OpenAI’s announcement of ChatGPT for Clinicians signals a new phase of healthcare AI adoption. The company is making a clinician-focused version of ChatGPT available for free to verified U.S. physicians, nurse practitioners, physician assistants, and pharmacists.

That matters because this is not a futuristic AI concept. It is a practical workflow tool designed to support the daily work that clinicians already struggle to complete.

OpenAI says the tool can support clinicians with documentation, medical research, referral letters, prior authorization language, patient instructions, care consultation support, and clinical search. It also includes reusable workflow “skills,” deep research across medical journals, and privacy protections that prevent conversations from being used to train models.

For clinicians, the benefits are clear. The tool can help reduce administrative burden, speed up routine writing, summarize complex information, support patient-friendly explanations, and make medical research easier to navigate. At a time when clinicians face inbox overload, documentation fatigue, and growing administrative demands, even modest workflow relief matters.

The more important point for healthcare CIOs is adoption.

OpenAI is not waiting for every health system to complete an enterprise AI strategy. It is putting a free tool directly in clinicians’ hands. A physician, pharmacist, NP, or PA can verify their credentials, download them, and start using them without waiting for an enterprise rollout.

That creates a familiar problem for CIOs: if the enterprise does not deliver usable tools fast enough, users will find their own.

Healthcare has seen this pattern before with mobile apps, cloud storage, messaging platforms, analytics tools, and generative AI. Clinicians adopt what helps them get work done. Governance usually arrives later, often after usage has already spread.

This announcement puts pressure on health systems to move faster. CIOs, CMIOs, compliance teams, and clinical leaders need to give clinicians an approved enterprise path that offers the same convenience, stronger controls, and better workflow integration.

The real opportunity is not simply giving clinicians access to ChatGPT. The real opportunity is embedding AI into clinical work: inside the EHR, documentation flow, inbox management, referral process, patient communication, prior authorization workflow, and knowledge search experience.

If health systems fail to do that, clinicians may default to the free tool because it is easy, available, and useful. That creates risk around PHI handling, documentation quality, policy consistency, auditability, and clinical accountability.

The CIO takeaway is straightforward: free clinician AI changes the adoption curve.

Health systems can no longer treat clinician-facing AI as a slow innovation project. They need a governed enterprise option that feels as easy as the consumer tool but works inside the health system’s security, privacy, compliance, and workflow model.

Clinicians want relief. OpenAI just gave them a direct path.

Now health systems must decide whether they will lead that adoption—or chase it.

U.S. Department of Veterans Affairs

• The VA implemented its unified Federal EHR at four Michigan medical centers, initiating the first of 13 planned deployments this year.

• The system supports real-time data sharing, enhances care coordination, and streamlines clinical workflows.

• Why it matters:
  The VA’s EHR transformation shows that process alignment across sites is essential. Large-scale initiatives increase benefits, such as data liquidity and care standardization, but also raise risks, such as workflow disruption and clinician burden. Disciplined execution and strong change management are critical.

2. Private equity reshapes medtech with $1.27B deal for

Avanos Medical

• American Industrial Partners will acquire Avanos in an all-cash deal valued at approximately $1.27 billion, representing a 72% premium.

• The acquisition is expected to accelerate innovation and provide greater capital flexibility for growth.

Why it matters:
Private equity continues to identify margin and growth opportunities in medtech. Anticipate increased cost discipline, portfolio rationalization, and faster commercialization cycles. Providers may experience short-term pricing pressure, but also benefit from greater innovation and improved vendor alignment over time.

3. Interoperability alliances deepen across Europe

• Tieto Caretech, x-tention, and Better announced a strategic partnership.

• The partnership will develop modular, standards-based clinical data platforms using the openEHR architecture.

Why it matters:
Composable, vendor-neutral platforms are gaining momentum. U.S. health systems should prioritize data orchestration across clinical workflows, AI, and partnerships rather than EHR ownership to remain competitive.

4. CMS ACCESS model expands tech-enabled chronic care

• More than 150 organizations, including vendors such as WHOOP, have been accepted into the CMS ACCESS program, which focuses on scalable chronic care innovation.

Why it matters:
The CMS ACCESS program highlights the shift toward technology-enabled, outcome-focused care. Health systems should prioritize continuous patient monitoring, digital therapeutics, and the use of patient data as core infrastructure for reimbursement.

5. Supply chain IT flagged as a margin crisis

• A new report projects that by 2026, poor supply chain visibility and manual workflows will directly erode hospital margins and disrupt care continuity.

• Why it matters:
  Modernizing supply chain IT has become a top financial priority for health systems. Automation, predictive analytics, and vendor integration are essential to prevent hidden margin losses.

6. Vendor-driven logistics innovation:

Medline

• MMedline launched Pick Pack Pro, a custom fulfillment technology designed to improve supply chain efficiency.

• Why it matters:
  Vendors are becoming strategic partners by integrating into operational workflows. Health systems may gain efficiency but also face increased dependency on vendors.

The AI Revolution and the Security Reality: This Week in Healthcare IT

As we enter the first full week of April 2026, the rise of agentic AI is reshaping healthcare IT. EHRs are being redesigned, and major AI deployments are accelerating change across the sector.

Here are the top stories you need to know from the week of April 1–8, 2026.

1. Greenway Health Reinvents the EHR with “Novare.”

Clinicians have long noted that Electronic Health Records (EHRs), digital versions of patients’ medical histories, often resemble outdated spreadsheets. This week, Greenway Health introduced Novare, which they describe as the first natively AI-enabled EHR.

Unlike legacy systems that add artificial intelligence (AI), software that simulates human decision-making, to existing code, Novare is built from the ground up with agentic AI, which can autonomously perform tasks for clinicians. The aim is to eliminate workarounds and create a system that anticipates clinician needs, automating documentation and revenue cycle tasks in real time. This approach signals a significant shift away from legacy systems.

2. Post-Acute Care Goes “All In” on AI

Creative Solutions in Healthcare announced a company-wide rollout of ExaCare AI across its 160 skilled nursing facilities (SNFs), marking one of the largest and fastest deployments in the sector. These facilities provide specialized medical care and rehabilitation.

“We have to be just as intentional about how we scale our systems as we are about our growth,” said Gary Blake, CEO of Creative Solutions.

The platform aims to improve the preadmission process, which is often slowed by paperwork and phone calls. By using AI to summarize patient journeys and streamline referrals, the initiative now processes over 1,500 referrals daily. This demonstrates that smart facilities using advanced digital and AI technologies have become the standard in post-acute care.

3. Cardiology Gets a “Second Set of Eyes.”

The Joint Research Center (JRC) released a report this week, Artificial Intelligence in Cardiovascular Care: From Promise to Practice, highlighting that AI now performs coronary artery calcium scoring as accurately as specialist radiologists.

The JRC also emphasized the importance of infrastructure. While AI can detect blockages in seconds, many hospitals lack the necessary hardware and supporting software. In response, the EU has committed €20 million to accelerate AI deployment in cardiovascular care.

4. The Security Reality Check: CareCloud & Hims, & Hers

This week also underscored the ongoing risks to valuable healthcare data from cyber threats.

• CareCloud confirmed a significant cyberattack this week that resulted in the theft of patient data and an 8-hour disruption of its EHR environment.

• Hims & Hers also disclosed a breach involving stolen support tickets from a third-party service, highlighting that security is only as strong as the least secure vendor’s application programming interface (API), the software connection between systems.

The Bottom Line

There is a clear shift from experimental to operational AI. With Greenway’s new EHR and Creative Solutions’ SNF rollout, the focus is now on efficiency at scale. However, the CareCloud breach highlights that as systems become more integrated and intelligent, cybersecurity risks increase.

Sources:

• Greenway Health: Novare Launch Announcement (April 7, 2026)

• Las Vegas Sun: Creative Solutions & ExaCare AI Rollout (April 8, 2026)

• European Commission JRC: AI in Cardiovascular Care Report (April 7, 2026)

• Acronis: MSP & Healthcare Cybersecurity Digest (April 7, 2026)

Healthcare AI announcements over the last several months reveal a market that is growing quickly. The conversation is no longer centered on hype, novelty, or generic chatbot capabilities. It is shifting toward more practical priorities: connected health data, trusted workflows, and measurable value for both patients and providers. Across the market, vendors are moving beyond broad AI claims and focusing on how their tools fit into healthcare operations, clinical decision-making, and the consumer health experience.

One of the clearest trends has come from vendors building consumer-facing health copilots. Perplexity Health reflects that shift. Rather than positioning AI as a standalone search tool, Perplexity has emphasized the value of combining health-related data sources into a more personalized experience. Its broader ecosystem announcements, including integrations with partners such as b.well and Function, point to an emerging industry-wide strategy. Healthcare AI vendors increasingly understand that strong model performance alone is not enough. The real advantage comes from connecting fragmented records, labs, wearable data, and other health inputs into a unified experience that can support better answers and more relevant guidance.

Microsoft has also pushed this strategy forward with Copilot Health. Its healthcare announcements show how large platform companies are trying to create secure environments where users can interact with health information more seamlessly. Microsoft’s positioning suggests that the future of healthcare AI will not reside in a separate innovation lab or remain confined to pilot projects. Instead, it will live inside broader digital ecosystems that bring together records, lab data, and device-generated information in ways that feel more seamless to both consumers and care teams. That direction matters because it highlights a larger market reality: healthcare AI is becoming an infrastructure conversation, not just a feature discussion.

On the provider side, Oracle has taken a more workflow-driven approach. Through Oracle Health Clinical AI Agent, Oracle has focused on helping clinicians reduce documentation burden and improve efficiency in high-pressure settings such as emergency and inpatient care. That strategy aligns with what many health systems want most from AI today. They are not asking for an abstract promise. They want tools that reduce clicks, speed note creation, support clinician productivity, and create value inside the daily workflow. Oracle’s positioning shows that enterprise healthcare AI is moving away from experimentation and toward embedded operational support.

Epic’s recent AI messaging reinforces the same point. With updates on AI Charting and broader AI results, Epic continues to show that AI is becoming native to the electronic health record rather than an external add-on. That distinction matters for CIOs and digital leaders. When AI capabilities live inside the core platform, adoption becomes easier, governance becomes more manageable, and the organization has a better chance of translating technology investment into real workflow improvement. Epic’s approach reflects a broader industry pattern in which EHR vendors are trying to keep AI close to the point of care.

OpenAI and Anthropic also remain important players in this evolving market. ChatGPT Health and Claude for Healthcareshow that foundation model companies want a direct role in healthcare, not just as model providers behind the scenes, but as branded platforms with healthcare-specific positioning. Their announcements signal that privacy, compliance, and healthcare-specific safeguards are now central to the competitive conversation. In healthcare, general intelligence is not enough. Vendors must also demonstrate that their tools can operate responsibly in sensitive environments where trust, oversight, and data stewardship carry equal weight with performance.

In summary, these announcements highlight three main takeaways driving the healthcare AI market forward: consumer-facing vendors are prioritizing the aggregation and personalization of health data; enterprise vendors are embedding AI directly into clinical and operational workflows; and platform companies are working to own the environments where health interactions occur. The key lesson is that future market leaders will be defined not by bold claims but by their ability to connect data, integrate seamlessly into care, and deliver measurable results for healthcare organizations.

Amazon launched Amazon Connect Health, an AI-enabled platform that automates key administrative tasks, including patient verification, appointment scheduling, medical history intake, clinical documentation, and coding. This move aims to modernize patient access and staff productivity, signaling to healthcare CIOs that AI’s next big impact could be in contact centers and access workflows, not just clinical settings.

Microsoft expanded the definition of ambient AI. At HIMSS 2026, Microsoft introduced new Dragon Copilotcapabilities, including Work IQ context, partner-built apps and agents, role-based workflows, proactive coding support, and expanded support for physicians, nurses, and radiologists. Microsoft is positioning Dragon Copilot as a unified workflow layer, not just a documentation assistant. CIOs should pay attention because this is where the market is heading: ambient tools are maturing into enterprise workflow platforms that connect clinical productivity, revenue cycle, and embedded intelligence in a single operating model.

Google Cloud made the case for agentic AI tied to outcomes. This week, Google Cloud highlighted Gemini-powered healthcare agents, including CVS Health, Highmark Health, Waystar, and Quest Diagnostics. The announcement focused on patient engagement, workflow automation, revenue cycle performance, and easier-to-read clinical information. That matters for CIOs because the strongest AI pitches now come wrapped in operational metrics and enterprise use cases. The conversation is no longer about whether a model can generate text. It is about whether a platform can reduce denials, simplify work, and scale safely across the health system without creating one more mess for IT to clean up at 2 a.m.

Epic pushed AI deeper into the core record. Ahead of HIMSS26, Epic previewed a no-code Agent Factory and continued expansion of AI tools across documentation, patient engagement, revenue cycle, and clinical workflows. Epic’s strategy is increasingly clear: it wants customers to build and orchestrate AI from inside the EHR environment rather than bolt it on from the outside. For CIOs, this move signals that Epic aims to control a greater share of the healthcare workflow layer, raising the competitive stakes as other vendors must now demonstrate unique value and seamless integration to avoid being displaced. The contest is increasingly about platform centrality and the ability to orchestrate AI within core health operations.

Ambient scribes have moved beyond the pilot phase and are becoming standard for clinicians. For healthcare CIOs, the central question is no longer whether to adopt this technology, but how to scale it responsibly.

This shift has accelerated over the past year: ambient AI has moved from novelty to necessity. Clinicians expect it. Health systems budget for it. Boards ask about it. What started as documentation relief now drives measurable impact on clinician satisfaction, chart closure time, and patient engagement.

Meanwhile, as the hype around agentic AI continues, ambient AI has matured in a more practical way. It embeds directly into workflows and runs quietly in the background. It reduces cognitive load without demanding behavior change, making it distinct. Rather than requiring clinicians to learn new systems, it removes friction from existing ones.

CIOs now evaluate ambient tools the same way they evaluate EHR modules: performance, security, governance, and ROI. Healthcare CIOs want to know:

• - Does the tool integrate natively or sit as an additional layer?

• - How does it handle data security and PHI?

• - Can we measure real productivity gains?

• - Who owns the output, and how do we audit it?

These are not experimental questions—they are operational ones.

Ambient solutions are no longer “nice to have.” In competitive labor markets, they are table stakes. When one health system offers AI documentation support, and another does not, clinicians notice. Recruitment teams notice. Retention numbers reflect it.

Given this, the next phase for CIOs is governance at scale. That means standardizing vendor selection, aligning with compliance teams, setting clear documentation policies, and defining performance metrics. It also means resisting the urge to chase every new AI feature, instead doubling down on tools that demonstrably reduce burnout and improve throughput. The real question will come down to whether an organization trusts the solution embedded in its EMR vendor or explores a bolt-on solution.

Rural hospitals must maintain broad clinical coverage despite limited staffing, rising supply costs, an unpredictable payer mix, and an aging, sicker population. Since 2005, 110 rural hospitals have closed permanently, including 24 in the past five years. The Center for Healthcare Equity and Reform estimates that nearly 800 more are at risk of closure due to financial distress.

Healthcare leaders believe that they can turn to technology, especially AI, for solutions. However, AI is not a simple fix. Technology can drive meaningful change only when rural health leaders align it with clear operational and clinical priorities. CIOs should ensure their IT strategy focuses on the following two areas.

Extend And Expand Technology Capabilities

Rural hospitals face daily challenges with patient access, including delayed transfers and limited specialty coverage. Clinicians often assume multiple roles rather than focusing on their primary expertise. While technology cannot create new specialists, it can provide timely access to specialty expertise for care teams. Expanding the right technology capabilities helps retain more patients locally, reduce unnecessary transfers, and shorten the length of stay.

Many rural leaders have demonstrated success with virtual specialty coverage, particularly telestroke and tele-ICU services. These solutions provide frontline teams with faster access to specialists, supporting better clinical decision-making. The objective is to make specialty access reliable and routine.

When staffing is limited, technology can help maintain capacity by enabling remote nursing support and virtual sitters. Virtual sitters help prevent falls without requiring one-to-one assignments in every room.

For rural health CIOs, foundational technology determines the success of these programs. Focus on implementing robust connectivity and network infrastructure, followed by strong system integration. Build redundancy with multiple circuits and consider newer connectivity options such as Starlink and 5G where appropriate. The key is integrating each solution directly into existing workflows while maintaining system uptime. Embed virtual care and hospital-at-home solutions directly into the EHR and daily operations instead of running standalone applications that add complexity. These programs are only effective when core technology operates reliably and consistently.

Fractional Or Shared IT Strategy

A fractional or shared IT strategy does not require rural hospitals to give up their independence. Instead, it allows them to avoid operating like a large system with limited resources. Small hospitals cannot independently negotiate, secure, staff, and innovate at the same scale. Rural hospitals must use shared technology services just like other healthcare service lines.

CIOs should begin by establishing fractional or shared cybersecurity and IT operations through a trusted vendor or regional hospital partner. Attackers often target rural hospitals because they have limited cybersecurity defenses. At a minimum, rural health CIOs must start with a shared model for security operations center, patch management, and managed endpoint protection across the organization.

Rural hospital leaders should centralize essential infrastructure while maintaining local governance. Technology alone won’t solve reimbursement challenges, but it can expand access and support care delivery. It creates value not by looking impressive, but by running reliably, fitting into daily operations, and staying tightly focused on outcomes.

Cybercrime now drains trillions of dollars from the global economy, and healthcare remains one of the most profitable targets. Ransomware attacks do more than lock systems. They destroy trust in data, backups, and identities. Once attackers gain administrative access, traditional disaster recovery plans often make matters worse by spreading the infection rather than containing it. A white paper by Rubrik and CHIME argues that prevention alone is failing and that resilience has become a clinical imperative.

Minimum Viable Hospital

Healthcare has long planned for physical disasters by separating data centers and failing over systems. Ransomware breaks that model. When malware contaminates backups, distance no longer matters. What matters is isolation.

Healthcare technology leaders described the move from standard disaster recovery to cyber recovery using isolated recovery environments. These environments create “security distance” so teams can restore systems without reintroducing malware.

Because building this capability is expensive, organizations must prioritize ruthlessly. That is where the concept of the “Minimum Viable Hospital” comes in. Instead of trying to recover hundreds of applications, CIOs must identify the small set that keeps patients safe and operations running. Labs, pharmacy, imaging, identity, and payroll rise to the top. Many systems people assume are critical simply are not.

This approach forces uncomfortable but necessary conversations. It also shortens downtime from weeks to days when an attack happens.

This is the same concept I mentioned in April, 2025, when I created this concept.

Identity Is the New Front Door

If resilience is the safety net, identity is the tightrope. Attackers no longer need to break in through the network when they can log in.

Healthcare leaders were blunt in the research interview: basic MFA is no longer enough. SMS codes, one-time passwords, and static credentials fail under social engineering, SIM swapping, and deepfake-assisted fraud. Identity verification must adapt.

Health systems are responding with higher-friction controls for high-risk actions. Video-based verification, badge checks, biometrics, and just-in-time access are becoming standard. Privileged Access Management and Privileged Identity Management are no longer “nice to have.” In many cases, they are required for cyber insurance.

The rise of non-human identities, including autonomous AI agents, only raises the stakes. Service accounts with passwords that never expire represent a silent but serious risk.

Zero Trust as a Culture, Not a Tool

Technology alone does not create resilience. Governance does.

Leaders shared how Zero Trust only works when security decisions move out of isolated IT committees and into everyday operational forums. Embedding security into clinical, architectural, and administrative discussions changes the tone from “no” to “how do we do this safely?”

Several organizations now run planned downtimes during business hours. These drills force teams to use paper workflows and manual processes while leadership watches. The goal is not disruption. It is muscle memory. When a real attack happens, clinicians already know what to do.

The Persistent Blind Spot: Medical Devices and IoT

Even as identity hardens, attackers look for softer targets. Medical devices and IoT systems remain a major gap. Many devices stay in service for decades and cannot be patched.

Visibility is the first step. Leaders emphasized the need for accurate inventories, software bills of materials, and network segmentation. If an infusion pump attempts to communicate with Active Directory, the breach has already begun. Segmentation limits blast radius and traps attackers before they pivot deeper into the network.

Next Steps for Healthcare CIOs

For healthcare CIOs, the path forward is clear:

1. Redefine recovery. Invest in isolated recovery environments and test them.

2. Define your Minimum Viable Hospital. Agree on what truly matters before an attack forces the decision.

3. Strengthen identity controls. Move beyond basic MFA and secure privileged access.

4. Practice under pressure. Replace tabletop exercises with real downtime drills.

5. Close the device gap. Demand visibility and segment what cannot be patched.

6. Reframe the board conversation. Talk about days of downtime, patient risk, and revenue loss, not firewall features.

1) A real-world breach reminder: Central Maine Healthcare (~145,000 impacted)

Central Maine Healthcare reported a breach affecting more than 145,000 people—far higher than the number initially reported to the state. The reports indicate attackers accessed patients’ personal and insurance information (and in some accounts, treatment data as well). (Bangor Daily News)

You should treat this as more than another headline. Breaches don’t just create compliance work; they create operational drag and trust erosion that lands on every frontline touchpoint. Leaders reduce damage when they run security like clinical safety: rehearsed incident command, clear downtime workflows, and patient communications that don’t read like they were written by a committee of robots and attorneys who have never met a worried human.

2) Ambient documentation gets more embedded: Solventum + MEDITECH Expanse

Solventum announced its designation as an Accelerator partner in the MEDITECH Alliance, integrating Fluency Align into MEDITECH Expanse to support ambient AI documentation using conversational and generative AI. (solventum.com)

This matters because the market is shifting from “ambient AI pilots” to “workflow-native” deployments. When ambient tools live within the EHR flow rather than alongside it, adoption rises—but so do your governance obligations: quality controls, documentation integrity, coding implications, and data handling.

3) Prior authorization and interoperability timelines: CMS makes 2026 the “get serious” year

CMS’s Interoperability and Prior Authorization Final Rule (CMS-0057-F) sets near-term requirements starting January 1, 2026, with most API requirements primarily due by January 1, 2027. (Centers for Medicare & Medicaid Services)

Translation: 2026 is the year you either build the plumbing or you accept chaos later. If your payer/provider data exchange still relies on one-off interfaces, brittle workflows, and heroic staff workarounds, you will struggle under tighter expectations for electronic exchange and reporting.

4) Rural cybersecurity becomes a workforce strategy issue, not just a tooling issue

The American Hospital Association expressed support for the Rural Hospital Cybersecurity Enhancement Act (S. 2169), which would direct HHS to develop a comprehensive workforce strategy and establish partnerships to expand cybersecurity capabilities in rural hospitals. (American Hospital Association)

Even if you don’t operate rural facilities, you live in a regional care ecosystem. Rural cyber weakness can drive diversion, disrupt transfers, and stress tertiary capacity. Workforce limitations—not just budgets—often sit at the root: rural hospitals can’t hire or retain specialized security talent at market rates.

HHS has released an AI strategy outlining how the agency plans to use AI to improve efficiency, drive innovation, and strengthen national health outcomes. Healthcare CIOs share similar goals, and the HHS plan provides a practical model for scaling AI responsibly.

HHS organizes its strategy around five pillars:

• Strengthening governance and risk management to build public trust.

• Designing user-centered AI infrastructure and platforms.

• Equipping the HHS workforce with tools and training to ease administrative burdens and boost mission impact.

• Promoting rigorous research standards (”gold-standard science”) to ensure reliability and reproducibility of AI-driven work.

• Modernizing care and public-health delivery to improve outcomes at both individual and population levels.

For healthcare organizations, the number of competing AI models and frameworks from industry groups can make adoption harder. Looking at HHS’s approach, two themes stand out as especially practical for CIOs: trust-focused governance and unified infrastructure with workforce enablement.

Trust-Focused Governance

HHS proposes a department-wide governance model that includes a central board, a shared inventory of AI use cases, and clear oversight for systems that affect health outcomes or individual rights. The strategy references the NIST AI Risk Management Framework as a foundation for assessing risk and requires steps such as pre-deployment testing, impact assessments, independent review, and ongoing monitoring.

CIOs can’t treat AI as a routine software rollout. Healthcare organizations will need to demonstrate how they govern their AI systems, what risks they’ve assessed, and who is accountable for decisions that affect clinical or operational outcomes.

A practical governance approach can include:

• A clear council or oversight group

• Documented decisions for high-impact models

• Coordination across legal, compliance, and risk functions

The CIO’s goal is to create transparency without unnecessary complexity.

Unified Infrastructure And Workforce Enablement

As a healthcare CIO, you should treat AI as an enterprise platform, not a collection of pilots. Follow the HHS theme on building a reusable “value layer” of shared AI capabilities that every department can plug into. This theme includes designing reusable components, establishing standards for model evaluation, and ensuring data and workflow integration across clinical and administrative functions.

Healthcare leaders need to treat workforce enablement as a core requirement, not an afterthought. Staff need role-specific training that moves from basic literacy to applied skills, so AI tools reduce the administrative burden rather than adding new tasks. When teams know how to use AI confidently and appropriately, organizations can automate repeatable work, freeing clinicians to focus on patient care while maintaining compliance with HIPAA and other requirements.

Healthcare CIOs cannot afford to wait for the perfect AI framework. The market is full of recommendations, many so complex that they slow adoption rather than help it. CIOs need to focus less on debating models and more on operationalizing the tools they already have. Progress comes from starting, testing, adjusting, and building momentum vswaiting for certainty. The key is to get moving.

Athenahealth announced an expansion of its ambient-documentation capabilities through a new partnership with Microsoft. The company plans to offer Microsoft Dragon Copilot as an option within Ambient Notes, its documentation tool that works inside the athenaOne electronic health record (EHR). Athenahealth says the integration is expected to be available in the first half of 2026

According to the company, clinicians will be able to choose Dragon Copilot alongside other ambient-AI tools already supported in athenaOne. Athenahealth positions this as part of its strategy to give individual clinicians more control over how they document care, even within the same practice.

What This Means for Ambulatory Care

Most ambient-listening tools promote similar benefits, and the claims here follow the same pattern. Athenahealth highlights several potential advantages:

• Lower administrative load. Ambient Notes can generate draft clinical notes during a patient visit for clinicians to review.

• Clinician choice. Users can select the ambient model that fits their workflow rather than being limited to a single option.

• Scalability. The company reports more than 170,000 clinicians across nearly 50 specialties using Ambient Notes today.

These points reflect the broader market narrative around ambient documentation rather than the benefits unique to this partnership.

Strategic Considerations for Health-System Leaders

For executives evaluating EHR strategy, several issues may be relevant:

• Vendor differentiation. Offering multiple ambient-AI choices may influence perceptions of flexibility and usability.

• Clinician workload. Tools that reduce after-hours charting could support retention and help address burnout.

• Operational efficiency. Faster note creation may reduce bottlenecks tied to documentation.

• Compliance and oversight. Ambient tools still rely on clinician review, which may help organizations maintain accuracy and regulatory alignment.

My Point of View

Notably, Athenahealth is moving toward deeper integration with Microsoft’s ambient AI tools. Customers have asked for more options in this space, so expanding the set of supported tools meets an explicit request. Up to now, the connection between Athenahealth and Microsoft has been limited, so the key question is whether this new effort results in meaningful, in-workflow integration inside the EHR rather than a loose technical connection.

Conclusion

The planned addition of Microsoft Dragon Copilot to Ambient Notes signals continued movement toward AI-supported documentation across ambulatory care. For health-system leaders, the development underscores growing expectations for EHR platforms that reduce administrative burden and give clinicians greater control over how they document care. As organizations assess the role of ambient tools, the focus will likely remain on reliability, accuracy, and measurable impact on clinical workflow.

The traditional waiting room experience, which involves managing physical IDs, insurance cards, and redundant paperwork, is quickly becoming outdated. CLEAR, a secure identity company recognized for its airport fast lanes, is now introducing its security and verification technology to the healthcare industry. Recent announcements highlight a rapid shift toward secure digital identity as a foundation for next-generation healthcare IT.

CLEAR’s Progress: Advancing a Seamless Patient Journey

The core of CLEAR’s healthcare strategy revolves around its secure identity platform, CLEAR1, which provides a single, reusable digital identity for both patients and providers. Recent announcements show an expanding footprint across key areas of the industry:

1. Advancing National Interoperability with CMS

CLEAR is a key participant in the Centers for Medicare & Medicaid Services (CMS) Health Tech Ecosystem initiative. This national effort seeks to build a more connected and patient-centered health system by:

• Eliminating manual paperwork and redundant verification steps.

• Serving as a trusted, IAL2/AAL2-certified identity layer. This NIST certification provides a secure, compliant foundation for accessing and sharing sensitive health data.

2. Strategic Partnerships with Major Health Systems

CLEAR has inked high-impact partnerships with large health networks to improve patient experience and operational efficiency:

• Hackensack Meridian Health and Tampa General Hospital (TGH): These partnerships allow patients to use verified identities for streamlined appointment check-in, MyChart account creation, and password resets.

• TGH reported significant improvements, including automating 80% of account recovery requests and achieving a 99% faster resolution time for help desk calls.

• A recent partnership with digital health company Sharecare will integrate CLEAR1 into its AskMD platform, allowing users to securely verify identity for real-time insurance eligibility, benefit routing, and secure data access.

3. Deep Integration with EHR Leaders

To ensure broad accessibility, CLEAR is developing direct integrations with major electronic health record (EHR) systems and consulting partners:

• Epic Systems: CLEAR1 is being integrated into Epic’s workflows, including the MyChart platform for patient account management and the EpicCare Link Toolbox to support secure identity verification for community health providers.

• Nordic: A partnership with the global consulting firm Nordic will embed CLEAR1 into the digital transformation initiatives of its health system clients, supporting seamless identity management across IT, HR, and clinical workflows.

In summary, CLEAR’s digital identity layer is becoming a critical enabler for healthcare IT innovation, from AI-driven diagnostics to secure data sharing, supporting the transition to truly patient-centric care.

Google introduced Gemini 3, its newest AI platform, with new capabilities for deeper reasoning, antigravity agents, and native multimodality. For healthcare CIOs, these upgrades can help clear long-standing clinical and operational hurdles. The examples below show how Gemini 3 can support real work inside healthcare organizations.

Deep Think

Healthcare leaders can use Gemini 3’s deep thinking to solve complex decision-making problems that require multiple layers of analysis. They may first think of clinical reasoning for challenging patient care or research scenarios, but they should also apply this capability to operational improvements. One strong use case is managing complex patients, where deep thinking adds real value.

• Complex Patient Cohort - If your health system spans multiple locations with disparate EMRs and a non-standard third-party bolt-on application, Gemini 3 can support your assessments of complex patients across the organization. It ingests complete medical histories, imaging reports, lab results from multiple labs, and health information exchange data, pulling from every EMR involved. The agent analyzes this information for a complex patient cohort, reducing the time required for case management review. This analysis helps the health system quickly navigate scattered data so a case manager can define next steps, control patient care costs, and improve care quality.

Antigravity Agent

The power of the antigravity agent lies in its ability to execute workflows across different software applications. The agent can be powerful in areas of revenue cycle and patient access, especially in an environment with many third-party solutions. Here is a revenue cycle opportunity for healthcare CIOs to explore.

• Revenue Cycle Enhancement - Health systems deal with claim denials every day, and an antigravity agent can speed up the entire process. If a claim is denied due to improper coding or missing authorization, the agent logs in to the payer system, checks the denial code, and acts accordingly. In this case, if the claim is coded incorrectly, the agent logs in to the coding system, updates the code, and alerts the hospital coding staff to sign off. Once the code is fixed, the agent accesses the correct system to find the authorization, whether it’s in a document management tool or an email. It then resubmits the claim with the correct coding and authorization, completing the whole workflow without human intervention.

Multimodality

Gemini 3 offers native multimodality, enabling it to interpret and act on images, text, audio, video, and code simultaneously. As ambient solutions gain traction in healthcare, a Gemini 3 agent can analyze ambient scribe data, review eight months of medical history in the EMR, read the final radiology report in the RIS system, and process the telemedicine video consult with the patient.

It can then recommend next steps or even schedule the right specialist appointment by logging in to the scheduling system, all without help from the contact center or the physician’s office staff.

Gemini 3 shows how fast AI is moving in healthcare, and its impact will only grow as other competitors strengthen their platforms. Healthcare CIOs who act now can use these tools to raise care quality, streamline operations, and fix long-standing gaps.

An organization’s AI adoption strategy will define its competitive edge. CIOs must manage the fast rollout of AI from multiple vendors and understand how users leverage it to enhance experiences. The next step is designing agent-to-agent (A2A) interactions—automating and connecting multiple AI agents—a trend reflected in recent major tech company announcements.

Below are key announcements and how healthcare CIOs should evaluate their strategy.

Google

Google Cloud has launched Gemini Enterprise. Google positions this platform as one that unifies all AI capabilities and makes it easier to create AI agents. The Gemini enterprise platform offers AI agent creation via a “no code” workbench, formerly called Agentspace, that supports users in developing AI agents without coding skills. The platform also includes pre-built Google AI agents and connectivity to various third-party applications.

Amazon

Amazon’s Bedrock AgentCore serves as an enterprise platform focused on foundational operations and security.AgentCore is designed to provide the essential infrastructure for securely running and managing production AI agents at scale.

The key components of the platform are:

• AgentCore Identity enables agents to act on behalf of users across multiple systems.

• AgentCore Runtime is a serverless, low-latency environment.

• AgentCore Gateway provides secure API access for agents.

Salesforce

Salesforce announced Agentforce 360, which includes:

• Agentforce Builder is a low-code/no-code environment that enables the building and testing of agents within a single interface.

• Agent Script is a scripting language designed to prompt the AI agent’s behavior, enabling more effective responses to if/then scenarios.

• Agentforce Voice delivers conversational voice agents tailored to a brand and integrates with contact-center platforms.

CIO’s Point Of View

Healthcare CIOs seek a platform that enables them to manage all AI agent capabilities. One way to design an agent-to-agent (A2A) interaction is to automate hospital functions, such as the contact center, physician workflows, and patient insurance eligibility checks. This A2A workflow determines patient eligibility, schedules appointments based on patient convenience, and generates a summary of relevant information for physicians before the visit.

A2A automation begins with Amazon AgentCore’s infrastructure, which powers complex automation by securely connecting to various data sources and triggering API actions. The Salesforce agent integrates with the contact center, interacts with the patient, collects demographic and insurance data, and determines eligibility for service. After verifying eligibility, the Salesforce agent schedules the appointment and contacts the Google Gemini agent, which makes an API call to the EHR system and compiles a summary of the patient’s medical history and past appointments for the physician.

This scenario shows how AI agents and platform integrations can streamline complex tasks.

Every AI platform competes to be the central coordinator for driving A2A automation across systems. CIOs demand secure, flexible platforms that integrate seamlessly. Whether A2A agents will replace humans in routine tasks and enable them to focus on higher-value work remains uncertain.

Healthcare is shifting faster than any leadership team planned for. Costs continue to rise, regulations become tighter, and consumers expect a stronger voice in their care. AI and automation are already reshaping clinical and operational decisions. The traditional operating model can no longer keep up, and leaders now need sharper skills, clearer instincts, and stronger partnerships to guide their organizations through the next decade.

HFMA’s latest research shows many C-suite leaders do not feel ready for the pressures ahead. Below are the key themes from the study.

AI Fluency Becomes a Core DNA

AI is no longer an emerging concept; it has become a mainstream technology. It influences diagnosis, treatment, and every major administrative workflow. Leaders must understand how the technology works, where it generates measurable value, and where hype can lead organizations astray. Moving too quickly exposes the enterprise to risk, but inaction carries its own consequences.

We cannot confine AI knowledge to a select few, as AI fluency must span the entire leadership team and extend through the director ranks. The executives who excel will know how to govern the technology, build trust in its use, and invest in the right opportunities with discipline and pace.

Enterprise Value Is A Team Sport

Healthcare CFOs used to focus on stewardship and capital decisions. That job has grown. Enterprise value now depends on tight alignment between finance, operations, clinical leadership, and technology. That shift is already changing how all of the C-suites function.

Leaders are digging deeper into clinical outcomes, consumer experience, and the total cost of care. They are redesigning workflows to align with new technologies and collaborating across departments to develop stronger risk-based arrangements and value-based care strategies. None of this happens in isolation. It takes collective ownership.

Three Priorities Stand Out

According to the HFMA findings and executive interviews, three priorities emerge.

1. AI and automation. Leaders see a significant opportunity to reduce administrative waste, improve decision support, and ease workforce pressure. But AI only works when the foundation is clean, reliable data, and a disciplined governance structure. There will be a lot of cleanup before an organization can effectively utilize AI. Let’s not take any shortcuts in this exercise.

2. Ambulatory and home-based care. Outpatient and home-based services are projected to grow faster than any other care setting through 2034. Building the right mix of services and staffing them well will be key to both financial performance and consumer expectations.

3. Payer-provider relations. Payers’ relationships are tricky. Leaders who understand contract mechanics, risk attribution, and clinical redesign position themselves to achieve lower costs and improved outcomes.

New Roles Signal a New Operating Model

As the scope of leadership expands, so do the titles that accompany it. Chief AI innovation officer, Chief digital officer, Chief medical innovation officer. Even the chief observability officer. These roles signal a broader truth. The future C-suite will be built around data, insight, experience, and accountable execution. However, leaders must strike a balance between expansion and clarity. Too many roles create confusion. The proper roles create alignment. A strong CIO who can influence and bring leaders together is well-positioned for the new role.

Execution Is the Currency of the Future

Vision matters, but execution will decide who leads the next era. Leaders must connect data to daily action, set clear expectations, and build cultures where results are visible. Teams perform best when accountability is shared, communication is transparent, and incentives point in the same direction.

Strong relationships inside the C-suite are crucial. Many CFOs now operate as strategic partners to CHROs, CMOs, chief physician executives, and other key leaders. Finance is no longer the back room. It is the backbone of decision-making across the enterprise.

A Future Built on Clarity and Confidence

Healthcare is full of uncertainty, but leadership cannot be. Executives must know when to take calculated risks and when to make strategic pivots. They must understand the macroeconomic environment and resist the urge to operate within an internal bubble. Above all, they must stay curious, challenge assumptions, and move forward with confidence toward what is next.

The C-suite of the future will not succeed on title or tenure. It will thrive on adaptability, collaboration, data fluency, and disciplined execution. The leaders who rise to that standard will guide healthcare through its most significant transformation in decades, into a model that works for patients, teams, and systems alike.

Artificial intelligence is making significant progress in healthcare operations, as recent announcements this past week highlight the field’s growing momentum. The focus remains on reducing clinicians’ administrative workloads and delivering faster, more coordinated care to patients.

Viz.ai Launches Viz Assist to Power Real-Time Care Coordination

Viz.ai has launched Viz Assist, an AI platform designed to streamline communication and data delivery for care teams. Acting as an AI agent, Viz Assist instantly gathers and delivers patient data to clinicians, enabling faster and more informed decision-making.

According to the company, this multimodal platform will address information gaps that often delay treatment, particularly in critical areas such as stroke and cardiovascular care. By consolidating fragmented clinical data into a single, actionable view, Viz Assist seeks to reduce delays, enhance coordination, and improve patient outcomes.

This development builds on Viz.ai’s leadership in AI-powered care coordination, expanding its capabilities from imaging and triage to operational efficiency and workflow automation. Turning to another significant advancement in healthcare AI:

Heidi Health Raises $65M to Scale Its AI Care Partner.

Heidi Health has announced a $65 million Series B funding round to expand its AI care partner platform globally. This brings the company’s total funding to approximately $100 million, reflecting strong investor confidence in its mission to automate time-consuming healthcare tasks.

Heidi’s AI platform automates administrative tasks such as clinical documentation, chart summarization, and care coordination support. By handling these repetitive activities, Heidi enables clinicians to spend more time with patients. The company states that the funding will support international expansion and further refinement of its AI models to better assist healthcare teams in various clinical settings.

Big Picture: AI Investment in Healthcare Operations Is Accelerating

Both announcements underscore a trend reshaping healthcare IT. AI is evolving beyond diagnosis to orchestrate the delivery of care. From Viz.ai’s workflow intelligence to Heidi’s administrative automation, these tools now manage both complex care logistics and clinical data.

This momentum reflects a surge in digital health investment. For example, states such as Ohio report rapid growth in data centers and digital health infrastructure, according to a recent Ohio Tech News report. This expansion demonstrates that AI-driven health systems are becoming essential to regional economies as well as hospitals.

The Takeaway

AI for care coordination and healthcare operations is advancing from pilot projects to full-scale deployment. The benefits are now tangible: Viz.ai enhances real-time clinical collaboration, while Heidi Health expands intelligent documentation globally, offering the healthcare workforce essential operational support.

As investment grows and adoption accelerates, healthcare teams are actively integrating AI to deliver faster, smarter, and more connected care.

1. American Medical Association (AMA) Launches Center for Digital Health & AI

The AMA announced that it has launched its new Center for Digital Health and AI to embed physicians throughout the lifecycle of technology development and deployment — from policy and workflows to education and partnerships. According to the press release, the Center will work on:

• Policy and regulatory leadership (shaping benchmarks for safe and effective use of AI in medicine).

• Clinical workflow integration (making sure digital health/AI tools actually fit into the daily work of physicians).

• Education & training (equipping physicians and health systems with the know-how to integrate AI)

• Collaboration (building partnerships across tech, research, government, and healthcare)

The AMA further notes that physician enthusiasm for AI is growing (about two-thirds of physicians report using some AI tools), but concerns remain about data privacy, reliability, workflow fit, and liability.

My commentary

This is a smart move by the AMA. But will they help organizations actually operationalize AI? Launching a Center and issuing guidance are steps in the right direction. However, the bigger challenges include tailoring tools to specialties, integrating into EHRs, ensuring adoption, addressing bias, and protecting data privacy and quality. The AMA’s value depends on translating ambitions into operational steps, such as vendor selection, governance, and implementation playbooks.

CIOs want any center of excellence to deliver:

• Clear frameworks for selecting/certifying AI tools.

• Case studies with workflow redesign examples (here’s how cardiology integrated decision-support; here’s how primary care introduced ambient scribes).

• Vendor-agnostic toolkits for implementation (including training, governance, and monitoring).

• Roles/responsibilities for physicians + IT + data science + operations.

• Metrics to measure ROI and safety (both operational and clinical).

If the Center implements clear operational programs, its impact on health systems will be significant. However, if efforts remain confined to policy and education, the value to executives and their organizations will be limited.

2. Hyro Raises $45 M Strategic Growth Round to Accelerate AI Agent Adoption in Healthcare

Hyro, a healthcare-native conversational AI/agent platform, announced a $45 million growth round (led by Healthier Capital, with Norwest, Define Ventures, ServiceNow Ventures, Bon Secours Mercy Health), bringing its total funding to about $95 million. The funds will accelerate development of administrative, operational, and clinical AI agents designed for healthcare workflows — e.g., chat/voice, scheduling, prescription management, patient routing. Hyro claims its platform already serves more than 45 health systems and more than 30 million patients across the U.S.

My commentary

Yes — the so-called “digital front door” strategy lives on. The idea of improving patient access via digital/voice channels, automating routine interactions, reducing phone wait times, and freeing staff touches continues to attract investor capital. Hyro’s raise shows that investors still believe that tools which differentiate patient access (especially those backed by AI) can deliver value.

Bottom line: This capital raise is a strong signal that the market still values digital front-door capabilities as a differentiator for health systems.

3. Shifting focus to organizational strategy, there’s also notable movement in system affiliations:

MultiCare and Samaritan approved an affiliation aimed at strengthening community-based care across the Pacific Northwest. The affiliation will bring together Samaritan (Oregon-based, community-focused) and MultiCare (Washington-based system) to invest in access, technology, and services, while retaining local governance and community roots. The anticipated timeline: signing definitive agreement, regulatory review, integration planning, and full operations in mid-2026.

My commentary

Healthcare continues to consolidate. Larger systems want scale, broader geographies, more diversified revenue streams, and greater bargaining power. The MultiCare-Samaritan affiliation is a textbook example: a community-based system aligning with a larger peer to sharpen capabilities while maintaining local governance.

The event, themed “Heroes & Legends,” is drawing 12,000+ leaders to discuss AI’s ROI, prevention strategies, women’s health, metabolic innovations, rare diseases, and oncology breakthroughs. Artificial intelligence dominates every aisle at HLTH 2025. The AI pavilion has doubled in size since last year, and every conversation centers on outcomes, not algorithms.

Mark Frank, CEO of SonderMind, captured the sentiment perfectly: “The hot topic is without question the role AI has played, and will continue to play, in mental health care… everything in the AI and mental-health space must be built with the utmost care given oversight, clinical rigor and privacy.” (Fierce Healthcare)

That emphasis on ethical deployment and measurable outcomes marks a maturation moment for health AI. Innovaccer’s launch of Galaxy, an AI-driven payer platform, and TytoCare’s new Smart Clinic Companion demonstrate how vendors are evolving from “data aggregation” to “actionable automation.” (STAT News)

The Capital Climate: Selective but Strategic

Funding headlines reflect cautious optimism. According to STAT News, Oura raised a massive $900 million round at an $11 billion valuation. At the same time, Town Hall Ventures — co-founded by Andy Slavitt — closed a $440 million fund focused on AI-driven health equity startups.

Other deals, like MD Integrations ($77 million), Brook.ai ($28 million), and Medmo ($15 million), highlight that capital is available but disciplined. Investors are shifting away from mid-stage bets toward proven operators. Growth funding now favors companies with credible data, compliance readiness, and sustainable unit economics.

For health-system leaders, that means vendor selection should hinge less on product novelty and more on financial and operational durability.

Care Models and the “Next Normal”

Executives at HLTH 2025 are re-centering the conversation on care delivery. Ami Parekh, Chief Health Officer at Included Health, summarized this shift: “I’m genuinely excited that we’re at a point where we can realize the outcomes from Advanced Primary Care… all of these pieces are starting to come together now.” (Fierce Healthcare)

This alignment of AI, advanced primary care, and behavioral health integration signals a post-pandemic evolution — from reactive digital health to proactive population management. “Food-as-medicine,” home-based diagnostics, and remote mental-health programs are now being discussed as mainstream strategies, not pilots.

What People Are Saying

Attendees and speakers are live-tweeting the energy, from raw critiques to inspiring stories. The vibe? Optimistic disruption amid healthcare’s “broken” realities. Here’s the chatter from X (latest posts as of today):

• Mark Cuban’s Blunt Keynote Fire: Opening the event, Cuban didn’t hold back: “Healthcare is f@@ked up—we need net pricing, not list prices, for true accessibility.” Attendees are raving about his no-BS call for transparency and Cost Plus Drugs to slash costs. One user summed it: “Powerful, direct—healthcare should be for all Americans.”

• Patient Stories Stealing the Spotlight: Emotional shares are trending, like Alicia Dellario’s journey through six lines of ovarian cancer treatment (including trials) and women revealing 20–48 years of misdiagnoses. Rob Lowe opened up on early detection and trials, noting only 7% of cancer patients join them: “That’s wild—we need change.” BBC Studios is collecting more stories on-site.

• Innovation and Networking Highs: Excitement over “magical mascots” and trailblazers unpacking AI adoption: “Human + AI workforce magic is here—adoption meets execution.” Sponsors like HelixVM are hyped for “reimagining what’s possible.” One fun snapshot: “America in one photo” of the chaotic, vibrant expo floor.

• GLP-1 Buzz and Beyond: Sessions on GLP-1s (e.g., from WeightWatchers’ Dr. Kim Boyd) are calling them “transformative—one of the most impactful treatments in 30 years,” with talks of life-extension apps.

Overall, HLTH 2025 has generated significant buzz within the healthcare vendor community; it will be interesting to see the balance between vendors and decision makers.

A major HealthTech vendor announces record quarterly earnings, a new AI-driven product, or a strategic partnership. The stock jumps, the headlines celebrate, and generalized market commentary quickly follows. However, for Private Equity funds and corporate strategy teams competing in this space, the official press release serves merely as a cover page.

The true competitive advantage—the granular insight that moves the needle—is buried in the operational reality of the vendor’s customers, competitors, and former executives. This is where the specialized expert network call becomes non-negotiable.

While public transcripts provide “what” a company said, our specialized experts tell you “why it matters,” “how it works in the field,” and, most importantly, “what the competitors are doing about it.”

The Three Competitive Blind Spots Solved by Specialized Expert Calls

Generalist expert networks can provide broad sentiment, but they lack the operational context to distinguish between marketing hype and genuine competitive disruption. Our specialized approach focuses on three critical areas that public data cannot quantify:

1. Market Penetration vs. Usage Depth (The “Sticky Factor”)

A vendor might report a 30% increase in new client bookings, which sounds excellent. But how much are those clients actually using the expensive new feature set?

• The Expert Question: “As a former RCM administrator at a hospital that recently adopted Vendor X’s new AI coding module, what percentage of coders are actively utilizing the module versus reverting to the previous workflow, and what are the friction points?”

• The Insight: Our experts—the Chief Clinical Informatics Officers or Revenue Cycle leaders—quantify the “shelfware risk.” They reveal if the new product is truly integrated into critical workflows (high competitive advantage) or if it’s sitting unused due to poor integration, alert fatigue, or lack of staff training (low competitive advantage, despite high sales).

2. The Competitive Response (The “Moat Erosion”)

When a dominant EHR or RCM platform announces a significant enhancement (e.g., seamless Generative AI integration), the true impact depends on the speed and efficacy of the competitor response.

• The Expert Question: “Following Epic’s recent LLM announcement, what specific, actionable product improvements are prioritized in the development sprint at Vendor Y (a direct competitor), and what is their projected time-to-market for a comparable feature?”

• The Insight: We connect you with former product managers and engineering leaders who have direct visibility into competitor roadmaps and budgets. They can forecast which competitor will successfully narrow the gap, and which will fall hopelessly behind, allowing you to adjust your portfolio strategy quickly.

3. Pricing Power & ROI Validation (The “Cost-of-Switching”)

The vendor claims their new product is accretive to customer bottom lines. The expert’s job is to validate this claim by assessing the real-world Total Cost of Ownership (TCO) and the effort required to rip and replace a legacy system.

• The Expert Question: “Based on your experience managing large-scale procurement for a multi-state payer system, how has Vendor Z’s recent pricing adjustment for their utilization management tool been received by other peers, and what is the internal debate around the cost-benefit analysis of switching to a lower-cost, high-interoperability alternative?”

• The Insight: Operational experts reveal the hidden costs—data migration, clinician training, and interoperability fees—that turn an impressive ROI projection into an operational nightmare. This insight is crucial for forecasting future customer churn and truly valuing the vendor’s competitive moat.

Actionable Next Steps: Accelerate Your CI Cycle

Stop waiting for industry analysts to catch up. When a public announcement drops, your analysis needs to be hours, not weeks, ahead of the market. Our Contextualized Expert Network offers instant access to precise, operational voices that can validate or debunk the latest HealthTech claims.

Need a Verdict on a Competitor’s New Product?

Contact us within 48 hours of any major earnings report or product launch to schedule a targeted consultation with an expert who knows the exact operational impact.

Here’s your final, fully cited version — edited for clarity, precision, and with inline source links you can publish directly to a healthcare executive. As of October 16, 2025, the U.S. federal government remains in a partial shutdown that began on October 1 after Congress failed to pass a continuing resolution before the September 30 deadline. The standoff stems from partisan disputes over nonessential spending demands (Forvis Mazars).

The shutdown has ended or suspended several temporary health policies extended from the COVID-19 era. While Medicare and Medicaid payments continue as mandatory spending, programs such as telehealth flexibilities and hospital-at-home (HaH) have been directly affected. Hospitals and providers are scaling back or pausing services to avoid unreimbursed care (NBC News).

The Shutdown: No End in Sight

Congress remains gridlocked. Senate and House leaders from both parties continue to trade blame instead of advancing a funding bill (NBC News).

Essential healthcare functions—such as Medicare claims processing—continue, but nonessential work like rule-making, program renewals, and oversight remains delayed or suspended (Foley Hoag LLP). The lapse includes waivers that had expanded access to remote care.

Telehealth Programs Roll Back

Medicare telehealth flexibilities expired on October 1, 2025, after temporary extensions through September ended without renewal. These policies had expanded access beyond rural areas and permitted home-based visits without geographic restrictions (American Telemedicine Association).

Without them, Medicare reverts to pre-pandemic rules:

• Patients must live in rural areas.

• Visits must take place at approved facilities (e.g., hospitals or clinics) (AAPA.org).

Providers who continue virtual visits outside those parameters risk losing reimbursement. Many have already canceled or converted telehealth appointments to in-person visits to avoid nonpayment (Health Journalism).

Patients are receiving notices that out-of-pocket costs could range from $221–$484 per visit without Medicare coverage (Stateline). Over 4 million Medicare beneficiaries used telehealth in the first half of 2025, making the rollback especially disruptive for older adults, rural residents, and patients with limited mobility (Stateline).

Federally Qualified Health Centers (FQHCs) and Rural Health Clinics also face reimbursement losses because they can no longer bill for many remote services (Telehealth Resource Center).

Advocacy groups such as the American Telemedicine Association continue to push for temporary extensions, but congressional gridlock has blocked progress. Some providers are switching to direct-pay or insurance-independent models to maintain patient access (MyRxAccessPlus).

Hospital-at-Home Programs on Hold

Hospitals across several states, including New Jersey, have paused or scaled down hospital-at-home (HaH) programs after the expiration of CMS waivers on October 1, 2025 (Telehealth Resource Center). These programs have allowed hospitals to deliver acute-level care at home, reducing inpatient stays and improving patient outcomes.

The shutdown rendered these programs “collateral damage,” as many systems were unable to sustain operations without Medicare reimbursement. As of late 2024, 366 hospitals had participated in the HaH program, serving more than 31,000 patients, according to federal data (Stateline).

The impact is most significant for older and rural patients who rely on home-based recovery to avoid hospitalization. Lawmakers from both parties have expressed support for reinstating the waivers, but no legislative fix is in motion (STAT News).

Broader Fallout Across Healthcare

The shutdown compounds several other financial and operational challenges:

• Medicaid DSH Cuts: An $8 billion reduction in disproportionate share hospital payments took effect October 1, straining safety-net hospitals (Forvis Mazars).

• Medicare Low-Volume Adjustments: Tighter eligibility rules may cut payments to small rural hospitals (Forvis Mazars).

• Rule-Making Delays: A prolonged shutdown could delay 2026 CMS payment updates and threaten funding for community health centers (NBC News).

• End-of-Life Care: Access to hospice and palliative telehealth services has narrowed, reducing flexibility for patients and families (Compassion & Choices).

The longer the shutdown lasts, the deeper these disruptions will reach. Advocacy organizations are urging Congress to retroactively extend telehealth and HaH provisions once funding resumes (CMS.gov).

Bottom Line:

Healthcare executives should anticipate continued disruption in telehealth and hospital-at-home operations. Monitor CMS updates, review exposure to reimbursement risks, and prepare for operational adjustments until Congress restores funding and regulatory authority.