Sunday, November 8, 2026

< + > Bonus Features – November 8, 2026 – 48% of Americans have used AI to review their health insurance options, 68% would independently verify AI-generated medication details, plus 34 more stories

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

News

Stats

Partnerships

Products

Implementations

Company News

People

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

 



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Saturday, November 7, 2026

< + > Weekly Roundup – November 7, 2026

Welcome to our Healthcare IT Today Weekly Roundup. Each week, we’ll be providing a look back at the articles we posted and why they’re important to the healthcare IT community. We hope this gives you a chance to catch up on anything you may have missed during the week.

What’s Next for eHealth Exchange? President and Executive Director Doug Dietzman sat down with John Lynn to outline the organization’s priorities for 2027: Engage with payers, expand beyond treatment-focused exchange, and strengthen relationships with federal partners. Read more…

Using Ambient AI to Reduce Physician Burden. SVP and CIO Mark Galea at Louisiana’s Willis Knighton Health, plus Commure’s Ian Shakil, got together with John to describe the importance of finding a vendor with a mature solution and a willingness to partner, not just one with EHR integrations. Read more…

How Virginia’s Augusta Health Automated Document Routing. CIO Leigh Williams, along with Audrey Brislin at Forward Advantage, talked to John about replacing digitized document routing with automation for use cases that are consistent and predictable – and boring. Read more… 

Advancing Healthcare AI Governance and Patient Identity Management. John summarized his day at Rhapsody Connect; highlights included doing identity management at scale, training AI on clean data, governing APIs, and supporting information exchange. Read more…

A Look at Workday’s ERP in Healthcare. John sat down with Keith Lohkamp to talk about Workday’s role helping health systems manage the business operations that ultimately support patient care. It starts with connecting clinical and operational data. Read more…

East Georgia Healthcare Center Discusses eClinicalWorks’ Pharmacy Solution and AI. COO Peyton Frye connected with John and chatted about bringing new pharmacy operation capabilities and AI tools into existing workflows and synchronizing data across applications. Read more…

Oracle Previews an Intent-Driven EHR Strategy. SVP and Chief Medical Officer Bharat Sutariya sat down with Colin Hung to talk about how to deliver next-generation clinical intelligence without forcing health systems into another painful data migration. Read more…

Life Sciences Today Podcast: Earlier Than Early Breast Cancer Detection. Danny Lieberman talked to Sivan Sadan at Pink Star Technologies about meeting strict U.S. privacy requirements to implement early screening of breast MRI. Read more…

CIO Podcast: Reliability in AI Adoption. Data scientist Renu Sara Nargund at UT MD Anderson Cancer Center joined John to discuss why “human in the loop” isn’t enough to solve the reliability problem with AI, especially in oncology. Read more…

Today’s ACO Technology May Not Be Enough for What’s Coming. ACOs now have a much bigger charge to manage specialty care and adopt CMS tools to negotiate rates. To support that, Theresa Hush at Roji Health Intelligence outlined sikx essential layers of value-based care technology. Read more…

Provider Enrollment: A Data Problem Hiding in the Denial Queue. Sooner is better for reconciling provider records, Madison Gardner at AMS Solutions said. Information can exist in multiple locations, and claims can fail even when EHRs and clearinghouses work exactly as designed. Read more…

Automation and AI Are Quietly Rebuilding the Hospital Back Office. Since the back office is data-rich, highly repetitive, and directly connected to financial performance, Paige Schwein at Healthrise said it offers a clear opportunity for effective AI adoption. Read more…

The Hidden Risks of Using Personal Cell Phones for Patient Communication. While HIPAA doesn’t prohibit the use of personal devices, the compliance question is whether an organization protects ePHI that the device creates, receives, stores, or transmits, noted Pankaj Gupta at iPlum. Read more…

Clinical AI Needs Version Control, Not Just Validation. Because AI tools can be updated far more frequently than traditional clinical technology, AI researcher Dr. Michael T. Neely said it’s critical for organizations to keep close tabs on how changes to clinical AI tools may impact performance, risk, or workflow. Read more…

This Week’s Health IT Jobs for November 4, 2026: Arkansas-based Forrest City Medical Center is looking for a CEO; so is Illinois-based Olympia Fields Hospital. Read more…

Bonus Features for November 1, 2026: 91% of patients want their permission required when AI is used for diagnosis; plus, 64% of providers plan to deploy AI for claims and denials management. Read more…

Funding and M&A Activity:

Thanks for reading and be sure to check out our latest Healthcare IT Today Weekly Roundups.



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Friday, November 6, 2026

< + > Health System Zombie, Treatment Coverage, and General Medicine – Fun Friday

Happy Friday everyone! You made it through another great week. We hope you have accomplished all you wanted and are ready for a great weekend. That means it’s time for another edition of Fun Friday where we try to make you smile as you head into the weekend.

This felt like an appropriate one for Halloween. Does anyone else feel like this looks like the healthcare system? The only thing I’d add is a lot more than 2 people or groups are pulling at it.

I probably shouldn’t laugh at this one, but I did. Sometimes coverage feels this way.

This one is so dumb it’s funny. There’s an interesting balance in healthcare between specialist and generalist.

That’s all for this week. We hope you enjoyed and that you’ll tune in next week for some more great health IT content.



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< + > Earlier Than Early Breast Cancer Detection – Life Sciences Today Podcast Episode 86

We’re excited to be back for another episode of the Life Sciences Today Podcast by Healthcare IT Today. My guest today is Sivan Sadan, Co-Founder and CEO at Pink Star Technologies. In this episode, I sit down with Sadan to talk about how Pink Star is making breast cancer detection earlier than early.

Check out the main topics of discussion for this episode of the Life Sciences Today podcast:

  • Tell us about your journey to Pink Star. How did you end up doing an AI startup for early screening of breast MRI?
  • How do you create value?
  • Who are your customers?
  • Who pays you, and how do you plan to charge people for using your system?
  • What’s your superpower? What’s your moat?
  • US privacy requirements are tough, so how did you get passed by Mount Sinai with this?
  • Breast cancer is known to be sensitive to race and ethnicity. How does that influence your AI model?
  • What are three things you want to do for your customers in the next twelve months?
  • What is the biggest anti-pattern in your industry?
  • What is the closest you’ve come to a surprise that would have cost you the company?
  • How many salespeople do you have?

Subscribe to Danny’s newsletter to get strategic patterns for life science leaders building a defensible business.

Be sure to subscribe to the Life Sciences Today Podcast on your favorite podcasting platform:

Along with the popular podcasting platforms above, you can Subscribe to Healthcare IT Today on YouTube.  Plus, all of the audio and video versions will be made available to stream on Healthcare IT Today. As a former pharma-tech founder who bootstrapped to exit, I now help TechBio and digital health CEOs grow revenue—by solving the tech, team, and go-to-market problems that stall your progress. If you want a warrior by your side, connect with me on LinkedIn.

If you work in Life Sciences IT, we’d love to hear where you agree and/or disagree with our takes on health IT innovation in life sciences. Feel free to share your thoughts and perspectives in the comments of this post, in the YouTube comments, or privately on our Contact Us page. Let us know what you think of the podcast and if you have any ideas for future episodes.

Thanks so much for listening!



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< + > The ACO Technology You Have Today May Not Be Enough for What’s Coming

The following is a guest article by Theresa Hush, Co-Founder and CEO at Roji Health Intelligence

The value-based care world—for which your ACO was built—has greatly altered. ACOs now have a much bigger charge to manage specialty care for their patients and to adopt CMS tools to negotiate rates with high-performance networks. The TEAM payment model is live, and ACOs have a role. ASM arrives in 2027 with more ACO investment. LEAD will reshape the ACO model for the next decade. Ahead lies a deeper role in care management, quality outcomes, and coordinated care across all types of providers, not just ACO participating providers. The same high-risk primary care patient sitting in your ACO panel is very likely the same person walking into a TEAM surgery or an ASM episode.

This new reality demands better technology. But here’s the honest truth: Many ACOs have no platform now and are still working their services from claims data with no aggregated data to back it up. Further, most value-based care platforms are not yet organized to handle all the functions your ACO will need.

Don’t lose time researching the ultimate system. Begin a process now that will enable your ACO to meet this central need: a unified hub for value-based care that can draw from every relevant data source to give your team a single coherent view of each patient, then support the interventions for that patient in each episodic or condition-based payment model. You need to be building toward that hub and evaluating your current tools against those needs if your ACO is to be at the center of your value-based care ecosystem.

The Essential Layers of Your VBC Technology

1. Your Foundation: A Central Database to Integrate Data from EHRs, Claims, Finance, Population Health, Episode Analytics, and Risk Adjustment Algorithms

Many ACOs discovered shortfalls in their data mastery during implementation of APP Reporting; they struggled to aggregate clinical data from diverse EHR systems across a heterogeneous practice mix. Some resorted to Medicare CQMs or chose eCQMs to avoid data hassles, but in the end both strategies wasted their data resources. As CMS moves to FHIR-based digital quality measures, your platform must have a credible, specific path toward FHIR adoption and seek deep clinical data. 

2. A Bifocal Lens on Total Cost of Care and Episodic Analytics

Patients most at risk in your ACO panel are likely those heading into a TEAM surgery or an ASM episode. A patient with uncontrolled hypertension, Type 2 diabetes, and coronary artery disease doesn’t stop being your ACO’s responsibility the moment a surgeon schedules a CABG. In fact, that’s exactly when your ACO’s role becomes most critical—and most financially consequential. The comorbidity burden in CABG patients is high, the complication rates are significant, and the opportunity for pre-surgical intervention to prevent complications is real.

This is precisely where ERAS (Enhanced Recovery After Surgery) protocols are so powerful and so underused. Hospital adoption has been slow because ERAS is operationally difficult without the right infrastructure. But your ACO, with visibility into a patient’s longitudinal primary care record, is uniquely positioned to facilitate that process. When should an ACO begin preparation for a TEAM surgery? It must be long before the surgical date, so you can hand a better-prepared patient to the surgical team. Validating patient conditions and pre-treatment of patient risks improves outcomes and reduces episodic costs. Your technology must be able to support this kind of coordinated view, spanning primary care, specialty care, and the episode window, without losing the patient in a hand-off between disconnected systems. 

3. Quality Reporting That Keeps Pace With CMS—Easily

Quality performance is not a compliance activity, but a direct multiplier on shared savings. APP Plus measures will grow, and MIPS Value Pathways are expanding to new specialties and may become mandatory. ASM will bring its own quality requirements in 2027. Your hub must keep pace with this trajectory automatically, not as a special project every fall when CMS releases a new final rule.

4. Post-Acute Care Visibility—Close the Black Hole

Post-acute care is an expensive and often poorly managed transition point in both Total Cost of Care models and TEAM episodic payments. For lower extremity joint replacements—the highest-volume TEAM procedure—the difference between a well-managed SNF referral and a poorly chosen one can mean days of unnecessary skilled nursing care, avoidable readmissions, and thousands of dollars in episode cost overruns. Your ACO and your TEAM hospital share a vested interest in solving this together. Your technology hub must be able to show you post-acute utilization patterns by facility, by referral source, and by episode type—so that you can build a preferred network based on performance data, not habit. Right now, many ACOs are flying blind on post-acute.

5. Specialty Network Intelligence for the LEAD Era

LEAD’s CMS-Administered Risk Arrangements (CARA) create a formal mechanism for ACOs to enter episode-based risk sharing with specialist groups. This is new territory, and the data requirements are genuinely different from what ACOs have managed before. To make CARA work, your ACO needs to be able to profile specialists by cost and quality performance across episode types, identify which specialty referral patterns are driving cost variation in your attributed population, and model what a preferred specialist network would do to your performance. These are not capabilities most ACO platforms were built for. But they are capabilities your hub must develop—because specialty costs are where the next generation of ACO savings will be won or lost.

6. Patient-Centric Care Management and Interventions

The components above are focused primarily on succeeding in payment models, or the ACO and its providers. But key ACO functions for patients, like improvement plans, specialty referral management, care management, and population health, are among the top reasons that ACOs need the functionalities that key clinical and other data provide. Interventions, for example, that are identified for patients in advance of a TEAM surgery or coming out of a condition-based episode, must be undertaken on a patient level, not a disease level. The ultimate purpose of a value-based care technology is to improve the patient’s status and his or her risks. Thus, the technology must be able to provide a window not only on all the data, payment models, and costs associated with an individual patient, but also to deploy corrective actions for that patient. Especially interventions, pre-surgical programs, and chronic disease management programs must be patient- and not disease-centric, so that the intervening providers— population health team, clinicians, health coaches, registered dietitians, and so on—have an organized plan for each patient.

No one expects your technology to do all this perfectly today. The payment models are new, the data standards are still evolving, and even the most sophisticated VBC platforms are building toward this vision, but have not yet fully arrived. But the vision itself is not optional. An ACO that is still evaluating technology purely by its claims analytics capability, or its quality reporting module in isolation, is asking the wrong questions in 2026.

The right question to ask: Does this platform have the architecture and the roadmap to become the central hub your ACO needs—connecting primary care data, specialty episode data, quality reporting, post-acute performance, and financial reconciliation into a single, coherent view of every patient? If the answer is yes, you have a foundation worth building on. If the answer is uncertain or evasive, that uncertainty will compound with every new payment model CMS introduces.

About Theresa Hush

Co-Founder and CEO at Roji Health Intelligence, Theresa Hush is a health care strategist and change expert with experience across the health care spectrum, including public, non-profit, and private sectors.



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< + > Midstream Health Raises $20M Series A | nPhase Secures $30 Million in Series D Funding

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.

Midstream Health Raises $20M Series A to Strengthen the Financial Sustainability of America’s Health Systems

AI Platform Now Optimizes Financial Decision-Making Across Health Systems Representing More Than $100 Billion in Annual Operating Expenses and 250 Hospitals

Midstream Health, the autonomous financial operations platform for health systems, today announced a $20 million Series A as it expands across a customer network representing more than $100 billion in annual operating expenses and over 250 hospitals nationwide. Midstream helps these institutions find and recover margin across both revenue and cost, strengthening the financial capacity required to continue investing in care and serving their communities.

The financing round was led by Valtruis with continued participation from Andreessen Horowitz (a16z), Foundry, and CommonSpirit Ventures, bringing Midstream’s total funding to $29.2 million. Fairview Health Services and Keck Medicine of USC are among the newest health systems to join the platform, alongside CommonSpirit Health, Mount Sinai Health System and Houston Methodist.

This announcement comes as health systems are facing a financial sustainability crisis, fighting to protect razor-thin margins. More than 110 rural hospitals have closed over the past 20 years, and another 720 — representing roughly a third of all rural hospitals — are at risk of closure. Much of what’s slipping away is money health systems have already earned, buried in their own contracts and spend. Recovering that margin is about more than improving the bottom line; it gives health systems greater capacity to invest in care, serve their communities, and deliver on the mission their patients depend on.

“In this environment, health systems need solutions that can improve their financial position quickly,” said Mike Spadafore, Managing Director of Valtruis…

Full release here, originally announced October 29th, 2026.

nPhase Secures $30 Million in Series D Funding to Drive Global Expansion of AI-Native Clinical Data Platform for Life Sciences

Investment Will Scale nPhase’s Enterprise Clinical Data Business and Accelerate Expansion of Its Statistical Computing Environment (SCE), Unified Data Management System (UDMS), and Agentic AI Capabilities Across the Clinical Data Lifecycle

nPhase, Inc., today announced the closing of a $30 million Series D funding round led by Viking Global Investors to accelerate the company’s AI-native clinical data platform for pharmaceutical sponsors seeking to unlock the full potential of their data and power AI at scale. Viking Global Investors is an investment firm managing more than $54 billion in capital across public and private investments. The financing represents nPhase’s first equity capital raise since 2017, reflecting the company’s disciplined approach to capital management and its ability to build and expand its business without additional equity financing for nearly a decade.

“We see a significant opportunity to modernize how the life sciences industry manages and uses clinical data,” said Levi Malik, a Principal at Viking Global Investors. “nPhase combines something rare in the AI market: an established foundation in clinical research, deep understanding of regulatory requirements, and a clear vision for enterprise-scale AI. We believe this combination positions the company well for its next stage of growth.”

The funding follows the launch of the nPhase.ai clinical data platform, which unifies its Unified Data Management System (UDMS) and Statistical Computing Environment (SCE) to connect the clinical data lifecycle from study startup through regulatory submission. Today, that journey can take months and require navigating numerous disconnected systems and manual handoffs. nPhase has built a unified platform that connects the clinical data lifecycle end to end, so data becomes…

Full release here, originally announced November 2nd, 2026.



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Thursday, November 5, 2026

< + > Provider Enrollment is a Data Problem Hiding in the Denial Queue

The following is a guest article by Madison Gardner, President at AMS Solutions, Inc.

A claim can pass every check a practice controls and still come back unpaid. The visit is documented, the codes are supported, and the clearinghouse accepts the file. Then the payer checks the clinicians on the claim against its enrollment records, which say something else.

Health IT teams rarely own that failure, because provider enrollment tends to be filed under paperwork. It behaves more like master data: the same facts about one clinician, held in several systems, each with its own update rule and its own deadline. When the copies disagree, the EHR and clearinghouse can work exactly as designed while the claim fails.

Four Records Describing One Clinician

The first is the national provider identifier (NPI) record. A covered provider must report changes to its required NPI data within 30 days, and a Medicare claim must carry the NPI of the billing provider and of any other provider identified on it.

The second is the Medicare enrollment record in PECOS. Physicians and their organizations have 30 days to report an added, moved, or closed practice location, and 90 days for most other changes.

The third is the clinician’s profile in the CAQH Provider Data Portal, now operated by DataSpring. Health plans use it for credentialing, enrollment, and directory management, and profiles run on a 120-day attestation cycle. The portal’s user guide tells clinicians that after any update, “you must complete attestation so that your authorized organizations can view your updated profile.” An edit saved without attestation is not the version the plans see.

The fourth is each payer’s own provider file. Cigna tells approved applicants that “we will upload your provider information into our directories and claim systems.” Under federal law, a plan must re-verify its directory entries at least once every 90 days and post a provider’s update within two business days of getting it. The same law requires providers to maintain business processes to send directory information when a network agreement starts or ends and when that information materially changes.

No rule carries an update from one record to the next.

Where the Copies Drift

A Practice Location Changes

A clinician moves to a new site, or the group opens one. The Medicare report is due in 30 days. Missing it exposes the practice to an overpayment assessed back to the date of the change and to deactivation, with an effective date that can reach back to when the practice fell out of compliance. No Medicare payment may be made while billing privileges are deactivated. The NPI record, the portal profile, and every payer file need the same new address, each on its own clock.

A Revalidation is Missed

Medicare requires each provider to resubmit and recertify its enrollment information every five years. CMS contacts the provider directly, and the response is due within 60 calendar days. Failing to furnish the information within 90 calendar days of that notice is a listed reason for deactivation. If the notice lands in a mailbox nobody reads, the first sign may be a denial.

The Group Linkage is Incomplete

Medicare pays a group for a clinician’s services through a qualifying employment or contractual arrangement, recorded as a reassignment of benefits. That reassignment carries its own effective date, set by the same rule as the clinician’s enrollment. A clinician can be approved individually while the group still cannot be paid. CMS has merged the paper reassignment form into the CMS-855I, but the transaction itself remains. Commercial plans draw a similar line: Aetna states that credentialing is different from contracting and that both must be complete before a clinician is in network.

Reconcile Before Go-Live

Timing is why this belongs early. Medicare dates a physician’s billing privileges from whichever comes later: the filing of an application that is eventually approved, or the first day of care at the new location, and outside a declared disaster, retrospective billing reaches back at most 30 days, and only where circumstances prevented enrolling in advance. A gap found after go-live can leave services that are never recoverable. For each new clinician or new location, onboarding should include:

  • A side-by-side comparison of all four records on the fields claims use: legal name, NPI, practice location address, specialty, and group affiliation
  • Confirmation that the Medicare reassignment to the billing group, not only the individual enrollment, is approved and effective no later than the first scheduled visit
  • Confirmation that the portal profile was attested after its last edit and that the group’s plans are authorized to view it
  • Written confirmation from each plan that the clinician is loaded at the correct location in both the directory and the claim system
  • Calendar dates, each assigned to one accountable person, for the next attestation and the next Medicare revalidation

What Belongs in Denial Follow-Up

Denial work should detect drift, not absorb it. When a denial traces to enrollment, resubmitting the claim does not repair the record, and each resubmission is time the record stays wrong. Those denials should route to whoever owns the record, with the finding logged against the clinician rather than the claim.

The lasting fix is a change trigger. Any change to a clinician’s location, group, or legal name should open a single task that updates all four records, timed to the shortest applicable clock. For a practice location, that clock is 30 days.

Practices have spent years making claims cleaner before submission. The enrollment record is the part of every claim the practice never sends, and payment still depends on it.

About Madison Gardner

Madison Gardner is President of AMS Solutions, Inc., a physician-founded medical billing, revenue cycle management, and credentialing company that has served physician practices nationwide since 1992. The firm’s coding and billing staff hold AAPC credentials.



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< + > Vera Health Raised $32 Million | SpendRule Raises $4 Million

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.

Vera Health Quietly Became One of the World’s Most Used Clinical Tools. Now It Has Raised $32 Million to Give Every Clinician in the World the Best Medical Knowledge in Seconds

With a Team of Just 12 Employees, the Clinical AI Company has Grown Largely Through Physician Referrals, Bringing Total Funding to $32 Million

A year ago, a few thousand clinicians were using Vera Health. Today, more than 800,000 are, most having discovered the platform through a colleague. Every month since June, Vera has been the most downloaded clinical app in the world across the App Store and Google Play. In September alone, it was downloaded more times than OpenEvidence and Doximity combined, while monthly downloads had more than tripled since February. With a team of just 12 employees, Vera has reached clinicians in 190 countries, including approximately 1 in 4 physicians in Spain and Italy, largely through word of mouth. Vera Health is a clinical AI search engine that reasons like a clinician, helping physicians find and evaluate medical evidence in seconds.

Today, Vera Health announced a $28.5 million Series A led by Threshold Ventures, with participation from Mantis VC and SV Angel. Existing investors Y Combinator and Gradient tripled down in the round, bringing the company’s total funding to $32 million. The investment will accelerate Vera Health’s mission to close the gap between what medicine knows and what every patient receives.

Only a few months after raising its Series A, Vera already has more daily active users than it had monthly active users at the time of the raise. Clinicians went from asking Vera a few thousand questions a day to asking hundreds of thousands, every single day.

“Clinicians are the best data scientists I’ve ever met. They make the call in seconds, with more evidence than any human could ever read,” said Taieb Bennani, Co-Founder of Vera Health…

Full release here, originally announced October 27th, 2026.

SpendRule Raises $4 Million with Backing from Mark Cuban to Build the Decision Layer Between Contracts and Payments

Seed Round Led by Mark Cuban’s Radical Investments, With Participation from Zeal Capital Partners, Will Expand SpendRule’s Work With Health Systems and Support Broader Applications of Its Contract Enforcement Technology

SpendRule, an AI contract enforcement platform that ensures health systems pay exactly what their purchased services contracts say, today announced a $4 million seed funding round led by Mark Cuban’s Radical Investments, with participation from Zeal Capital Partners. The round brings SpendRule’s total funding raised to $6 million.

The new funding will allow SpendRule to deepen its work with health systems, invest further in product development and engineering, and bring the same contract enforcement technology built for complex healthcare contracts to a broader range of businesses.

“Companies spend all this time negotiating contracts, but what’s the point if nobody checks whether they’re getting what they paid for? That’s the problem SpendRule is solving,” said Mark Cuban.

SpendRule has $2.91 billion in annual contracted purchased services spend across 2,187 business relationships as it builds infrastructure for businesses and AI agents. The platform connects negotiated terms to actual transactions and the evidence needed to enforce them, helping organizations prevent overpayments, recover money they’re owed, and protect the value of what they negotiated. As AI agents increasingly buy, approve and pay on companies’ behalf, SpendRule provides the decision layer they need to understand what each contract allows and act accordingly.

“Every company makes commitments it can’t monitor, enforce or keep current,” said Joseph Akintolayo, Co-Founder and Co-CEO at SpendRule…

Full release here, originally announced October 29th, 2026.



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Wednesday, November 4, 2026

< + > A Look at Workday’s ERP in Healthcare

Healthcare technology conversations often focus on the EHR and clinical systems, but the technology supporting a health system’s HR, finance, and supply chain operations is just as critical to keeping things running. Workday is increasingly playing a strategic role in healthcare ERP, helping some of the nation’s largest health systems manage the business operations that ultimately support patient care.

At Workday Rising, I sat down with Keith Lohkamp, VP of Supply Chain Management for Healthcare at Workday, to talk about the company’s growing presence in healthcare and where it’s investing next.

AI is becoming a bigger part of that story. Workday’s announcements include Sana as a new front door for the platform, helping bring together the agents and workflows being developed across the system. Lohkamp also highlighted candidate profiles designed to reduce friction when healthcare workers apply for jobs, along with decision intelligence and Data Cloud capabilities that can help health systems connect operational and clinical data to support better planning and decision-making.

Those capabilities have practical applications across the organization. In recruiting, Workday’s talent acquisition agent can help identify candidates and schedule interviews more quickly. Lohkamp pointed to AdventHealth, which has reduced agency spending by more than $60 million using Workday tools. Finance teams can benefit from more automated close and audit processes, while supply chain teams can use AI to make it easier to find products, create contracts, work with suppliers, and capture savings.

Supply chain resilience is another major focus. Lohkamp explained that healthcare organizations have to be ready for shortages, back orders, recalls, natural disasters, and other disruptions that can quickly affect the availability of critical supplies. Workday now works with more than half of the organizations on Gartner’s healthcare supply chain Top 25, and he shared an example of West Coast health systems that had to quickly adjust their purchasing after a major distributor experienced a fire at its distribution center. Workday helped those organizations pivot their ordering and track supplies so patient care could continue without disruption.

Making all of this work also requires connecting Workday to the rest of a health system’s technology environment. Lohkamp discussed the company’s integration approach with EHRs and other systems, including connections for item master, product, pricing, and financial data. He also highlighted Accounting Center, which can bring detailed revenue cycle transactions into Workday to support deeper financial analysis, along with Data Cloud’s ability to connect data across different sources.

Watch the full interview to hear Lohkamp’s perspective on Workday’s growing role in healthcare and how AI, connected data, and more resilient supply chain operations are shaping the next generation of health system ERP.

Learn more about Workday: https://www.workday.com/

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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Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.



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< + > Willis Knighton Health Uses Ambient AI from Commure to Reduce Physician Burden

Before standardizing on MEDITECH for their EHR, the Louisiana provider Willis Knighton Health had 140 different instances of EHRs. Senior VP and CIO Mark Galea said it was critical to get everyone on a single EHR. But he also knew the transition would be challenging for staff and cause a lot of disruption. He felt that the institution owed it to their doctors to see how technology could make their work easier after such a significant change. After a pretty extensive search and evaluation, Willis Knighton brought in Commure to provide an ambient AI scribe to alleviate some of the burden on their clinical staff.

In a recent interview, Galea along with Ian Shakil, Chief Strategy Officer at Commure sat down with us to share the detailed, carefully planned strategy used by Willis Knighton to choose their ambient AI vendors and roll it out efficiently. Shakil and the team at Commure were one of the original creators of ambient AI, and the company has particular expertise in difficult settings such as emergency departments.

One of the key needs of Willis Knighton was that their AI scribe vendor was able to integrate well with MEDITECH. Plus, Galea said he didn’t want Willis Knighton to be the first customer—or even the tenth—because he didn’t want a vendor to “experiment” on them. He talked to and ruled out many ambient AI vendors that at first looked promising, and settled on Commure and one other vendor for pilots.

Some intensive analytics also went into Willis Knighton’s decisions. They looked at what the doctors were actually doing: when doctors are using the EHR, which parts, and how often have to go back to the same place. They tried the two pilot solutions on 28 specialties, one doctor for each. Shakil praised Willis Knighton, saying they were unusual among providers because “they knew what they wanted” when talking to vendors and did the work to measure those outcomes.

One of the advantages of Commure is that it partners closely with clients. Shakil says they emphasize not just technology, but how to measure and report returns so Willis Knighton was a good match.

Deployment actually went faster than expected, with less time spent on support and 14 months to deploy the solution. Galea did not want a lot of customization or optimization up front. Other factors in choosing both the EHR and ambient AI included data security and cost. Like most providers, Willis Knighton has very limited capital.

Galea is a strong believer in using technology strategically to gain a competitive edge. For instance, they use robots in 60% of the operating rooms. He thinks that only in the past four to five years, the investment the health care industry made in digital technologies is starting to deliver on its promise.

Both Galea and Shakil offered thoughts for the future. Shakil said that, proud as he was to invent the ambient AI scribe, he looks forward to helping it disappear into a broader suite of AI-assisted tools for summaries, search, and other use cases embed in workflows. He also wants Commure to move into more niche settings and RCM.

Galea and Shakil agree that providing more data to consumers “will shift the playing field.”

Watch our interview with Mark Galea from Willis Knighton Health and Ian Shakil from Commure for other valuable insights into a successful roll-out of ambient AI.

Learn more about Commure: https://www.commure.com/

Learn more about Willis Knighton Health: https://www.wkhs.com/

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

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

Commure is a proud sponsor of Healthcare Scene.



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< + > How Automation and AI are Quietly Rebuilding the Hospital Back Office

The following is a guest article by Paige Schwein, Vice President, Technology Services at Healthrise

Ask most people where AI is changing healthcare, and they’ll describe a surgical robot or an algorithm that reads scans faster than a radiologist. But after spending more than a decade in revenue cycle operations, the real revolution unfolding quietly in the administrative back office.

Health systems and hospitals that embed intelligent automation into their day-to-day operations can reduce the administrative burden created by endless claim queues, denial worklists, and prior authorization backlogs.

There is a compelling business case for this pivot. Administrative work consumes 15% to 30% of U.S. healthcare spending, and most hospitals operate on margins between 1% and 3%, leaving virtually no room for avoidable waste. First-pass denial rates still top 10% nationally, even at organizations that have spent heavily on billing software and staff.

The 2025 CAQH Index estimates that automation saved the industry $258 billion in administrative costs in 2024 and puts the savings still on the table at another $21 billion a year.

That makes the hospital back office one of the clearest opportunities for AI adoption: it is data-rich, highly repetitive, and directly connected to a health system’s financial performance. The next phase of healthcare AI isn’t about adding more tools; it’s about embedding intelligence into the work hospitals already do. Most AI efforts began as isolated pilots targeting a single payer or denial category. Now, the opportunity is to move beyond those pilots and integrate automation directly into daily worklists, embedding flagged claims into existing queues so staff don’t have to check separate dashboards.

What AI Tools Actually Do

For years, denial management meant someone exporting claims data into a spreadsheet and piecing together patterns long after the revenue had been written off. Predictive models with embedded large language models (LLMs) now read through that data and surface the trends a person might miss. Health systems using them have cut incoming denials by an average of 25%.

The same historical data (billing history, seasonal swings in patient volume, and the habits of individual payers) also lets revenue cycle leaders forecast cash flow and identify where to focus resources before a shortfall arrives.

Coding and audit teams work differently now as well. Random sampling used to decide which accounts got reviewed, so the costliest errors often went unexamined. Automated selection sends reviewers to the highest-risk accounts first. Systems using standardized audit-coach-measure workflows have seen underperforming team members progress to consistent top performers in fewer than 90 days.

Together, these tools shift revenue cycle work from reacting to problems after they happen to identifying where attention is needed before those problems become costly. The technology handles the volume and pattern recognition, while revenue cycle teams can spend more time interpreting what the data means, deciding what action to take, and improving the processes behind it.

Confronting Bureaucratic Hurdles

New federal mandates require health plans to enforce strict prior authorization turnarounds — 72 hours for urgent cases and seven days for standard requests — before moving to standardized electronic submissions by 2027.

Physicians and their staff already spend about 13 hours a week on prior authorization. Keeping pace with those deadlines without adding headcount or exhausting the team you have requires automation that connects clinical documentation to the billing system, backed by a denial prevention program that catches problems before a claim goes out.

Before Adding One More Tool

A typical revenue cycle department already juggles an EHR, a clearinghouse, a claims scrubber, a denial tracker, and multiple point solutions. Another AI tool can easily become one more place for work to hide.

Before introducing new technology, healthcare leaders should confirm it can embed into existing workflows, assign clear ownership for flagged issues, and avoid duplicating current functionality. To track progress and prove it works, it’s important to establish concrete baseline metrics before the tool goes live, such as first-pass denial rates, days in A/R, and authorization turnaround times.

The goal shouldn’t be another dashboard. It should be a better workflow.

Healthcare Still Needs a Human Touch

Physicians have good reason to be wary. Six in ten say they worry payers will use AI to deny more claims, and nothing in the technology itself prevents that. A model that flags a questionable claim or an audit risk has done half the job. The other half belongs to a trained specialist who reviews the flag, understands the context around it, and has the authority to correct what’s wrong.

Governance decides whether these tools make the work easier for the people doing it or harder, and that requires clear ownership, visible oversight and a defined process for acting on what the software finds.

When those pieces are missing, automation just makes a broken process run faster. When they’re in place, the billing office finally catches up to its own workload. For a hospital operating on a 2% margin, the claims it stops losing can matter as much as anything new in the operating room.

About Paige Schwein

Paige Schwein is Vice President of Technology Services at Healthrise, where she leads the technology behind the company’s revenue cycle work for health systems. She has spent more than a decade in revenue cycle operations and builds teams that use data to improve efficiency and financial performance.



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< + > This Week’s Health IT Jobs – November 4, 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:

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.



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Tuesday, November 3, 2026

< + > East Georgia Healthcare Center Shares Its Experience with the New eClinicalWorks Pharmacy Solution and AI

East Georgia Healthcare Center is taking an innovative approach to healthcare technology by working with eClinicalWorks to bring new pharmacy capabilities and AI tools into its existing workflows. In our recent interview at the eClinicalWork National Conference, Peyton Frye, COO at East Georgia Healthcare Center, shares how the organization helped shape eClinicalWorks’ new pharmacy module, why having pharmacy and EHR workflows integrated makes a difference, and what the implementation has meant for its staff.

One of the biggest advantages of the new pharmacy module is how it connects pharmacy operations with the existing eClinicalWorks EHR. Frye explains how information such as patient contact details is now synchronized between the medical and pharmacy sides, eliminating the need to update multiple systems.  This may seem like a small thing, but it’s made a big difference in their organization.

Clinicians can also see whether medications are in stock or available for next-day delivery. On the pharmacy side, real-time updates to patient sliding fee scales help ensure pharmacists have the right information when patients arrive to pick up prescriptions. Plus, for an organization managing both an open-door pharmacy and its 340B program, having these workflows connected makes a meaningful difference.

We also discuss with Frye the AI solutions East Georgia Healthcare Center is using, including healow Genie and AI-powered analytics. Frye shares how the organization initially implemented Genie at its largest location before expanding it to two locations that had some of its lowest patient satisfaction scores for telephone access. The results were encouraging: within the second month, patient satisfaction sentiment at those locations increased from the low 80s to the low 90s. Genie gives patients 24/7 access to answers about things like lab results, appointments, and prescription status, helping address missed calls and the heavy volume of calls that often comes at the beginning and end of the workday.

Beyond patient calls, East Georgia Healthcare Center is also using eClinicalWorks’ AI-powered analytics capabilities to make it easier for its quality team to query data using natural language rather than building complex SQL queries. Frye also discusses the importance of having the right staff oversee AI implementations.  He shares why human intervention still matters and the additional AI capabilities he’s excited to see coming to healthcare.

Watch the full interview to hear how East Georgia Healthcare Center is leveraging the new eClinicalWork Pharmacy solution in their FQHC along with a number of other AI tools.

Learn more about East Georgia Healthcare Center: https://eghc.org/

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

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

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

eClinicalWorks is a proud sponsor of Healthcare Scene.



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< + > Augusta Health Automates Document Routing With Forward Advantage AI

AI is making contributions in many health care settings by creating doctors’ notes, but an equally urgent task in many organizations is processing, storing, and routing incoming documents such as referrals and prescription requests. Augusta Health, a community health system in central Virginia with a 255-bed hospital, four urgent care clinics, and many other sites, has to deal each year with 750,000 paper documents—a total of 2.4 million pages—submitted by scanning or fax.

In our recent interview, Leigh Williams, CIO at Augusta Health, and Audrey Brislin, Vice President of Product and Marketing at Forward Advantage, talk about the AI-based solution for document recognition and scanning from Forward Advantage that is relieving staff at Augusta Health of the tedious and error-prone job of redirecting the documents.

Augusta Health has had a relationship with Forward Advantage since 1999 and so it made sense to extend this relationship with Forward Advantage’s new document routing solution. Prior to implementing this new solution, Augusta Health would present each document to a human agent on a screen. The agent would determine what kind of document it was, where it should be stored, and which clinician should receive it for action. This was preferable to paper handling, but still delayed both treatment and billing. Williams said they needed “a really slick process.”

Luckily, Forward Advantage has recently added AI-driven categorizations that can potentially automate the entire process of identifying, storing, and routing documents. According to Brislin, the key is to understand the provider’s workflows. Some are more consistent than others, and automation should be applied to those that are consistent and predictable. One of the benefits of Forward Advantage is that it does leave room for a human in the loop.

Augusta Health has been deploying the AI automation for a few months and is finding it a great solution that fixes a “long-standing, intractable problem.” Success metrics they’re tracking include labor costs, and the time required to get documents to the clinicians to act on.  Clinicians love getting the documents in their native MEDITECH workflow faster than when the documents were routed by a human. Williams expects the automation to help with staff retention, because categorizing documents by hand was so boring and unfulfilling, “no value add.”

Automation, along with centralizing the categorization process, allows Augusta Health to run analytics and derive insights such as where prescriptions and referrals are coming from. Williams summarizes their experience as a safe and high-impact deployment of AI. Brislin expects that in the future, AI will also route documents outside the organization and enable work with third parties.

Watch our interview with Leigh Williams from Augusta Health and Audrey Brislin from Forward Advantage to learn more about this AI solution which is solving real world healthcare challenges.

Learn more about Forward Advantage: https://www.forwardadvantage.com/

Learn more about Augusta Health: https://www.augustahealth.com/

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

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

Forward Advantage is a proud sponsor of Healthcare Scene.



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< + > Clinical AI Needs Version Control, Not Just Validation

The following is a guest article by Dr. Michael T. Neely

Healthcare AI is often governed as though validation were a one-time gate: test the system, approve it, deploy it, and move on. That model breaks down when the software changes.

AI tools can be updated far more frequently than traditional clinical technology. A vendor may replace an underlying model, modify a prompt or retrieval layer, change thresholds, retrain on new data, alter workflow logic, or release a new version without changing the product name clinicians see. When that happens, an organization can still have a “validated” system on paper while a materially different system is operating in practice.

The governance question is therefore not only, “Was this AI validated?” It is, “Which version was validated, which version is running now, what changed, and what evidence tells us the change is still safe for this use?”

Validation Without Version Identity is Incomplete

Healthcare organizations already understand version control in other high-stakes domains. Medication formularies, clinical protocols, cybersecurity patches, laboratory methods, and medical devices are not managed as timeless objects. Changes are documented because a change can alter performance, risk, or downstream workflow.

AI should be treated the same way.

The FDA’s final guidance on predetermined change control plans for AI-enabled device software functions offers a useful regulatory example. It asks manufacturers to describe planned modifications, the methods used to develop and validate those modifications, and the impact of those changes. Not every healthcare AI tool is an FDA-regulated medical device, but the operational principle travels well: change should be anticipated, documented, assessed, and tied to evidence.

Health systems need an internal version record that identifies, at minimum, the vendor and product, deployed model or build, material configuration, approved use, implementation date, validation evidence, and responsible owner. For generative AI, the record may also need to capture prompt templates, retrieval sources, orchestration logic, and other components that meaningfully shape output.

Material Changes Need a Trigger

Not every software update requires a full revalidation. A cosmetic interface change is different from replacing the model that drafts a clinical summary. The goal is not bureaucracy for its own sake; it is a defensible material-change process.

Organizations should define in advance which changes trigger review. Examples include a new model family, altered training or tuning, changes to decision thresholds, new data sources, expanded intended use, changes in clinical workflow, a new autonomous capability, or modifications that affect how outputs are presented to clinicians or patients.

Vendor contracts should support this process. A health system cannot govern a system it is not told has changed. Material-change notification should therefore be treated as an operational requirement, not simply a courtesy from the vendor.

Revalidation Should Match the Risk

Once a material change is identified, the next question is how much testing is enough. The answer should depend on what the system does and the consequences of error.

A documentation assistant may require testing for factual accuracy, omission, workflow fit, and clinician review burden. A predictive decision-support tool may require renewed performance assessment, subgroup analysis, calibration checks, or workflow-specific validation. A patient-facing system may also need testing for clarity, escalation behavior, unsafe advice, and whether human review remains available when needed.

The NIST AI Risk Management Framework is useful here because it treats risk management as a lifecycle activity rather than a single approval event. That lifecycle view is especially important for AI systems that can drift, be reconfigured, or change through vendor updates.

Keep the Ability to Stop and Roll Back

Version control is not meaningful if an organization cannot act when a problem appears.

Every consequential healthcare AI implementation should have a defined process for suspension, rollback, or isolation. Governance teams should know who can make that decision, what evidence triggers it, what version can be restored, and how affected users will be notified.

Incident review also depends on traceability. If a problematic output contributed to a patient-facing communication or clinical workflow, the organization should be able to reconstruct which system version produced it, what data or context were used, what the output was, and what human review occurred.

Without that record, post-incident analysis becomes guesswork.

Transparency Has to Survive the Update Cycle

ONC’s HTI-1 final rule established algorithm-transparency requirements for predictive decision-support interventions in certified health IT. That transparency is most useful when it stays current. Documentation that accurately described a model six months ago may be misleading after a material update.

Hospitals and health systems therefore need a simple rule: every meaningful AI change should force a question about whether prior documentation, validation, disclosures, training, and monitoring still describe the system that is actually in use.

That is the core discipline of AI version control.

Validation tells you that a particular system met a standard at a particular moment. Version control tells you whether that is still the system affecting care today. In healthcare, where software changes can influence clinical judgment, patient communication, workflow priority, and organizational accountability, that distinction is not administrative detail. It is part of safe AI operations.

About Dr. Michael T. Neely

Dr. Michael T. Neely is an independent researcher and AI educator whose work focuses on responsible AI, governance, accountability, patient protection, and human oversight. He is CEO of Global Music Conference and XS10 Magazine and brings more than four decades of leadership in the creative industries. His healthcare-AI commentary has appeared in KevinMD and Healthcare Business Today. His work examines how organizations translate responsible-AI principles into operational controls.



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< + > Bonus Features – November 8, 2026 – 48% of Americans have used AI to review their health insurance options, 68% would independently verify AI-generated medication details, plus 34 more stories

Welcome to the weekly edition of Healthcare IT Today Bonus Features . This article will be a weekly roundup of interesting stories, product ...