyar went further and shared his opinion that patient retention and referral patterns will reflect this operational divide sooner than many executives think. “We are moving into a world where these things will very quickly become table stakes. Patients will expect to call and be able to talk to someone immediately, not stay on hold or print off and then fax a form in order to get a referral,” Nayyar cautioned. “Your scores across all of these metrics, including the soft metrics, will immediately begin to degrade relative to your peer group, and that has real implications. That’s not just numbers on a page.”

The Bottom Line

Health IT leaders cannot afford to wait for total data standardization before streamlining operations. By deploying agentic AI to handle cross-system tasks, organizations can immediately remove manual labor from front-desk staff while improving patient satisfaction. PocketHealth demonstrates that the path forward lies in pairing trusted systems of record with smart automation tools built specifically for process orchestration.

Questions Healthcare IT Leaders Are Asking

How does agentic AI address health system interoperability?
Agentic AI can bypass traditional data integration challenges by interacting with software through graphical user interfaces rather than relying solely on custom APIs or shared data standards. The AI navigates screens, inputs data, and executes tasks across disparate systems just as a human staff member would. This allows health systems to automate cross-platform workflows immediately without waiting for underlying software architectures to unify.

Why shouldn’t health systems rely on EHRs for longitudinal workflow orchestration?
EHRs are engineered as static systems of record designed to preserve ground-truth clinical data at specific points in time. They lack the architectural flexibility required to orchestrate complex, multi-step workflows that span across different service lines, third-party systems, and patient communication channels. Using purpose-built automation layers on top of the EHR allows each system to perform its primary function effectively.

What are the operational risks of postponing administrative automation?
Delaying operational automation exposes health systems to severe degradation in patient experience, lower retention rates, and reduced referral volumes. Today’s patients expect immediate response times and digital self-service options. Organizations that maintain manual phone lines, paper forms, and slow scheduling processes, especially for referrals, will rapidly lose market share to competitors offering frictionless access.

Learn more about PocketHealth: https://www.pockethealth.com/en-us/

Listen and subscribe to the Healthcare IT Today Interviews Podcast to hear all the latest insights from experts in healthcare IT.

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< + > Why Patient Financing Belongs in the Digital Front Door, Not Just the Billing Office

The following is a guest article by Drew Allen from Conceptualized Inc.

Health systems and practices have spent the past several years building out the digital front door: online scheduling, patient portals, digital intake, and telehealth triage. The goal was to make the start of the patient journey feel as easy as booking a flight or ordering groceries.

Payment got left out of that redesign. At many organizations, the financial conversation still happens the old way. A phone call after the visit. A paper statement in the mail. A payment plan was hashed out verbally at the front desk. That gap is getting harder to justify as patients cover more of the bill themselves and as the technology to fix it becomes widely available.

The Patient Payment Reality Behind the Numbers

The scale of the shift is well documented. According to Kodiak Solutions’ 2026 State of the Healthcare Revenue Cycle report, the insured patient’s share of net revenue rose from 6.8% in 2024 to 7.3% in 2025, while the share of that responsibility providers actually collected fell from 45.1% to 42.4% over the same period. Providers are owed more, yet collect less of it.

Rising deductibles are part of what’s driving that. KFF’s Employer Health Benefits Survey tracked the average single-coverage deductible climbing from $1,217 a decade ago to $1,886 in 2025, with more than a third of covered workers now on a plan with an individual deductible of $2,000 or higher.

Patient expectations have moved, too. Experian Health’s State of Patient Access research found that roughly 70% of patients want their healthcare financial experience to look like the other services they pay for: clear pricing, digital payment options, and flexibility. Not a mailed invoice that shows up weeks after the appointment.

The Digital Front Door Was Built for Scheduling, Not Paying

Most digital front door strategies aim to solve access problems: get patients in faster, reduce no-shows, and eliminate phone tag with the front desk. Those investments have paid off in patient satisfaction and operational efficiency.

The financial side rarely got the same treatment. A patient can book an appointment in two taps, fill out intake forms on a phone, and then, weeks later, get a paper bill with a phone number to call about payment options. That handoff, between a smooth clinical experience and a clunky financial one, is where a lot of the collection trouble documented above actually starts.

Where Financing Fits in the Health IT Stack

Point-of-care financing tools are increasingly being built to close that gap by plugging directly into the same digital journey that already handles registration and scheduling, rather than existing as a separate, manual process.

In practice, that typically means a pre-visit or point-of-service cost estimate is paired with a customer financing offer presented in the patient portal or at checkout, similar to the buy-now-pay-later integration patterns patients already encounter in retail. This kind of tool typically works from the provider side: a patient applies in the same digital moment they’re reviewing their bill or treatment plan, receives a decision in seconds, and the practice is typically funded upfront, regardless of the payment term the patient selects.

For RCM and IT teams, the appeal is straightforward. Instead of a balance sitting in accounts receivable for 60 or 90 days while staff attempts phone collections, the financing partner assumes that timeline, and the practice’s cash flow is no longer tied to the patient’s ability to pay in full at the time of service.

What This Looks Like in a Typical Workflow

Take a mid-sized specialty practice, a fairly common scenario: a patient is scheduled for a procedure with an estimated $2,400 in patient responsibility after insurance. In a traditional workflow, that number might get mentioned verbally at check-in, followed by a mailed statement once the claim is adjudicated, then phone calls if the balance goes unpaid. Every step in that chain adds days or weeks before any money changes hands, and a chunk of the balance is usually written off as bad debt.

Embed financing in the digital front door, and the same estimate shows up in the patient portal before the appointment, with a financing option the patient can apply for and get approved for in under a minute. From there, the practice can treat that balance as effectively resolved at the time of scheduling, rather than watching it age through weeks of accounts receivable. Multiply that across dozens or hundreds of balances at once, and the shift changes the shape of the whole collection’s workload, not just one patient’s experience of it.

There’s an equity angle here, too. A growing share of patient responsibility now comes from self-pay and post-insurance balances rather than from deductibles alone, and patients without much credit history or existing credit products are often the ones most likely to put off or skip care due to cost. Financing tools built around a soft pull rather than a hard credit inquiry can expand affordability options for the population most likely to fall through the cracks of a phone-based collections process.

What IT and RCM Leaders Should Evaluate

Financing integrations aren’t interchangeable, and the technical and compliance details matter as much as what the patient sees on screen. Teams evaluating a financing layer for their digital front door tend to focus on a few key areas.

Integration depth matters first: does the tool plug directly into the practice management or EHR system, or does it force staff to use a separate portal outside their existing workflow? Real-time accuracy matters too, since a cost estimate is only useful if it reflects actual negotiated rates and remaining benefits rather than a generic average. The credit model is worth scrutinizing on its own: a hard credit inquiry can scare off patients with limited or damaged credit, where a soft pull or alternative underwriting approach won’t.

Compliance posture is its own category, covering how a vendor handles state-specific lending regulations and disclosures, since financing products are subject to consumer lending law regardless of the healthcare context in which they’re used. And funding timeline rounds it out: how fast the practice actually gets paid once a patient is approved and a plan is chosen, since that’s the piece that determines whether the cash flow benefit is real.

The Last Mile of the Digital Front Door

Healthcare IT teams have spent years polishing the front end of the patient journey: search, scheduling, intake, clinical documentation. Payment was treated as someone else’s problem, owned by the business office instead of the digital experience team.

That division is getting harder to defend as patient financial responsibility continues to climb. The organizations closing the gap between collection performance and patient satisfaction are those treating the payment moment as part of the same digital experience as everything leading up to it, rather than a separate process that begins only after the clinical encounter ends.

About Drew Allen

Drew is a husband and father of three who writes about the intersection of healthcare, technology, and the patient experience. His perspective focuses on how practical technology can help make healthcare more accessible, transparent, and easier to navigate—from the digital front door through the financial side of care. He is particularly interested in the ways healthcare organizations can use technology to improve the experience for both patients and the teams who serve them.

< + > Wellinks Closed $10 Million Series B Funding | Function Secures $450 Million Growth Financing

Check out today’s featured companies who have recently raised a round of funding, and be sure to check out the full list of past healthcare IT fundings.

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Wellinks Closed $10 Million Series B Funding from UMass Memorial Health and Inside Investors

Investment Builds on Wellinks’ Strategic Partnership with UMass Memorial Health and Other Commercial Partners to Accelerate Growth and Expand Patient Access to Its Predictive Care Model

Wellinks, a leader in cardiopulmonary care, today announced the first close of its Series B Funding, securing $10 million to fund commercial growth with participation from UMass Memorial Health and inside investors. The investment builds on Wellinks’ multiyear relationship with UMass Memorial Health and other partners to accelerate the expansion of Wellinks’ predictive care solution.

Wellinks’ FDA-cleared Spire Remote Patient Monitoring (RPM) System helps identify early physiologic changes associated with clinical deterioration, supporting earlier intervention and proactive management of chronic respiratory disease beyond traditional care settings.

Wellinks and UMass Chan Medical School first collaboratively approached reducing acute care utilization in COPD patients through the Healthy at Home program. The study found that Healthy at Home participants had more than 60% lower odds of 30-day hospital readmission, with trends toward fewer emergency department visits and shorter hospital stays than similar patients who did not participate. For more information, read “Healthy at Home study demonstrates feasibility, effectiveness of mobile care for COPD.”

“Our continued collaboration with Wellinks reflects a shared commitment to advancing proactive, data-driven care,” said Dr. Eric Dickson, CEO at UMass Memorial Health. “Together, we’re generating real-world clinical evidence that supports better outcomes for patients and informs the future of cardiopulmonary care.”

Wellinks will use the funding to…

Full release here, originally announced August 4th, 2026.

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Function Secures $450 Million Growth Financing from General Catalyst’s Customer Value Fund (CVF)

Financing Will Accelerate Function’s Mission to Help Millions More People Own Their Health

Function today announced the closing of $450 million in growth financing from General Catalyst’s Customer Value Fund, accelerating the company’s mission to help millions more people understand and take ownership of their health.

The financing underscores conviction in Function’s vision to fundamentally change how people take ownership of their health. Since early beta launch in 2023, Function has defined a new category by bringing lab testing, imaging, and personalized intelligence into a single platform designed for lifelong health.

The capital will enable Function to bring its platform to millions more people faster. This announcement comes on the heels of Function’s Q2 expansion acquisitions of Getlabs’ nationwide at-home or office blood draw network and SuppCo’s supplement platform.

“Our mission is simple: enable you to live 100 healthy years. Everyone deserves to feel their best and avoid suffering,” said Jonathan Swerdlin, Co-Founder and CEO at Function. “Every dollar invested in Function is a vote for one hundred healthy years for eight billion people. This growth financing allows us to pull the inevitable and optimistic future of health into the present.”

“This financing reflects our belief that Function is one of the defining companies of our generation,” said Pranav Singhvi, Partner and Co-Head at CVF, General Catalyst…

Full release here, originally announced July 30th, 2026.

< + > What Ethically Built AI Must Mean in Behavioral Health

The following is a guest article by Michael Arevalo, Psy.D. Director of Clinical Strategy at Core Solutions

Picture a behavioral health clinician early in a career, reviewing an intake form on an ordinary morning. The presenting complaint reads clean: anxiety, disrupted sleep, some family conflict. Nothing unusual, on the surface. Then one phrase stands out, an offhand line from the person. “I’m not sleeping much, but that’s normal for me.” This might be nothing. Then again, it might be the start of something worth asking about further.

That instinct, the willingness to sit with discomfort rather than paper over it, is exactly what most AI systems struggle to replicate. I see this gap constantly in conversations about AI and behavioral health.

Why Agreeable isn’t the Same as Accurate

Most large language models are trained to be helpful, and helpful, in practice, usually means agreeable. Ask one a question, and it hands back something confident-sounding, with no room left for doubt. That’s a minor annoyance in most fields, but in behavioral health, it’s a real problem. A clinician’s job, especially early in a career, often comes down to catching the detail that doesn’t fit: a phrase in an intake note, a shift in someone’s affect a template would never pick up on. An AI tool that hands you a clean summary isn’t saving you time so much as it’s quietly deciding what didn’t matter.

This is where ethically built AI earns its name. It is a specific standard and one with real requirements: a system that stays transparent about how it reaches conclusions and keeps a named person accountable for what it produces while treating safety and privacy as basic requirements. In behavioral health, this can help to protect the therapeutic relationship itself and keep the clinician as the one who makes decisions.

Clinical judgment, treatment authority, and responsibility for outcomes stay with licensed professionals. An AI system can surface a pattern, flag a risk indicator, or draft a summary for review. What it cannot do is make the final call. The moment a tool renders a judgment a clinician cannot trace back, examine, or override, something important has been lost.

Where the Law Already Agrees

The law is starting to catch up. Illinois’ WOPR Act prohibits licensed providers from letting AI make independent clinical decisions. Nevada’s AB 406 goes further, barring AI from providing professional behavioral healthcare outright. Utah’s HB 452 requires mental health chatbots to disclose their use and limits how they handle sensitive data.

The FDA draws a similar boundary between support and decision-making in the form of a four-part test that determines whether clinical decision support software stays exempt from medical device regulation. The software cannot analyze signals or images on its own, and it has to work from existing medical information. It must support a clinical decision rather than direct it, and a clinician must be able to independently review how it arrived at any recommendation. Fail any one of those tests, and the software becomes a regulated device. Put simply: If a clinician cannot see how a tool reached its conclusion, that tool now answers to a regulator.

What This Means for AI Adoption in Behavioral Health

AI can give clinicians real-time feedback, and few fields need that relief more than behavioral health. An AI-driven EHR activates every capability starting at implementation. What matters most is how well an organization governs it. 

Daily workflows are where that governance gets tested. Staff need dedicated time to review AI-generated insights before those insights shape care. Training should teach staff to notice when an output feels a little too clean rather than just how to operate the tool. The real test is whether clinicians still trust their own read when something in the record doesn’t add up. 

Going back to that intake form example from the beginning: The clinician reviewing it did not need an AI system to tell them the chart looked fine. They needed one that would not have smoothed over the line that gave them pause in the first place. That’s the standard behavioral health must live up to.

About Michael Arevalo

Michael Arevalo, Psy.D., PMP, is the Director of Clinical Strategy at Core Solutions, a company that has spent more than 25 years developing behavioral health and IDD EHR technology and today supports care for more than 500,000 individuals. He brings a background in clinical psychology and project management to his work guiding how AI and other emerging technologies are evaluated and adopted across Core’s platform. Dr. Arevalo focuses on ensuring new capabilities strengthen, rather than undermine, the clinical judgment and human relationships at the center of behavioral health and IDD care.