Tuesday, August 11, 2026

< + > Governance is the New Differentiator in EHR-Adjacent AI

The following is a guest article by Angela Adams, CEO at Inflo Health

Healthcare has spent the past several years adding AI into clinical workflows across imaging, documentation, and decision support. It’s mostly been in service of less manual work, better triaging, and fewer things falling through the cracks, all of which are worthwhile pursuits. What gets less attention amid all the hype, though, is what happens when these tools are wrong. 

I don’t mean catastrophically wrong. I mean quietly wrong: a finding that doesn’t route anywhere, a recommendation no one owns, an automated step that fails without anyone noticing. In most health systems today, nobody can answer the most basic governance question about the AI in their stack: when this tool makes a mistake, who catches it, and how fast can they do so? 

From imaging to documentation to decision support, healthcare teams have integrated ever more models into their workflows to save time and ensure patient engagement loops are properly closed. Each one adds new capability, but each one also adds a new place where something can fail—sometimes silently. As AI touches more of the patient journey, those failure points multiply faster than anyone’s ability to trace them. 

As AI’s role in supporting healthcare workers begins to integrate further with patient care and internal processes, more touchpoints become disconnected and difficult to trace due to a lack of clear governance across the models.

Roughly half of radiology follow-up recommendations are never completed. Patients absorb the delayed diagnoses while health systems absorb the avoidable costs and the liability. In most cases, that failure is hard to notice. There are no alerts. Nothing escalates. The gap becomes visible only when the patient comes back, usually sicker.

What’s Next? Governance that Lives Within the Workflow 

The next wave of digital health differentiation will come from practical AI governance that operates at the workflow level. No single platform can govern every model, workflow, and user action across the enterprise, but what if each platform had governance built in?

Built-in governance means the system knows what should happen after every output. Based on embedded rules, it knows who owns the next step, what the time window is, and what triggers escalation if the step doesn’t happen. Audit trails run from finding to completed action. Committee-level governance asks whether a tool should be deployed. Workflow-level governance asks, every day, whether the tool’s outputs are actually turning into safe care.

The federal HTI-1 Final Rule introduced new algorithm transparency expectations for AI and predictive tools in certified health IT, raising the bar for what clinical users should be able to understand about the tools that support decision-making. That direction reinforces a broader market reality: governance needs to be tied to patient safety and measurable outcomes, not committee rituals.

What Practitioners Should Demand from Vendors

As practitioners, it’s incumbent upon us to demand that the EHR-adjacent vendors we welcome into the walls of the hospital actually set our teams up to succeed. If governance will be baked into all health IT predictive tools, that means that health systems can make decisions based on what models are willing to offer. The key things to look out for include: 

  • Role-Based Output Controls: AI outputs should reach the right person, at the right time, every time; ensuring that information gets into the hands of the person equipped to act on it—and that they have the right permissions—protects patient safety, privacy, and the integrity of the workflow
  • Audit Trails that Follow Care: Maintaining clear paths along which teams can easily find the source of mistakes prevents patient harm, nips growing issues in the bud, and allows systemic fixes instead of one-off band-aids
  • Escalation Pathways: The most dangerous failing in clinical AI isn’t an incorrect finding, it’s a right answer that goes nowhere; vendors should be able to show what happens when a follow-up stalls: who gets notified, on what timeline, and what prevents the case from simply aging out of view— with clear steps already in place, no incidents go without a resolution plan

When we take on the mantle of providing care to patients, the first promise we make is to do no harm. That bond exists between clinicians and patients, but it exists everywhere else, too—and the promise doesn’t stop applying when the work is done by software. When we consider allowing AI into our hospitals and care relationships, how do we ensure these tools strengthen that promise rather than weaken it? How do we know that we are elevating care and not just making things easier for the sake of making things easier? 

Through governance: knowing what the tool touches, who acts on its output, and what happens when it’s wrong. By putting patient safety first in every decision, we keep our oath and build trust with the people healthcare was always supposed to be about.

About Angela Adams

Angela Adams, RN, started her career as a critical care medicine nurse at Duke University Medical Center. Driven to make a broader impact, Angela looked to the emerging healthcare AI segment for solutions that would allow her to help patients as well as assist clinicians to become more effective and efficient in solving complex medical issues. She helped advance AI adoption and overcome skepticism at companies like Jvion (acquired by Lightbeam Health Solutions), where she applied deep machine learning to lower nosocomial event rates and prevent patient deterioration. She went on to create her most recent solution at Inflo Health, where she focuses on missed follow-up radiology appointments.



< + > Raintree Acquires Spike Technologies | Doctronic Expands Into Pediatrics

Check out today’s featured companies who have recently completed an M&A deal, and be sure to check out the full list of past healthcare IT M&A.


Raintree Acquires Spike Technologies, Bringing Genuinely Agentic AI Voice to Revenue Cycle and Patient Engagement

Native to the EMR, the Acquisition Automates the Most Manual Work in Revenue Cycle Management: The First and Most Critical Step Toward Fully Autonomous RCM for Rehabilitation and Physical Therapy Organizations

Raintree, the leading electronic health record (EHR) and practice management platform for rehabilitation and physical therapy organizations, today announced it has acquired Spike Technologies, a developer of genuinely agentic AI voice technology for healthcare. The acquisition embeds AI voice directly into Raintree’s platform to take on the most tedious, manually intensive work in revenue cycle and patient engagement, including payer calls, claim follow-ups, eligibility and prior authorization, and patient outreach, and marks an important step toward fully autonomous revenue cycle management (RCM).

Revenue cycle work remains one of the most labor-intensive parts of healthcare. Physical therapy practices face an average claim denial rate of roughly 13%, and nearly three-quarters of those denials must be appealed. Front-desk teams spend ten minutes or more per patient on prior authorization alone, and most practices have had to add administrative staff simply to keep up. Industry analyses estimate that AI and automation in the revenue cycle represent up to $360 billion in potential annual savings. By putting genuinely agentic AI voice to work on this manual burden, Raintree and Spike aim to return that time to care.

Unlike scripted phone trees, rules engines, or chatbots layered on top of legacy workflows, the technology is genuinely agentic: AI voice agents that understand context, make decisions, and complete multi-step work, not a fixed menu of options. Because the capability is native to Raintree’s EMR rather than a bolted-on third-party layer, the agents act with full clinical, scheduling, and financial context. It is the foundational piece of a broader vision: fully integrated, agentic orchestration across the entire revenue cycle and patient engagement.

“Getting paid is the hardest, most manual part of running a therapy practice, and voice is where that burden is heaviest. We chose to take on the hardest piece first,” explained Nick Hedges, Raintree CEO…

Full release here, originally announced July 15th, 2026.


Doctronic Expands Into Pediatrics, Accelerating Its Vision for an AI-Native Primary Care Platform for the Entire Family

Acquisition of Summer Health Brings Leading Text-Based Pediatric Expertise to Doctronic, Extending AI-Powered Primary Care from Birth through Adulthood

Doctronic today announced its expansion into pediatric primary care, marking the next step in its mission to build a comprehensive AI-native primary care platform. To accelerate that vision, the company has acquired Summer Health, the leading platform for virtual, text-based pediatric care.

The expansion reflects a broader shift in healthcare: patients increasingly expect immediate, continuous access to trusted care, yet pediatric primary care remains difficult to access outside traditional office hours. For parents, questions about fevers, feeding, medications, sleep, or development rarely arise on a schedule. By extending its platform to children beginning at birth, Doctronic aims to make high-quality primary care more accessible during the moments families need it most.

Founded in 2022, Summer Health pioneered on-demand, text-based pediatric care, supporting more than 100,000 pediatric encounters for tens of thousands of families. Its conversational model and deep pediatric expertise closely complement Doctronic, which has supported more than 30 million health encounters in just two years through its proprietary AI doctor and nationwide network of licensed clinicians delivering personalized medical guidance and video visits for $39.

“Families don’t experience healthcare in silos,” said Dr. Adam Oskowitz, Co-Founder and Co-CEO at Doctronic…

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



Monday, August 10, 2026

< + > CIO Podcast – Episode 119: Improving Through Data and Research with Eric Lee

For the 119th episode of the CIO podcast hosted by Healthcare IT Today, we are joined by Eric Lee, MD, Chief Health Information Officer at AltaMed Health Services, to talk about improving with data and research! We kick this episode off with Lee sharing his experience with the KLAS Arch Collaborative. Next, we discuss some of the results Lee saw from the survey. Using that same survey, we then get into what Lee has done or is looking to do based on the results. Then Lee shares a recent successful project he’s worked on at AltaMed, and we dig into what went into the project and what made it a success. We then dive into AI to discuss what we now understand about AI in healthcare and what we are still trying to figure out. Lastly, Lee passes along the best piece of advice he’s been given in his career.

Here’s a look at the questions and topics we discuss in this episode:

  • What’s been your experience with the KLAS Arch Collaborative?
  • What are some of the results you saw from the survey?
  • What have you done or what are you looking to do based on these results?
  • What’s a recent project you’ve worked on at AltaMed that was a success? What went into the project and what made it a success?
  • What do we now understand about AI in healthcare, and what are we still figuring out?
  • What’s the best piece of advice you’ve been given in your career?

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

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We appreciate you listening!

Listen to the Latest Episodes



< + > What Makes a CIE Work? Five Lessons from the Field

The following is a guest article by Mark Taylor, VP of Product Strategy at Ready Computing

Community Information Exchanges (CIE) are often described as technology initiatives. In practice, the successful ones are much more than that. A CIE works when it helps real people coordinate care across health, social care, government, and community-based organizations without forcing every partner to abandon the systems and workflows they already use.

The goal is not just to exchange data. It is to make it easier to identify needs, connect people to services, close the loop on referrals, measure outcomes, and support the organizations doing the work.

Our experience supporting social care and whole-person care initiatives across New York State’s 1115 Waiver, Georgia’s statewide CIE infrastructure through GaHIN, and the Connect2 network in Washington State has shown that the strongest CIEs share five core traits.

1. They Start with the People and Services, Not the Technology

A CIE should be designed around how people actually move through care. That means understanding where needs are identified, how referrals are made, who follows up, and what information frontline teams need at each step.

In New York’s 1115 Waiver work, the challenge is not simply collecting HRSN screening data. It is helping social care networks operationalize screening, eligibility, referrals, consent, service delivery, and reporting across many different organizations.

The same principle applies in Washington State’s Connect2 network. The value of the platform is not just that data can move. It is that organizations can coordinate around people in a more consistent, connected way.

A working CIE supports the journey from need to service, not just the movement of records.

2. They Connect Existing Systems Instead of Replacing Them

Community networks are diverse by nature. Hospitals, health plans, HIEs, government agencies, social care organizations, and community-based providers often use different tools. A CIE that requires every participant to adopt one new system creates friction before the work even begins.

The stronger model is interoperability. Let organizations keep the systems that already support their operations, while creating a shared infrastructure for exchange, orchestration, and oversight.

This is central to the work we support across these networks. In Washington State, secure, standards-based exchange powers the Connect2 infrastructure. In Georgia, the work with GaHIN supports broader statewide infrastructure that connects health and social care data across a complex ecosystem.

A CIE works when it becomes the connective layer, not another silo.

3. They Build Trust Through Governance, Consent, and Compliance

CIEs handle sensitive information across organizations that may have different responsibilities, regulations, and levels of technical maturity. Trust is essential.

That trust depends on clear rules for participation, strong privacy and consent management, secure hosting, and compliance practices that give partners confidence. This is especially important when social care data is being connected with clinical or payer data.

In New York’s 1115 Waiver environment, consent, eligibility, and service documentation are not side issues. They are foundational to making the model work at scale. In Georgia, statewide exchange requires a similar focus on governance, security, and reliability.

A CIE cannot succeed if participants do not trust how data is protected, shared, and used.

4. They Make Frontline Workflows Easier

The success of a CIE depends heavily on adoption. If the platform adds administrative burden, frontline organizations will struggle to use it consistently.

That means the system needs to support practical workflows: screening, referral management, eligibility checks, service documentation, status updates, closed-loop communication, reporting, and escalation. It also needs to work for organizations with different staffing levels and technical resources.

The best CIEs reduce duplicate entry, make the next step clear, and help teams see what has already happened. They also provide flexibility, because the workflow for housing support may look different from food assistance, transportation, home modifications, or substance use disorder-related services.

A CIE works when it makes coordination simpler for the people doing the coordinating.

5. They Prove Value Through Data, Reporting, and Outcomes

CIEs need to show impact. That means capturing not only referrals, but whether needs were met, services were delivered, gaps remain, and outcomes improved.

For social care networks under the NYS 1115 Waiver, reporting and payment-related workflows are critical. For statewide efforts like GaHIN, the ability to reduce silos and provide a broader view of community health needs is essential. For Connect2, the value lies in creating the infrastructure needed to support more coordinated, community-centered care across the network.

The strongest CIEs create visibility at multiple levels: for care teams, for network operators, for funders, and for policymakers. They help answer practical questions: Who needs help? What services are available? What happened after the referral? Where are the gaps? What is working?

A CIE becomes sustainable when it can demonstrate measurable value.

A successful CIE is not defined by a single platform, referral tool, or data standard. It is defined by whether it helps communities work together more effectively.

The most effective CIEs are built around people, designed for interoperability, grounded in trust, aligned with frontline workflows, and measured by outcomes. Across New York State, Georgia, and Washington State, one lesson is clear: CIEs work when they connect more than systems. They connect organizations, services, and people around a shared model of care.

About Mark Taylor

Mark Taylor is VP of Product Strategy at Ready Computing, a healthcare technology leader with experience advancing interoperability and connected care across complex health and social care networks. He focuses on how technology can help organizations coordinate services, address social needs, and support more connected models of care.



< + > RevealDx Announces Distribution Agreement and Investment | Prosper Medical Raises $16M

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.


RevealDx Announces Distribution Agreement and Investment from 4DMedical

4DMedical to Distribute RevealAI-Lung in the US, Europe, Australia, and New Zealand

RevealDx, a leader in AI characterization of lung nodules, announced today, following World Lung Cancer Day, a distribution agreement and strategic investment of $3.4 million by 4DMedical (ASX: 4DX), expanding access to its flagship product, RevealAI-Lung. RevealAI-Lung has received MDR Certification, TGA Approval, and FDA clearance. In the transaction with 4DMedical, Chestnut Partners, Inc. served as the exclusive financial advisor to RevealDx.

This news follows 4DMedical’s recent acquisition of Austrian-based Contextflow. 4DMedical, a global medical technology company, is revolutionising respiratory care through advanced imaging and artificial intelligence. Contextflow offers advanced chest CT technologies that automate the identification of lung nodules. RevealAI-Lung has been integrated into the Contextflow platform and is already operational at several clinical sites across Europe.

The RevealDx technology characterizes incidental lung nodules by producing a Malignancy Similarity Index (mSI), a score that helps radiologists make more informed follow-up recommendations to assist in cancer diagnosis. The company has validated the software on over 1,500 patients from a variety of cohorts.

The RevealAI-Lung CADx device offers several key capabilities, including:

  • Significant improvement in Radiologist reader performance
  • Use of real-world NLST data as our reference population
  • Clinically relevant malignancy scoring
  • First-ever integration directly into PACS, vastly improving workflow
  • Proven generalizability across exam types and patient populations

“We are excited to announce our new partnership with 4DMedical,” said Chris Wood, CEO at RevealDx. “As we recognize World Lung Cancer Day, this milestone underscores our commitment to helping clinicians identify potentially malignant lung nodules earlier and with greater confidence. The incredible team at 4DMedical and the resources they bring will expand our reach and benefit patients.”

Andreas Fouras, Founder and CEO at 4DMedical, said, “For 4DMedical, this is about more than adding products. It is about building a connected ecosystem for cardiopulmonary care. CT:VQ gives physicians physiological insight into how the lung is actually functioning. By surrounding that capability with disease detection and AI-powered risk stratification, we can help health systems identify the right patients earlier and ensure they receive appropriate care. The result is a platform that has the potential to improve outcomes for patients while increasing utilization of advanced functional imaging across vital disease areas.”

In addition to its recent regulatory milestones, RevealAI-Lung is reimbursable by Medicare in the United States under CPT codes 0721T and 0722T, helping to support broader clinical adoption.

About RevealDx

RevealDx has developed RevealAI-Lung, the first Medical Imaging AI software to achieve reimbursement in both the US and EU. The company has published several studies demonstrating significant improvement in both early cancer detection as well as reduction in false positives. Studies show that by integrating this patented technology into routine clinical use, healthcare providers can more effectively triage lung nodules. For more information, contact sales@reveal-dx.com.

Learn more at reveal-dx.com

About 4DMedical

4DMedical Limited (ASX:4DX) is a global medical technology company revolutionising respiratory care with advanced imaging and artificial intelligence. Its patented XV Technology transforms standard scans into rich, functional insights that allow physicians to detect, diagnose, and monitor lung disease earlier and with greater precision.

4DMedical’s expanding software portfolio includes the FDA-cleared XV Lung Ventilation Analysis Software (XV LVAS), CT LVAS, and the ground-breaking CT:VQ solution designed to set new benchmarks in cardiothoracic imaging by combining ventilation and perfusion analysis.

Delivered seamlessly through a Software-as-a-Service (SaaS) model, 4DMedical’s solutions integrate into existing hospital infrastructure, enhancing physician productivity and enabling more personalised patient care. With the addition of advanced AI capabilities from its 2023 acquisition of Imbio and 2026 acquisition of contextflow, 4DMedical continues to push the boundaries of medical imaging to redefine how respiratory disease is understood and treated worldwide.

Learn more at 4dmedical.com

Originally announced August 3rd, 2026.


Prosper Medical Raises $16M to Bring AI-powered Concierge Care to All

Prosper Medical today announced $16 million in financing to scale its AI-powered concierge primary care platform. The company was founded by Ryan McQuaid and James Wantuck, MD, who previously built and sold PlushCare, one of the country’s first direct-to-consumer telehealth platforms, for $450 million. Now they’re back, and they’re using AI to address one of healthcare’s most persistent challenges: delivering personalized, seamless primary care at scale.

While telemedicine made healthcare more convenient, McQuaid and Wantuck came away with a larger realization: convenience alone doesn’t solve the primary care crisis. The real problem is a trusted relationship. Most Americans don’t have a physician who knows them well, really listens to them, and cares about them. That kind of care has always existed, but for most people it’s been out of reach, and Prosper was built to change that.

“When we built PlushCare, we learned that making appointments easier wasn’t enough,” said Ryan McQuaid, Co-Founder and CEO at Prosper Medical. “The real challenge is everything that happens after a patient leaves the visit. Following up on test results, finding the right specialist, collecting comprehensive health data, and preventing major problems before they arise. AI finally gives us a way to deliver that level of care and personalization at a scale that wasn’t possible before.”

The goal isn’t to replace physicians, but to supercharge them in caring for their patients. Prosper’s platform maintains continuity across every patient interaction, aggregates all of your health data, coordinates care, and ensures important data signals and communication don’t get lost between appointments. The result is a Prosper doctor who arrives with context, Prosper AI that can intervene earlier, a Care Concierge Team, and a healthcare experience that feels far more personal than traditional primary care.

Unlike many concierge or membership-based healthcare services, Prosper is designed to be accessible to more than only the ultra-wealthy…

Full release here, originally announced July 23rd, 2026.



Sunday, August 9, 2026

< + > Bonus Features – August 9, 2026 – 57% of home- and community-based providers evaluating AI tools, 28% of patients have put off canceling an appointment because it required a phone call, plus 25 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 and 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.



Saturday, August 8, 2026

< + > Weekly Roundup – August 8, 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.

Keeping the Patient at the Center of Large-Scale Technology Deployment. John Lynn connected with Lindsey Bengfort at NTT Data to discuss trying to manage the pace of change with AI, especially from the start of a pilot to the time to ramp up adoption. Read more…

Turning Data Into Actionable Insights. Renee Wiczorek at Truven by Merative gave John a demo of the company’s dashboards and insights, which help organizations evaluate program benchmarks and determine where investments will have the biggest impactRead more…

Integrating Back-Office Systems With Clinical and Front-End Applications. The Healthcare IT Today community is solving this challenging problem with flexible infrastructure, platforms, device-level security, ambient documentation, and AI agents embedded in clinical workflows. Read more…

Life Sciences Today Podcast: Scaling Physical Therapy Without New Clinics. Danny Lieberman connected with Dr. Ashok Gupta at TheraNow, which uses virtual physical therapy to help health systems expand capacity without adding buildings or staff. Read more…

Healthcare IT Today Podcast: Leadership Succession. In light of Sumit Rana leaving Epic, John and Colin Hung discussed whether a company’s leadership and succession plan matters to customers, along with how to ensure a smooth path forward. Read more…

The Growing Gap Between Healthcare Risk and Healthcare Governance. AI can help organizations improve threat detection, prioritize alerts, and streamline security operations, but AI cannot compensate for fragmented governance or inconsistent risk management practices, noted Sam Peters at IO. Read more…

How to Maintain Patient Care During Communications Outages. Lori Stone at First Responder Network Authority, the overseer of national broadband network FirstNet, explained how FirstNet supports direct communications and acts as backhaul for Wi-Fi and other systems. Read more…

The Denial Economy Is Asymmetric. Knowing That Can Start to Fix the Issue. John Beene at Soupy Audit explained why providers don’t audit Recovery Audit Contractor extrapolations – and why they should respond by flagging risks, tracking payer activity, and monitoring changes in demand. Read more…

Taking a New Approach to Physical Security in Healthcare. It’s difficult for humans to continuously monitor live video for potential signs of security threats. Shikhar Shrestha at Ambient.ai described agentic physical security that can reason about what’s happening, decide if it matters, and initiate the right response. Read more…

How Trust-Centric Design Reduces Patient Stress and Retains Users. Yuliia Apanasenko at Phenomenon Studio provided four user experience principles that help reduce uncertainty and guide patients toward the next step in their care journey without leaving them to figure it out themselves. Read more…

This Week’s Health IT Jobs for August 5, 2026: Houston-based Texas Children’s Hospital seeks a CISO. Read more…

Bonus Features for August 2, 2026: Vizient projects 8% increase in healthcare IT spending for 2027; 70% of clinicians chart outside of working hours. Read more…

Funding and M&A Activity:

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



< + > Governance is the New Differentiator in EHR-Adjacent AI

The following is a guest article by Angela Adams, CEO at Inflo Health Healthcare has spent the past several years adding AI into clinical w...