< + > Great Stats from Epic UGM

In case you missed it, we shared our roundup of announcements from Epic UGM.  One of the other parts I love at Epic UGM is all of the stats they share about the impact that Epic and their users are having on healthcare.  Below you’ll find our compilation of the various stats that were shared at the event:

• Epic customers train over 90% of medical students
• 17 countries in the Epic community; Germany is the newest as Charité joins
• 1.4 million clinicians assisted by AI in Epic each month
• Monthly gen AI activity in July 2025 was 50 million and is now 2 billion as of July 2026
• Art clinician and nurse summaries are in use at more than 300 health systems
• Chart with Art is live in more than 70 unique specialties and multiple clinical roles
• Chart with Art for nursing is live at 11 health systems
• More than 1/3 of Emmie conversations happen after-hours
• Professional Billing Coding Assistant reduced coding-related denials by 33% across 160 organizations
• In Basket Art reduced time spent reviewing patient messages by 50% (Texas Children’s)
• Ask Emmie – 1,000+ hours saved for call center staff over 10 months (Ochsner Health) and 73% fewer billing-related In Basket messages (Community Health Network)
• Dynamic Scheduling Templates saw a 16% increase in online availability (OhioHealth)
• Patient Flow saw a 15% increase in bed days using AI Transfer Assistant (Loma Linda University Health)
• MyChart Central has 346 organizations live in 50 states and available to 115 million patients
• SlicerDicer SideKick reduced time spent creating queries by up to 85% (RWJBarnabas Health)
• Epic Staff did 31,126 R&D Immersion Days in 19 countries since last UGM
• Epic used to release new versions every 18 months, now they do so every 3 months
• A single quarterly Epic release now carries roughly the enhancement volume of an old 18-month
  release. The latest release contained 27% more code than the same version a year ago

In the last year…

• When ordering or administering a medication, clinicians changed course 224 million times based on an advisory from Epic
• 127,000 gallons of blood were saved in the last year by using automatic order adjustments in Epic to combine draws and avoid unnecessary sticks for patients
• 413,000 lung nodules were identified in radiology reports using AI for discrete follow-up tracking helping 2,050 patient start treatment for lung cancer earlier
• Dentists changed medications 278,000 times based on warnings shown in Epic
• Patients were seen an average of 30 days sooner with Fast Pass in MyChart
• Patients saved $300 million on medications when providers switched to lower-cost alternatives thanks to alerts in Epic
• 9.3 billion patient records exchanged across 50 states and 10 countries – 50% between Epic & non-Epic – 90% of Epic organizations are live or installing TEFCA
• 21,000 duplicate imaging tests were prevented thanks to images exchanges across health systems

Implementation and Technical Service Stats

• 300k new users live
• 35 full go-lives
• 460 Add-ons
• 35k Gold star featured turned on resulting in 2000 more Gold Stars
• 1,500 upgrade complete

Cosmos and Cosmos-enabled insights:

• 320 million unique patients, 23 billion encounters, 99 billion lab results, 186 million surgeries, 170 million home care visits, 25 million cancer cases, 18 million rare disease patients, 15 million mom-baby links in Cosmos.
• More than 220 papers published (10 journals) based on research from Cosmos
• Look-Alikes used more than 25,000 times last year.
• Best Care Choices for My Patient live at more than 60 organizations.
• 20 customers are early adopters of Cosmos Curiosity.
• 56 organizations live with Best Care Choices for My Patient
• 1 million monthly admissions use Cosmos Median Length of Stay

Those were most of the stats shared at Epic’s 2026 UGM.  Which stats stood out to you?

< + > The Role of Data Governance and Master Data Management in Ensuring Accuracy and Consistency Across Back Office Systems

Data is a major part of everything we do in healthcare; back-office health IT systems are no exception to this. There is a tremendous amount of data that is needed to successfully run all claims processing, medical billing, patient scheduling, etc. Gathering data isn’t usually the issue; however, governing and managing it is. For example, it’s not very hard to create a bill for rendered services, but what is hard is tracking what was paid in full, what is on payment plans, what charges are in dispute, and making sure that information is only accessible to the relevant parties.

To get a better picture of the importance of data management in back office health IT systems, we reached out to our wonderful Healthcare IT Today Community to ask — what role do data governance and master data management play in ensuring accuracy and consistency across back office health IT systems? Below are their responses.

Ashley Murgatroyd, Director of Healthcare Strategy at LexisNexis Risk Solutions
Data governance and master data management are critical to back-office health IT systems because they create a single, consistent foundation for patient data across fragmented administrative workflows. By resolving identities and eliminating duplicate records, organizations can improve data accuracy, streamline claims processing, and reduce costly errors tied to misidentification. These capabilities help maintain a cohesive, longitudinal view of patient records as they move through billing, eligibility, and other back-office functions, which can improve operational efficiency and support more reliable outcomes.

Ultimately, strong governance and master data management practices enable health systems to reduce financial leakage, protect sensitive data, and ensure consistency across the systems that power day-to-day administrative operations.

Denis Whelan, CEO at Documo
They’re critical. Automation is only as good as the data governance frameworks backing it up. Data governance and master data management are foundational business drivers. When you invest in clean, governed master data, you create the trust required to fully embrace automation—allowing you to scale your back office, wipe out administrative burnout, and protect the financial and operational health of your organization.

Even the most advanced AI and Machine Learning models encounter ambiguity—like a smudged, handwritten fax or a poorly scanned invoice. Data Governance dictates the exact protocol for what happens when data drops below a specific confidence threshold.

Instead of letting a system guess and corrupt the database, a strong governance framework should route that specific file to a human-in-the-loop workflow. A team member verifies or corrects the record, and that human intervention is used to train the model to be more accurate next time. This ensures that the master database remains untainted while maintaining high operational velocity.

John Squeo, Senior Vice President at CitiusTech
Without a trusted, enterprise-wide master record for entities like patients, providers, vendors, and cost centers, back-office analytics produce conflicting outputs that erode executive confidence and slow decision-making. Data governance and MDM platforms, including Microsoft Purview, Databricks Unity Catalog, Snowflake Horizon, Informatica, Reltio, and Profisee, are increasingly essential for maintaining a single source of governance across fragmented Health IT landscapes. Strong data governance frameworks establish accountability structures, including data stewards, ownership policies, and quality SLAs that sustain accuracy beyond the initial implementation.

In value-based care environments especially, flawed provider or payer master data directly translates into misdirected payments and compliance risk. Data governance is particularly critical when modernizing with AI to establish data provenance, traceability, and governance of metadata collation that drives user trust in generated insights and reliability in automated processes. Forward-looking organizations are now treating data governance and MDM as foundational infrastructure for AI readiness, recognizing that model quality is only as good as the data underneath it.

Kevin Erdal, President, Advisory Services at Nordic
Healthcare organizations generate massive amounts of operational, financial, workforce, and supply chain data, but without strong governance structures, they often struggle with duplicate records, inconsistent definitions, and fragmented reporting.

Master data management establishes a single source of truth for critical enterprise data, including vendors, suppliers, employees, locations, the chart of accounts, and operational metrics. This improves consistency across systems and enables more accurate reporting, forecasting, and analytics.

Strong data governance also helps organizations build trust in their data. When finance, HR, supply chain, and clinical teams are aligned around standardized definitions and ownership models, leaders can make decisions with greater confidence.

This becomes even more important as organizations invest in AI and advanced analytics. AI tools are only as effective as the quality and consistency of the underlying data. Organizations that prioritize governance and data integrity are better positioned to scale automation, improve interoperability, and generate meaningful operational insights.

Monte Sandler, Chief Operating Officer at WebPT
Data quality is foundational in healthcare. If patient or payer information is inaccurate at the front end, those issues create denials and delays later in the revenue cycle. Strong data governance helps organizations standardize how information is captured and updated, while also making it easier to identify patterns and root causes across workflows. Reliable data is what makes proactive, “shift left” strategies possible.

Rachel Blum, VP, Emerging Markets and Partners at Verato
Highly accurate MDM is essential and absolutely critical to ensure data accuracy and consistency across not just back office systems, but all Health IT systems. The downstream impact of poorly executed MDM is flawed reporting, compliance risk, and operational inefficiencies that can ripple across the organization. At its worst, mismanaged data erodes trust in the system entirely, forcing teams to rely on manual workarounds instead of the technology meant to support them. Trying to scale to support AI? Better get MDM right, or AI will quickly expose these flaws in your data infrastructure.

Sherri Atchley, AVP for Altera Managed Services at Altera Digital Health
Data governance and master data management play critical roles in ensuring accurate patient matching, workflow integrity, financial reconciliation, and operational consistency across integrated health IT systems. Without strong governance practices, organizations face increased risks of duplicate patient records, incorrect patient associations, payment posting discrepancies, delayed processing, and downstream operational errors.

As automation expands into back office workflows, such as inbound fax filing or remittance/payment posting, maintaining strong governance standards and audit controls becomes increasingly important to ensure accurate document routing, indexing, reconciliation, and financial integrity.

While robotic process automation (RPA) can help enforce process consistency and reduce manual errors, organizations still require strong governance frameworks, clearly defined business rules and ongoing monitoring to maintain high-quality operational and financial data across integrated applications.

Dr. Scott Schell, Chief Medical Officer at Cognizant
Data governance is now operationally essential. Organizations cannot scale analytics, automation, or AI with inconsistent enterprise data. Master data management creates consistency around identities, locations, workforce structures, and financial attribution. Governance establishes accountability for maintaining that consistency over time.

So many great ideas 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 data governance and master data management play in ensuring accuracy and consistency across back office health IT systems? Let us know over on social media, we’d love to hear from all of you!

< + > Agentic AI in Healthcare Operations: A Build-vs-Buy Framework for Health-System CIOs

The following is a guest article by Chandresh Patel from Bacancy Technology

Agentic AI is no longer just a concept for healthcare. Many health systems are already exploring how AI agents in healthcare can automate administrative and clinical workflows. However, the bigger question today is whether to build an agentic AI solution in-house, buy a ready-made one, or combine both approaches.

Choosing the right approach has become one of the biggest challenges for healthcare leaders as they move from AI experimentation to enterprise-wide adoption.

According to research conducted by Microsoft and The Health Management Academy, published in the NEJM AI in January 2026, found that 43% of health system leaders are testing or piloting agentic AI. Yet only 3% have deployed an AI agent into a live clinical or operational workflow.

That gap between the pilot and deployment is where most organizations struggle, and it’s rarely a technology problem. It’s a trust problem.

Giving an AI agent the ability to schedule patients, update an EHR, submit claims, or coordinate care is very different from deploying a chatbot. Every action it takes must be accurate, secure, easy to track, and meet clinical and regulatory requirements.

For CIOs evaluating this shift right now, the real decision is how much operational responsibility they are ready to hand an AI agent, what governance needs to be in place, and which implementation approach best fits the organization’s long-term strategy.

These are the conversations we have most often with healthcare leaders exploring enterprise AI. Thus, before choosing a platform or starting development, let’s understand why agentic AI in healthcare changes the way health systems approach the build-versus-buy decision.

What Makes Agentic AI in Healthcare Different From Traditional Build vs. Buy Decisions?

Healthcare organizations have been making build-versus-buy decisions for years. Agentic AI changes that decision because it does more than provide information. It can take action and complete tasks on its own.

While a chatbot answers a query, an agent understands the purpose, makes a decision on what must be done, reaches into multiple systems, and executes the process without manual monitoring.

Think of a denied insurance claim, for example. Rather than just recognizing the problem, an AI agent could confirm eligibility, retrieve the required documents, fix coding mistakes, ensure the claim follows the right approval process, and refile the claim.

That shifts the evaluation from comparing software features to evaluating operational responsibility.

Before selecting any solution, CIOs should answer three fundamental questions:

• Can the agent securely interact with every system required to complete the workflows, whether that’s Epic, Oracle Health, or a claims platform?
• Can every action it takes be reconstructed later for a compliance review?
• And does the workflow reflect something specific to how your organization delivers care, or is it a problem every health system solves the same way?

Where the Evaluation Usually Breaks Down

The biggest mistake CIOs make isn’t choosing the wrong vendor or investing in the wrong technology. It’s assuming that if an AI agent can complete a workflow, it’s ready for production.

A Black Book Research survey of 182 U.S. hospital leaders, reported by Presidio following HIMSS26, found that only 22% feel confident they could produce a complete, auditable explanation of an AI agent’s decision for a regulator within 30 days.

That’s the number CIOs should be reacting to, not the adoption hype. If a vendor can’t show approval logs, role-based access controls, and a clear record of what an agent did and why, the deployment speed they’re selling doesn’t matter. Ask for the audit trail before you ask for the demo.

Build, Buy, or Hybrid: How Do the Options Actually Compare?

The table below is the framework we walk through before any technical conversation starts.

Decision Factor	Buy	Build	Hybrid
Deployment time	Weeks	Months	Weeks to months
Workflow fit	Standard workflows	Custom workflows	Standard + custom
EHR integration	Vendor-supported	Fully customized	Mix of both
Compliance & audit	Vendor-managed	Fully controlled	Shared responsibility
Maintenance	Vendor handles it	Internal team	Shared
Flexibility	Limited	High	High
Upfront cost	Lower	Higher	Moderate
Vendor lock-in	Higher	None	Lower
Best for	Scheduling, intake, basic RCM	Clinical workflows, payer rules, care pathways	Fast deployment with custom logic

Note: Budget often influences the first decision. Buying is usually the less expensive option to get started, while building costs more initially but gives you greater ownership over time. However, without a skilled AI and integration team, maintaining a custom solution can quickly become a challenge.

Why the Hybrid Model Wins for Most Health Systems

Few health systems need to commit to one approach forever. What tends to work best is using a platform to handle standardized, high-volume workflows like patient intake, eligibility checks, and appointment scheduling, while relying on custom development for the workflows tied to a specific payer contract, clinical protocol, or care pathway that no vendor platform was designed to handle.

This is exactly the gap we close; we offer custom healthcare software development services to build and extend AI solutions around your existing platforms, giving you the flexibility to support unique workflows without replacing the systems you already use.

Instead of forcing you to choose between an off-the-shelf platform and a fully custom build, we help you combine both approaches to gain speed without giving up control.

How Bacancy Technology Helps Health Systems Build Production-Ready Agentic AI

With more than a decade of expertise in offering Healthcare IT services, we’ve learned that getting an agent to work in a demo is one thing; deploying it inside a health system’s real compliance rules and real EHR systems is another. That’s the biggest difference between a successful pilot and enterprise-wide adoption, and it’s where our expertise delivers the most value.

• Instead of replacing the systems you already use, we integrate with Epic, Oracle Health, MEDITECH, Cerner, FHIR R4 APIs, HL7, and your existing scheduling and revenue cycle platforms. This allows AI to work within your current environment without forcing you to replace the tools your teams already depend on.
• Approvals, logging, role-based access control (RBAC), and security guardrails are included in the initial release. This is how we achieve compliance with zero delays in rollouts or rollbacks.
• Prior authorization, denial management, patient access, scheduling, clinical documentation, and care coordination all have different operational challenges. We build around those workflows rather than trying to fit healthcare into a generic AI platform.
• Whether the right fit is Azure OpenAI, AWS Bedrock, Google Vertex AI, LangGraph, CrewAI, MCP, or a secure RAG architecture, we choose the technology based on your business and clinical requirements, not the other way around.
• Some organizations need help evaluating commercial platforms. Others need custom development tied to payer requirements or clinical protocols. Most projects combine both, using a vendor platform with a custom layer to move faster without giving up control of critical workflows.

When the development and implementation of your healthcare system has advanced beyond the pilot phase, this is the point where our discussions typically start. We help you determine whether a build, buy, or hybrid approach best fits your operational, technical, and compliance goals.

If you’re evaluating agentic AI in healthcare for production, our healthcare AI specialists at Bacancy Technology can help you assess your workflows, existing systems, and compliance requirements to determine whether a build, buy, or hybrid strategy best fits your organization.

Conclusion

When it comes to agentic AI in healthcare now, the issue is not whether to build or buy; the critical question is whether the model you choose will be safe to use, able to interact with your existing systems, and sustainable beyond the pilot stage.

The decision should come from your workflows and your compliance requirements, not from which option looks fastest on paper.

At Bacancy Technology, we help health systems plan and implement healthcare AI solutions that fit their workflows, existing systems, and compliance requirements. Whether you need to evaluate a vendor, build a custom solution, or consider a hybrid approach, our team can help you choose the right path and deliver solutions that work in real-world healthcare environments.

About Chandresh Patel

Chandresh Patel is a seasoned technology professional and passionate writer at Bacancy Technology, with years of experience helping businesses navigate the ever-evolving digital landscape. With a strong background in software development and IT strategy, he specializes in delivering technology solutions for the healthcare and finance sectors, translating complex technical concepts into practical, actionable insights for readers of all backgrounds. Chandresh has contributed to numerous industry publications, sharing his expertise on emerging trends, compliance-driven innovation, and digital transformation strategies that drive growth for healthcare providers and financial institutions alike. When he’s not writing, he enjoys mentoring young professionals and staying up to date with the latest advancements in technology.

Bacancy Technology is a proud sponsor of Healthcare Scene.

< + > Blaze.tech Raises $8.5M Pre-Seed | HealthSnap Secures $25 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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Blaze.tech Raises $8.5 Million Pre-Seed, Marking First Investment from New Healthcare Venture Firm Friale

Announcing $8.5 Million in Pre-Seed Funding, Blaze Enables Healthcare Teams to Create HIPAA-Compliant Custom Software with AI

Blaze.tech (Blaze), the AI app building platform purpose-built for healthcare, today announced an investment from Friale, a new healthcare-focused venture firm founded by the family behind HCA, the nation’s largest hospital operator. Blaze is Friale’s first investment, and the round adds $5 million additional capital to Blaze’s pre-seed, bringing the total to $8.5 million.

“Our mission is to make building healthcare software radically easier, so anyone with an idea to improve healthcare can have the power to build it,” said Nanxi Liu, Co-Founder and Co-CEO at Blaze.tech. “Every week, we see someone build a prototype with AI, demo it to a customer, and then hit a wall because the app isn’t connected to systems healthcare runs on and doesn’t have the compliance that real patient data demands. We built Blaze for that last mile—production apps that handle real patient data, write back into EHRs, and send prescriptions nationwide.”

“Blaze can generate multi-portal applications, fully structured relational databases, and end-to-end workflows in minutes. But in healthcare, speed only matters if you can trust what you ship,” said Tina Wojcik, Co-Founder and Co-CEO at Blaze.tech. “That’s why we pair AI generation with deterministic, auditable workflows, guardrails on every AI action, and separate development, staging, and production environments to protect live patient data. Healthcare teams get the velocity of AI with the control of enterprise software baked in from day one.”

From individual doctors to Fortune 500s, healthcare organizations use Blaze to build HIPAA-compliant solutions tailored to how they operate. With Blaze, patient portals, scheduling, custom EMRs, billing, and prescribing workflows are optimized for each organization’s unique operations. Kiaora runs its entire online GLP-1 and hormone-therapy prescribing business on Blaze; The Care Connexion runs its therapist-referral platform on it. Larger provider groups use Blaze to automate clinical workflows inside their EHRs…

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

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HealthSnap Secures $25 Million Growth Financing to Accelerate AI-Powered Virtual Care Management Leadership

New Senior Secured Facility Validates Company’s Category Leadership and Fuels Next Phase of AI Innovation and Enterprise Growth

HealthSnap, the pioneer and category leader in AI-powered virtual care management, today announced it has secured a $25 million senior secured growth financing facility led by Eastward Capital Partners, LLC. The new facility strengthens the company’s balance sheet, refinances existing debt, and provides significant additional capital to accelerate artificial intelligence innovation, expand commercial operations, and scale deployment of its Advanced Primary Care Management (APCM) platform across the nation’s leading health systems.

The financing follows a period of exceptional growth and market momentum for HealthSnap as healthcare organizations increasingly adopt AI-enabled solutions that improve patient outcomes, reduce costs, strengthen clinical efficiency, and extend care beyond the traditional clinical setting.

HealthSnap has helped define the rapidly emerging virtual care management category by bringing together Remote Patient Monitoring (RPM), Chronic Care Management (CCM), Principal Care Management (PCM), Advanced Primary Care Management (APCM), AI-powered clinical workflows, enterprise analytics, reimbursement optimization, and care coordination into a single, EMR-Integrated, intelligent platform that enables healthcare organizations to proactively manage patients at scale – unlocking capacity without adding headcount.

Today, HealthSnap supports more than 80,000 active patient programs across 200 health systems and physician organizations, with the company projecting more than 100,000 active patient programs by the end of 2026. HealthSnap’s platform currently ingests 2 patient measurements every second, and patients enrolled in HealthSnap’s programs see a 97% reduction in alert frequency by their twelfth month, demonstrating remote patient management at scale.

HealthSnap partners with many of the nation’s leading healthcare organizations, including Prisma Health, AdventHealth, Ascension Health, Sentara Health, Tampa General Hospital, UnityPoint Health, Baptist Health South Florida, Mount Sinai Medical Center, and University Hospitals. Even more importantly, several of these organizations, including Sentara Health, Tampa General Hospital, and UnityPoint Health, have chosen to invest strategically in HealthSnap, reflecting their confidence in the company’s technology, leadership, and long-term vision…

Full release here, originally announced August 6th, 2026.

< + > 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.