For the 118th episode of the CIO podcast hosted by Healthcare IT Today, we are joined by Jason Ava, Director of Information Systems at Kahuku Medical Center, to talk about IT management in rural healthcare! We kick this episode off by discussing what makes managing IT unique at a rural healthcare organization. Next, we talk about some of the advantages of providing healthcare in a rural community. Then, Ava shares what went into the decision to implement Epic at Kahuku Medical Center. Ava also shares why he decided to work with OCHIN to implement Epic at his organization. Next, we dig into what Ava’s experience has been with Epic so far while also learning about some of the successes and learnings from this implementation. With Epic being a bigger application, we then discuss how it was a fit for rural health. Ava is very passionate about leadership, so we get into some of the big leadership lessons he has learned over the years. Lastly, we conclude this episode with Ava passing along the best piece of advice he’s received in his career.

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Overall trust in AI for healthcare has dropped to 44%, down from 52% in 2024, according to new digital health research. But among the 14% of Americans who actually use AI for health and wellness, trust sits at 88%.

That 50-point gap reveals something important: most people are being asked to trust something they can’t see, don’t control, and aren’t sure won’t be used against them.

What’s Driving the Hesitation

When we asked people to explain their hesitation, three concerns dominated. The first was fear of inaccuracy and potential harm, specifically concerns about AI “hallucinations” and misdiagnosis. As one Gen X respondent put it: “AI is often wrong. I wouldn’t trust it with my health.” The second was data privacy: how personal health information is collected, shared, sold, or exposed. And the third was the fear that AI dehumanizes healthcare, stripping away empathy and individualized care. One Gen Z respondent said she didn’t want her “healthcare in the hands of a robot” when she’d “rather be cared for by a human with human thoughts and feelings.”

The Pattern Healthcare Keeps Repeating

Electronic health records were supposed to make care seamless, but often made documentation a burden. Patient portals promised empowerment but delivered jargon-filled lab results with no context. Telehealth worked when it solved an obvious problem during the pandemic, then had to prove its value all over again.

The pattern is consistent: technology succeeds in healthcare when it reduces friction without creating new uncertainty. AI can translate complex medical language, coordinate care across fragmented systems and fill gaps when access is slow or expensive. But in healthcare, people adopt tools they trust to behave predictably, not tools with the most impressive capabilities.

What the Research Shows About Building Trust

Understanding why trust is falling requires a different kind of listening. We used a conversational research methodology for this study, combining quantitative data with open-ended responses and video feedback captured in real time on mobile devices. That approach surfaced the emotional texture behind the numbers: the language in an AI response that felt cold instead of helpful, the confusion about who to call when something seemed wrong. Those details don’t emerge in a standard five-point scale, but they reveal the specific moments where trust breaks down.

The data points to several patterns that separate experiences people trust from those they abandon.

Low-risk entry points drive adoption. Among current users, the most common applications are using chatbots for medical questions or symptom checking (55%), getting personalized health or fitness recommendations (35%), and interpreting test results or lab data (27%). Among people open to using AI, the highest interest is in scheduling appointments and reminders (50%), summarizing complex medical information (49%), and understanding insurance coverage (48%). These are friction points people actively want help with, and they don’t ask someone to gamble their safety on a model’s output.

Visible boundaries build confidence. When we asked what would make people more comfortable, respondents talked about knowing when AI is uncertain, having clear paths to human care when symptoms sound urgent, and understanding what the tool can and can’t do. As one millennial put it: “I would need to know that there are limitations and that it would be very clear when I need to see an actual doctor.” The research suggests that AI that knows when to stop is more reassuring than AI that always has an answer.

Privacy transparency matters more than privacy policies. The data privacy concerns that surfaced in open-ended responses were specific and practical: What data are you collecting? Can I use this without giving you everything? Will this show up in my record? Is it being sold? People want answers upfront, in plain language, with meaningful choices.

Accountability shapes trust. One recurring theme was the fear that no one would be responsible when AI gets something wrong. The responses suggest people are more open to AI when there’s an obvious handoff to a human when it matters and when they know who to reach if something feels off.

Confidence is the metric that matters. Utilization and satisfaction scores can mask underlying trust issues. The gap between users (88% trust) and non-users (38% trust) suggests the critical question is whether people understand what just happened, know what to do next, and feel more in control or more anxious after an interaction.

Trust shifts over time. A one-time study at launch won’t catch the moment when early enthusiasm turns into quiet abandonment or when a small friction point compounds into a trust issue. This is where ongoing research approaches like insight communities become valuable because they allow you to track how sentiment evolves as people have more experiences with AI, as features change, and as news cycles create new concerns. That continuous feedback loop gives you the early signals you need to course-correct before adoption stalls.

The Real Risk

There’s a version of this story where healthcare sprints ahead with AI deployment, hits utilization targets and checks the innovation box, then watches trust erode as people feel surveilled or dismissed. We’ve seen that movie before. It ends with backlash, regulatory intervention, and years spent trying to win back credibility.

The smarter play is to treat trust as infrastructure and build it into workflows, interfaces, data practices, and ongoing research, such as voice-of-market approaches. Trust requires continuous monitoring, not just a launch study. Organizations need to understand how people’s confidence shifts as they use AI over time, where friction emerges, and what reassures them at each stage of adoption, whether that’s in a chatbot, a care journey or an AI-enabled medical device in the home. In the medical devices arena especially, people may be more willing to embrace AI when it clearly improves convenience or monitoring, but less forgiving when setup feels confusing, alerts feel alarming, or the technology creates more stress than support.

Consumers aren’t waiting to be convinced that AI is smart. They’re waiting to be shown that it’s safe, human-centered, honest, and accountable when things go wrong. The organizations that keep listening to the market and to patients in real time (not just at launch) will be the ones that define what responsible AI in healthcare actually looks like.

About Dara St. Louis

Dara St. Louis is an Executive Vice President at Reach3 Insights, a full-service consultancy specializing in conversational insights. With over 20 years of experience in market research, Dara is a leader in CPG, tech, retail, health, and experiential insights, known for driving innovation and team empowerment through creative, tech-accelerated solutions in qualitative, quantitative, and community-based research.

Colibri Group Announces Acquisition of Audirie to Advance AI-Enabled Professional Learning

Acquisition Expands Colibri’s Capabilities in Simulation-Based Learning, Assessment, and Professional Skill Development

Colibri Group (Colibri), a professional education company that empowers professionals to achieve more, adapt, and thrive in their careers, announced today the acquisition of Audirie, an AI-driven simulation and assessment company focused on helping professionals build real-world skills through conversational practice, personalized assessment, and actionable feedback. Colibri Group is backed by Gridiron Capital, LLC (Gridiron Capital), a leading investment firm focused on partnering with management teams to build market-leading companies.

The acquisition represents a strategic investment in the future of professional education and the evolving ways professionals learn, practice, and build expertise throughout their careers. Audirie’s technology enables learners to practice realistic scenarios through AI-powered conversational simulations. Combined with Colibri’s domain expertise and decades of professional education experience, these capabilities create new opportunities for professionals to practice, build confidence, and prepare for real-world situations.

“We’ve made significant strides in AI-driven personalized learning experiences through innovations like Newt and Rubi, improving the effectiveness of learning while supporting the human expertise essential to professional success,” said Shravan Goli, CEO at Colibri Group. “Audirie adds exciting new capabilities that will help us leverage AI further in pursuit of what has long been the holy grail of learning — a personalized, interactive, one-on-one learning experience.”

Today, Audirie’s solutions are deployed primarily in healthcare settings. Colibri sees significant opportunities to extend these simulation-based learning capabilities across the professions and industries it serves. Together, the companies will focus on expanding access to this technology across licensing, continuing education, professional development, and workforce training solutions.

“Joining Colibri Group creates a tremendous opportunity to bring simulation-based learning to more professionals across a broader range of industries,” said Michael Alexander, Co-Founder of Audirie…

Full release here, originally announced June 17th, 2026.

ChartSpan Acquires Validic to Create the Industry’s Leading Platform for Data-Driven, Cost-Effective Clinical Care

ChartSpan Unites Best-In-Class Care Management with the Industry’s Largest Digital Health Platform for Wearable and Clinical Device Data, Enabling Continuous Patient Visibility and Improving Health Outcomes; This Positions ChartSpan as the Leader in Clinical Services and Infrastructure for Data-Driven Care

ChartSpan, a leading provider of care management services, today announced the completed acquisition of Validic, the leading personal health data platform. Together, ChartSpan and Validic will redefine remote care management by uniting specialized clinical services, expert care teams, and the technology infrastructure that transforms patient-generated health data into proactive clinical action. The combined company, ChartSpan, will provide clinical services, devices, and infrastructure for healthcare clients.

With Validic’s team and technology now part of ChartSpan, the unified company is uniquely positioned as the intelligence, conduit, and action layer powering effective remote health programs, including Chronic Care Management, Advanced Primary Care Management, Remote Patient Monitoring, and custom programs.

“Healthcare has historically made decisions based on snapshots of patient health,” said Christine Hawkins, Chief Executive Officer at ChartSpan. “By combining Validic’s personal health data infrastructure with ChartSpan’s clinical services, we’re helping healthcare organizations move from periodic observation to continuous understanding: identifying risk earlier, intervening sooner, and improving outcomes while lowering costs at scale. This partnership lays the foundation to turn health data into high-precision clinical action at every step of a patient’s journey, giving our customers the tools to stay ahead of both acute episodes and chronic disease progression for every patient they serve.”

“For over a decade, Validic has worked to make personal health data accessible and actionable within healthcare,” said Drew Schiller, Chief Executive Officer at Validic…

Full release here, originally announced June 22nd, 2026.

Stats

• A Buzz Health report found 94% of HR, CFO, and benefits leaders are very likely to adopt a tool to help educate employees on prescription affordability.
• A study by Piwik PRO and Verified Data found 73% of hospitals are ignoring Global Privacy Control opt-outs, which is recognized in 12 U.S. states. Additionally, 69% were using marketing or advertising cookies.
• A Smallpdf survey found healthcare workers lose 161 hours per year dealing with PDFs, with that lost productivity costing $5,635 per worker.
• A Teradata survey found 87% of senior tech and data leaders in healthcare said unifying data across business functions is a challenge for their organization.

Partnerships

• ECG diagnostics technology from AccurKardia will power the analytics behind Wellysis‘ cardiac monitoring offering in the U.S.
• Quantitative analysis technology from Cortechs.ai is now integrated with Viz.ai‘s disease detection and care coordination platform.
• Helix and AstraZeneca are partnering, with cohort data from Helix’s GenoSphere now accessible to AstraZeneca. In addition, the company announced Helix’s GenoSphere MCP connector is available in Claude Science, Anthropic’s AI workbench for scientists.
• Kinomatic and WHOOP launched Kinomatic RESTORE, a concierge recovery pilot program purpose-built for joint replacement.
• AI agent outreach technology from PatientGenie is now integrated with RevSpring‘s National Provider Directory MCP.
• Genomic testing and profiling services from Quest Diagnostics have been integrated with Flatiron Health‘s OncoEMR through a ​​pilot program with American Oncology Network.
• Remote therapeutic monitoring platform Medbridge is partnering with SaRA Health, a patient engagement, billing, and network infrastructure platform for outpatient rehabilitation.

Products

• 1upHealth announced the 1up Gateway to support compliance with the CMS Interoperability and Prior Authorization Final Rule among health plans with existing FHIR infrastructure.
• Senior care company Bold expanded its clinician-led weight management program to include GLP-1 prescriptions as part of the CMS Bridge program.
• Cantata Health Solutions expanded Arize, its EHR platform, with capabilities for child and youth services organizations.
• Carta Healthcare announced Lighthouse for Oncology, which allows health systems to apply Carta Healthcare’s Hybrid Intelligence approach to extracting data from cancer registries.
• Data fidelity company Kythera Labs launched the Clinical Semantic Bridge MCP on the Databricks Marketplace.
• The Institute for Healthcare Advancement released HealthLiteracyCopilot, a platform for evaluating health communication against validated, evidence-based standards.
• Trice Imaging launched Trice Workspace Reporting to support clinical decision-making and improve efficiency in obstetrics and maternal fetal medicine.
• Withings announced Withings Medical, a clinical care service that launched first for the Medicare population as part of the CMS ACCESS Model.

Implementations

• The National Basketball Players Association selected Teladoc Health as its preferred virtual care provider.
• New York state FQHC Sun River Health selected VisualDx for clinical decision support.

Company News

• CliniComp announced FDA clearance of PACS Viewer as a Medical Image Management and Processing System.
• Clover Health Investments subsidiary Counterpart Health published research indicating decision support for chronic care management is linked to improved HEDIS performance.
• Clinical AI vendor emtelligent published research showing its frontier models outperform LLMs alone in SNOMED CT coding.
• IKS Health complete its acquisition of TruBridge, which was first announced in May.
• InStride Health published research showing access to virtual specialty treatment can significantly reduce caregiver strain for individuals caring for youth with complex anxiety, OCD, and related disorders.
• RadiantGraph published research showing AI-powered voice outreach increased appointment completion rates by 3.4x and enabled a 9x increase in outbound call volume compared to human agents.
• Surgical Safety Technologies rebranded as Aimbient to reflect its aim to boost efficiency and quality across every procedural space in the hospital.

People

• Evergreen Healthcare Partners named Saad Chaudhry as CEO; he was most recently Chief Digital Information Officer at SSM Health.
• Pivot Point Consulting appointed Terri LeFort as CEO; she was most recently President at Nordic International.
• Qure.ai appointed Malika Shrivastava as Chief Marketing Officer; in addition, Qure.ai published research indicating greater likelihood of early-stage lung cancer detection using the company’s AI-enabled chest X-ray technology.
• Health information network eHealth Exchange appointed Doug Dietzman as President and Executive Director.

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.

The 2026 EHR Market is Cooling as Leaders Pivot to AI. Colin Hung connected with Paul Warburton at KLAS Research, which recently released its U.S. Acute Care EHR Market Share Report. The takeaways: Large systems are in a holding pattern, smaller systems are switching to Epic, and large-scale IT projects aren’t happening. Read more…

Practical AI and the Reality of Data Standards. At eHealth26, Canada’s leading health IT event, Aidan Lee and Matt Leducat OntarioMD joined Colin to discuss the role of actionable guidance for implementing healthcare data standards, particularly when it comes to AI use. Read more…

Building Trust and Interoperability Across Canadian Healthcare. Also at eHealth26, Colin talked to Karen Gauthier and Gurpreet (GP) Singh at ELLKAY about leading data migration projects in several provinces, with a focus on viewing archiving and interoperability as part of a larger data strategy. Read more…

Unlocking RCM Capabilities With Generative AI. Malinka Walaliyadde at AKASA sat down with John to talk about AI’s role in quickly and accurately coding patient records, which contain dozens of documents and 50,000 words for the average patient. Read more…

Where RCM Needs a Human Touch Instead of AI. This is an important question as automation takes hold in the revenue cycle. Advice from the Healthcare IT Today experts included complex denials and appeals, assessing performance, understanding regulations, and providing empathy to patients in need. Read more…

The Power of Voice AI Agents in Automating RCM. John connected with Sam Schwager at SuperDial, which rolled its own AI voice agent and marketed it to other RCM vendors. The company has since made more than 7 million automated calls. Read more…

Sumit Rana to Step Away from Epic. John had a chance to interview Epic’s President, who’s stepping away from Epic on August 14 to devote more time to his family – which is certainly understandable as he recently lost his father. Among Sumit’s proudest moments at Epic: Seeing MyChart grow to 195 million users worldwide. Read more…

Life Sciences Today Podcast: The Industry You’ve Never Heard of Is About to Change Hands. Rachel Timberlake at Bend Bioscience talked to Danny Lieberman about why disruption is coming to the world of contract development and manufacturing. Read more…

Healthcare IT Today Podcast: RCM Trends. John and Colin reflected on what they heard about RCM during the spring conference season. That made them wonder: Are we heading for a day when we have totally autonomous RCM? Read more…

‘The Pitt’ Cyberattack Scenario Wasn’t Fiction – Most Health Systems Still Aren’t Ready. Most downtime procedures were designed for temporary outages, not prolonged operational paralysis, noted Matt DeFrain at Arcova. The solution starts with reframing cybersecurity around patient impact. Read more…

The Strategic Value of a Patient Portal Service Desk. The success of a patient portal relies on the support structure that enables patients to effectively utilize them. Specialized support for account access, navigation, technical troubleshooting, and patient education helps accomplish this, said Chris Durham at HCTec. Read more…

Closing the Gap Between Personal and Population Health. Saikrishna Kavali at Sacred Heart University detailed outlined a FHIR-based family health record framework. This aims to bridge the gap between detailed medical records and scattered sources of household intelligence such as availability of food and levels of stress. Read more…

Innovation Fatigue in Healthcare Is Real. Here’s How to Avoid It. Melissa Powell at The Allure Group offered five tips for ensuring innovation leads to measurable improvements in care delivery and clinician experience. Starting with workflows and co-designing with clinicians are important first steps. Read more…

Why Connected Doesn’t Necessarily Mean Cared For. Despite growth in FHIR API adoption, healthcare’s walled garden problem is real and underacknowledged. Ryan Carlson at Soracom said successful deployments built care models around constraints such as unclear data flows and indirect integrations. Read more…

This Week’s Health IT Jobs for July 8, 2026: Roles in behavioral health, community health, and cybersecurity. Read more…

Bonus Features for July 5, 2026: 58% of dermatology practices see patients daily with AI-generated diagnoses; 94% of CIOs say AI delays would put their orgs at a competitive disadvantage. Read more…

Funding and M&A Activity:

• Assort Health announced a $120 million Series C funding round; the company makes an AI agent for specialty care workflows.
• Cadence announced in $100 million in Series C funding; the company’s AI platform supports chronic care management for older adults.
• Clinical decision support vendor xCures closed $46 million in Series B financing.
• Brazil-based clinical AI platform Telepatia raised $33 million in Series A funding.
• Primary care platform Elation Health acquired Aster, an AI-native EHR focused on women’s health.
• Vizient acquired Empierus, an advisory firm specializing in IT contracting and healthcare technology management.
• Compliancy Group acquired Healthicity, a provider of healthcare auditing and compliance software.
• Belmont Medical Technologies acquired Arcos, maker of blood transfusing tracking and resuscitation support software.

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

This week, we actually created some of our own cartoons that highlight some of the absurd pitches we get from startup companies.  BTW, the worst thing you can do when pitching us is to share something that we know isn’t true.

This one happens quite a bit.  If you describe yourself narrow enough, then I guess you are unique.  I’m the only health IT media guy in Las Vegas who has written for 20 years with a receding hairline and 5 kids.  Definitely one of a kind.

I think most people should remove the word only from their pitching.  It’s almost never true and you really lose credibility when we know of 5-5000 others doing it.

We hope you enjoyed these.  Have a great weekend!  We’ll see you back next week with more great healthcare IT content.

Timberlake has spent two decades inside this industry. She started at a small owner-operated CDMO doing — in her words — “chief cook and bottle washer” work and moved through roles of increasing scale into national sales leadership. Timberlake is one of the few people who can explain this industry in plain language — she has lived every altitude of it, from small-shop BD to national sales leadership inside a large platform, and she is now choosing what comes next.

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

• What is a CDMO? What does a sponsor actually buy, and why doesn’t every drug or device company just build its own factory?
• Chief cook and bottle washer to national sales — what did a small CDMO look like when you started, and what did business development actually mean back then?
• When a biotech CEO calls a CDMO for the first time, what does the first ninety days actually look like — and where does it most often go sideways?
• Onshoring is the tailwind everyone is talking about — BIOSECURE, tariffs, GLP-1 capacity. What are you actually seeing in the RFPs?
• What should a founder ask a CDMO in diligence that most of them don’t think to ask?
• What is the biggest anti-pattern you see at the sponsor–CDMO interface?
• What’s the kind of problem you’d most want to work on next?

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:

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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!

When this season of “The Pitt” depicted a hospital spiraling into chaos after a ransomware attack forced clinicians to abandon digital systems and go analog, many viewers saw it as gripping television. Healthcare cybersecurity leaders saw something else entirely: a realistic preview of what happens when a cyber event becomes an operational crisis.

On the show, clinicians lose access to digital health records, lab orders disappear, paper charts replace connected systems, and patient care begins to deteriorate in real time. The frightening part is how familiar the scenario feels.

For years, many organizations approached cybersecurity through the lens of compliance and baseline controls. Did we meet the HIPAA requirement? Did we complete the audit? Do we have the right tools in place, and are they secure? Those questions still matter, but they are no longer enough.

The better question is, if critical systems disappeared tomorrow, how long could your organization safely continue delivering care?

Most healthcare organizations are not prepared to answer.

Downtime Planning Was Built for Hours, Not Weeks

Nearly every health system has downtime procedures. The problem is that most of them were designed for temporary outages, not prolonged operational paralysis.

Across healthcare, cyberattacks have evolved beyond data theft and financial extortion. Today, the real risk is operational disruption at scale. We are now seeing attacks capable of delaying surgeries, disrupting care coordination, taking down entire hospital networks, and jeopardizing patient safety.

That shift requires healthcare leaders to fundamentally rethink what cybersecurity preparedness actually means.

Healthcare leaders often think about cyber resilience in terms of restoring technology. They should also be thinking about sustaining patient care during extended disruption. It’s worth noting that, as operational pressure increases, the likelihood of medical error rises with it.

It is now table stakes to test whether manual workflows can realistically scale beyond a few hours. Teams must also audit and understand where hidden dependencies exist between systems to identify which clinical and operational processes would fail first under prolonged downtime conditions.

The Biggest Threats Often Enter Through Third Parties

One of the most important lessons from recent healthcare cyber incidents is that organizations do not need to be directly breached to experience catastrophic disruption.

Healthcare operates through a deeply interconnected network of vendors, technology providers, partners, and external platforms. Every connection creates another potential attack vector.

The Change Healthcare incident illustrated this reality on a massive scale. A compromise originating through a third party affected claims processing, pharmacy operations, payment systems, and healthcare delivery organizations across the country. Many hospitals that considered themselves operationally secure still found themselves severely impacted.

The challenge becomes even more complicated as healthcare organizations rapidly adopt AI-enabled tools and external data platforms. Employees are also increasingly using generative AI tools on personal devices or outside formal governance structures. In many environments, shadow AI adoption is already happening at scale, creating significant exposure risks around sensitive data, metadata leakage, third-party integrations, and uncontrolled information sharing.

Healthcare organizations need a far more comprehensive understanding of how all of these pieces are woven into their environment, what data is accessed where, and how privilege escalation could occur. You can’t govern what you can’t see, or what you don’t know exists. Visibility across partners, vendors, AI tooling – visibility across the full ecosystem – is the first step.

Most of All, Cybersecurity Must Be Reframed Around Patient Impact

One of the reasons “The Pitt” resonated so strongly with viewers is that it showed how patient care suffers when systems fail. Now more than ever, maintaining quality patient care must become the central organizing principle for healthcare cybersecurity moving forward, regardless of the scenario.

Too often, cybersecurity conversations are narrowly focused on compliance metrics, technical controls, or financial loss. Those issues matter, but they miss the broader operational stakes. Boards, executives, IT leaders, clinical leadership teams, and security teams all need to operate from a shared understanding that cybersecurity resilience is directly tied to care continuity.

Organizations should be running realistic operational resilience exercises that include clinical leaders and staff, not just IT teams. They should be stress-testing how long they can operate under degraded conditions. They should understand how communications, supply chain systems, imaging workflows, and third-party dependencies intersect with all team members’ unique roles during a crisis.

Most importantly, they need to stop viewing cybersecurity preparedness as the goal. The goal is maintaining safe patient care under adverse conditions.

The Next Healthcare Cyber Crisis Will Be Operational

The healthcare industry is entering a new era of cyber risk where operational disruption will define the severity of an incident. “The Pitt” felt believable because healthcare leaders already know how fragile interconnected systems can become under pressure. Increasingly, that pressure is what healthcare leaders need to be preparing for now.

This shouldn’t become a battle for who has the longest compliance checklists or the largest security budgets. Instead, it’s the organizations that prepare for resilience at every level of the operation that will see the most enduring success.

About Matt DeFrain

Matt DeFrain is Managing Director at Arcova, where he advises healthcare organizations on cybersecurity, governance, operational resilience, and risk management strategies. He works closely with healthcare leaders to strengthen preparedness against evolving cyber threats that impact both technology infrastructure and patient care.

xCures Closes $46 Million Series B Financing to Transform Fragmented Medical Records into Decision-Ready Data Through Its Clinical Clarity Engine

New Capital Brings Total Funding to More Than $76 Million and Will Fuel Continued Expansion of the Company’s Platform for Turning Fragmented Medical Records into Decision-Ready Clinical Data

xCures, a pioneering healthcare data company focused on improving healthcare outcomes, today announced the close of a $46 million Series B financing round led by Innovius Capital, with participation from iGrow, GKCC, Spring Mountain Capital, and existing investors. The new capital brings xCures’ total funding to more than $76 million and will support the continued expansion of the clinical clarity layer to turn fragmented medical records into decision-ready clinical data.

Patient information is scattered across thousands of labs, hospitals, imaging centers, and EMRs, often arriving as unstructured documents that are difficult to use in clinical workflows. The xCures Clinical Clarity Engine brings together three integrated capabilities: decision-ready checklists built from automated patient histories and backed by evidence-grade data. It creates the clarity that providers, value-based care, diagnostics labs, and consumer health organizations have long needed.

To date, xCures has processed over 300 million medical records sourced from more than 550,000 healthcare locations nationwide, supporting clinical decisions for millions of patients across the U.S.

“Healthcare has spent decades generating enormous amounts of patient data without a reliable way to make that information usable. We’re changing that,” said Mika Newton, CEO at xCures. “This financing allows us to accelerate product development, expand our team, and help more organizations turn fragmented records into information they can actually act on.”

Stu Posluns, Partner at Innovius, added, “The promise of AI in healthcare depends on having accurate, complete, and trustworthy clinical data. xCures has built by far the most compelling platform we’ve seen for turning fragmented medical records into actionable clinical intelligence…

Full release here, originally announced June 24th, 2026.

Cadence Raises $100M Series C Led by Spark Capital to Automate Chronic Care

This New Investment Will Help Scale AI Agents to Meet the Needs of Over 56 Million Older Adults with Chronic Disease Amid a Deepening Clinician Shortage

Cadence, the clinical AI company managing chronic care for older adults, announced a $100 million Series C, amid adoption of its AI-powered care model across the nation’s leading health systems.

The Series C was led by Spark Capital. Thrive Capital, General Catalyst, Coatue, B Capital, Corewell Health Ventures, Memorial Hermann, and Duke Health participated in the round.

Today, Cadence also announced new affiliations with Duke Health, a world-class academic health care system serving patients across North Carolina, and Texas Health Resources, the nonprofit health system that cares for more patients in North Texas than any other. Now working alongside over 20 leading health systems, Cadence treats more than 100,000 active patients, has demonstrated significant clinical improvements in peer-reviewed literature, and saves Medicare roughly $2.7 million every week. The company tripled annual recurring revenue in 2025.

“We believe the most consequential AI companies of the next decade will be built in categories where the technology changes the underlying mechanics of the business. Cadence has done the hardest work first – demonstrating clinical outcomes, building trust with the country’s leading health systems, and proving out the safe and effective deployment of AI inside care delivery,” said Will Reed, Partner at Spark Capital and new Cadence Board Member. “There is no other AI care platform in the country with this combination of scale, peer-reviewed clinical outcomes, and economic proof.”

“At Duke Health, our mission is to advance the health of our patients and the communities we serve. The moments that matter most for a patient’s health often happen at home, not in the clinic,” said Jeffrey Ferranti, MD, MS, Senior Vice President and Chief Digital Officer at Duke Health…

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

While attending eHealth26, I sat down with Aidan Lee and Matt Leduc, both Executive Directors at OntarioMD, to discuss their respective sessions on data standards and deploying AI midstream into established workflows.

Key Takeaways from OntarioMD at eHealth26

• Standards need practical translation. Creating a healthcare data standard is only the first step. Vendors need active support to incorporate and activate those standards within their solutions
• AI requires governance. Integrating AI into healthcare operations requires careful consideration of privacy, security, patient safety, and clinical workload. Cross-functional governance is needed.
• Technology cannot ignore human factors. A successful AI rollout depends heavily on understanding the direct impact on a clinician’s daily workload rather than just the software capabilities.

Translating Data Healthcare Standards for Vendors

Establishing Pan-Canadian Health Standards (like CACDI) is a massive achievement, but those standards sit idle if electronic medical record vendors do not know how to implement them. Organizations like OntarioMD bridge that gap by partnering with agencies like CIHI to provide actionable guidance to the marketplace.

“Vendors always ask, ‘What do we do with these [standards]?’ and this is where Ontario MD’s approach and history will benefit the EMR community,” Lee explained.

Building AI with Governance

When OntarioMD introduced an artificial intelligence tool to extract information from hospital and radiology reports within their Health Report Manager (HRM) system, privacy was a priority. That was by design.

“You need to have the right controls in place. Introducing artificial intelligence is something that has to do that in a constrained way,” Leduc noted.

The OntarioMD hopes their approach will serve as an example to others – that AI is not to be feared but does need to be respected.

Prioritizing Human Factors in AI

The initial expectation for clinical AI was that it would instantly reduce physician workloads and replace human effort. In practice, inserting immature AI into an established workflow can easily backfire if the deployment fails to adapt to the reality of human behavior.

“It really is all about the human factors around the way you’ve introduced AI,” Leduc observed.

Ultimately, AI is simply a tool to handle heavy data processing so doctors can focus on the human elements of care they do best. Lee agreed, adding that AI is “giving physicians ‘superpowers’ in some cases.

Questions Healthcare IT Leaders are Asking

Why do vendors struggle to adopt new data standards?
Standards are often highly technical and disconnected from the daily realities of software development. Vendors require practical guidance and partnership to understand how to build these standards into their existing architectures in a way that benefits clinicians.

How should organizations evaluate the privacy risks of clinical AI?
Leaders must treat AI tools with the same strict governance applied to any clinical system. Organizations must ensure that any AI vendor operates within a constrained environment where patient data is isolated and protected from external model training.

Learn more about OntarioMD at https://www.ontariomd.ca/

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