When Congress enacted the No Surprises Act (NSA), the primary objective was straightforward: protect patients from unexpected out-of-network medical bills. Since implementation in 2022, however, the law has created a complex framework for resolving payment disputes between providers and payors through the Federal Independent Dispute Resolution (IDR) process.

What began as a well-intentioned arbitration mechanism has evolved into a system burdened by millions of disputes, operational inefficiencies, administrative complexity, and mounting costs. Recognizing these challenges, the Departments of Health and Human Services, Labor, Treasury, and the Office of Personnel Management recently finalized significant reforms to the Federal IDR process. While much of the discussion surrounding these changes has focused on hospitals and physician organizations, laboratories and diagnostic providers should pay close attention. Several provisions in the final rule could materially impact dispute management workflows, reimbursement strategies, and administrative costs.

A System Under Pressure

Since the Federal IDR process launched in April 2022, more than five million disputes have been submitted, far exceeding original government projections. The volume has created substantial backlogs, increased costs for participating organizations, and generated frustration among both providers and payors.

For laboratories, pathology groups, and other diagnostic providers that occasionally find themselves involved in out-of-network reimbursement disputes, the administrative burden associated with pursuing IDR has often outweighed the potential financial recovery. As a result, many organizations have simply absorbed underpayments rather than invest the resources necessary to challenge them.

The latest reforms are intended to address these challenges by improving efficiency, increasing transparency, and lowering barriers to participation.

Lower Costs May Encourage More Dispute Participation

One of the most notable changes is the reduction of the Federal IDR administrative fee from $115 to $15 per party, per dispute.

While this may appear modest, the reduction could significantly alter the financial equation for providers evaluating whether to pursue arbitration. For laboratories operating on increasingly narrow margins, particularly those performing specialized diagnostic testing, lowering the cost of entry may make it more practical to challenge inappropriate reimbursement determinations.

Organizations that previously dismissed smaller disputes as economically unfeasible may now find it worthwhile to pursue recovery through the Federal IDR process.

Expanded Batching Could Be a Game Changer for Laboratories

Perhaps the most impactful provision for diagnostic providers is the expansion of batching flexibility.

Historically, restrictive batching requirements forced providers to submit multiple disputes even when claims involved similar services. This increased administrative effort, delayed resolution timelines, and elevated costs.

The final rule now permits qualified items and services to be batched under broader criteria, including pathology and laboratory services that fall within the same Category I CPT code section. In addition, up to 50-line items may be included within a single batched dispute.

For laboratories managing multiple related claims, this change could substantially reduce the administrative burden associated with dispute preparation, submission, and tracking. Instead of treating each service line as a separate arbitration event, organizations may be able to consolidate disputes into a more efficient and cost-effective process.

This is particularly important as diagnostic testing continues to become more complex and specialized, often involving multiple services associated with a single patient encounter.

Greater Transparency Between Providers and Payors

Another persistent challenge within the No Surprises Act framework has been inconsistent communication regarding payment determinations.

Providers frequently receive remittance information that lacks sufficient detail to determine whether a claim qualifies for IDR or to understand the rationale behind a reimbursement decision.

The final rule addresses this issue by requiring health plans and issuers to provide standardized Claim Adjustment Reason Codes (CARCs) and Remittance Advice Remark Codes (RARCs) when communicating payment decisions.

This additional transparency may help laboratories more quickly identify potentially disputable claims, understand denial rationales, and determine whether arbitration is an appropriate next step.

For revenue cycle teams, these requirements may also support greater automation opportunities by allowing organizations to systematically identify claims eligible for escalation.

Operational Readiness Will Matter

The reforms also introduce new procedural requirements surrounding open negotiation activities, including mandatory portal-based submissions and response timelines.

Organizations that rely on manual workflows may find compliance with these requirements increasingly difficult as dispute volumes grow. Success will depend on having the operational infrastructure necessary to identify eligible claims, manage negotiation deadlines, track dispute status, and maintain supporting documentation.

As regulatory requirements become more prescriptive, reimbursement teams will need greater visibility into denial trends, reimbursement patterns, and dispute outcomes.

This is where advanced analytics and workflow automation become increasingly important. Organizations that can quickly identify underpayments, track negotiation activity, and prioritize high-value disputes will be better positioned to maximize recovery while minimizing administrative burden.

Looking Ahead

The latest Federal IDR reforms represent an acknowledgment by regulators that the original process required modernization. By reducing fees, expanding batching opportunities, improving transparency, and introducing a centralized IDR Gateway platform, federal agencies are attempting to create a more efficient and scalable dispute resolution framework.

For laboratories and diagnostic providers, these changes present both opportunities and responsibilities. Organizations that proactively evaluate their dispute management strategies, strengthen reimbursement analytics, and prepare for evolving operational requirements will be best positioned to benefit from the reforms.

The No Surprises Act remains a dynamic and evolving regulatory landscape. While these changes are unlikely to eliminate payment disputes altogether, they may provide laboratories with more practical and cost-effective tools to address them when they occur.

About Clarisa Blattner, CCS, CPC

Clarisa Blattner is the Senior Director of Revenue and Payor Optimization at XiFin, Inc. She serves as a subject matter expert in revenue cycle management (RCM) and payor and market strategies, focusing on achieving operational efficiencies and maximizing revenue. With over 25 years of experience in the healthcare sector, Clarisa has an extensive background in revenue cycle management, particularly within the healthcare industry. Previously, she oversaw the billing and reimbursement operations for the outsourced billing department

What You Should Know

• Digital health orchestration leader Xealth has announced the strategic appointment of Travis Moore as Chief Revenue Officer (CRO).
• Moore brings over 25 years of healthcare industry experience, transitioning from an initial clinical career as a pediatric nurse to senior commercial leadership roles across major health tech and AI-powered behavioral health platforms.
• In his previous role as SVP of Sales & Growth at Kyruus, Moore successfully scaled start-up commercial operations to reach more than 300 large provider customers across major Epic and Oracle Health EHR networks.
• Xealth provides a centralized care orchestration platform that embeds digital therapeutics, remote patient monitoring (RPM), and education directly into the native clinician EHR chart.
• Backed by Samsung Health, Moore will lead Xealth’s commercial organization to scale its deployment footprint, which currently spans more than 500 hospitals and over 70 digital solution partners.

Bridging Clinical Reality with Enterprise Go-To-Market Scale

Moore’s professional background combines hands-on medical delivery with enterprise-grade technology sales. He began his healthcare journey directly in high-velocity clinical settings as a pediatric nurse, gaining an immediate understanding of the administrative and workflow burdens that frontline care teams experience daily. Shifting into health technology leadership, Moore built a 25-year track record navigating complex product management, marketing, and cross-functional revenue pipelines.

As the Senior Vice President of Sales & Growth at Kyruus, he engineered the startup commercial framework that expanded to serve over 300 major provider customers across dominant Epic and Oracle Health EHR platforms. Most recently, Moore spearheaded the commercial strategy for an AI-powered behavioral health platform, where he successfully managed rapid multi-market revenue growth, structured team execution, and customer retention.

“Travis brings a powerful combination of clinical experience and go-to-market expertise to Xealth – and he’s exactly the right person to help us expand our impact,” stated Mike McSherry, Chief Executive Officer of Xealth. “As Xealth and Samsung continue to advance a vision of AI-connected care, he is well positioned to help us leverage our deep expertise and extensive healthcare network to drive this transformation forward.”

Moore echoed this strategic focus, emphasizing that modern health systems face intense pressure to simplify digital health deployment, streamline platform management, and build deeper connections into the overall patient experience. Xealth is built to serve as the critical infrastructure link for digital health growth. Backed by the broader enterprise vision of Samsung Health, the company is positioned to help healthcare commercial teams confidently scale that impact.

Right at this moment, a physician is logging out of a new digital health tool for the very last time. Not because it stopped working. But it started feeling like a chore rather than a savior. The tool never worked right to keep up with the fast pace of her daily workflow.   

She will eventually return to her old school ways. A sticky note, a quick phone call, and an old spreadsheet that keeps the staff on life support. That six-figure platform her health system just built? It will be nothing more than deadweight, destined to join the pile of unfortunate innovations that did not really do much.

This is happening everywhere. According to research published in JMIR, 53% of digital health apps get uninstalled within 30 days. On the enterprise side, the numbers are worse. Up to 80% of digital health solutions never make it past the pilot stage. Nine out of ten never reach a meaningful scale.

That handwritten note wins every single time. It is not about technology — it is about being right there, requiring no login, and meeting the physician’s needs in under three seconds. When an expensive tool starts losing to a handwritten note, the problem is not the note.

This is not a failure of technology. It’s the failure of understanding who’s actually going to use the final product.

The Workflow Problem Nobody Wants to Talk About

I’ve seen this over and over again. A startup builds something impressive for hospitals and physicians, with a polished demo and a clean, compelling pitch deck. The AI does exactly what it’s supposed to do in a controlled environment. 

The real problem starts when it is implemented in a real clinic.

The nurse has to open a separate browser tab to use it. The data doesn’t flow back into the EHR without manual re-entry. The physician gets three new alerts per patient that she doesn’t have time to evaluate. Studies show clinicians already override 89 to 96% of drug interaction alerts because the signal-to-noise ratio has become absurd. Only about 7% of clinical alerts are deemed appropriate in some settings.

The alert problem is worth shedding light on as it explains the core reasons behind the failure of a health tech tool. 

Every alert was developed under the impression that it would help the physician. The intention was on point, but the implementation failed to understand the workload of a physician’s day. A physician who already has to forcefully override most of the alerts does not need more fluff. 

Instead, they would rather have a system that goes through the unnecessary fluff and shows only what is critical. It becomes obvious that the person who developed the tool never really saw a physician working a 12-hour shift.

The biggest mistake easily visible in healthcare app development is designing for the needs of the buyer rather than the user. The VP who will sign the contract does not have to go through the daily struggles of a physician, like going through an endless stream of notifications daily. When that gap shows up, and it almost always does, the tool starts dying slowly. The staff goes back to their old, reliable habits that get the job done with the least hassle.

Pilots That Were Never Meant to Scale

In the world of IT, there is an annoying pattern that no one wants to say out loud. A lot of pilot programs are just theatrics for stakeholders and investors.

The organization wants to show its board or its CEO that innovation is happening. But there’s no budget for a rollout. No staff allocated to own it past the pilot phase. No integration roadmap. The person who championed the pilot has a full-time clinical role and can’t also manage an enterprise deployment.

And the pilot itself is a lie, structurally. It runs in a controlled setting with hand-picked users and extra support. The moment it hits a real unit with real patient volumes and real EHR chaos, it falls apart. 

This comes as no surprise, and the pattern is predictable. Despite repeated failures, the industry continues to run these pilots through the same flawed process as if it will produce a different result.

What Actually Survives

The health tools that really work are the ones that stop feeling like tools and become invisible. 

They don’t really disappear, but integrate so well into the existing routine that you forget you are even using one. There is no extra fluff, no extra steps, no jumping through hoops. The technology works behind the scenes in the clinician’s native environment, easing their day.

Ambient documentation tools are a good example. They sit in the background during a patient encounter, generate the clinical note, and push it into the EHR. The physician doesn’t interact with the tool directly. She just gets her evening back. That’s why ambient AI is one of the few categories seeing sustained enterprise adoption rather than pilot-and-die cycles.

The pattern holds across use cases. Smart scheduling that reduces no-shows by integrating with the existing patient communication workflow. Denial prevention tools that flag coding issues before the claim leaves the building, not after it gets rejected. These aren’t flashy. You’d never raise a Series A off a demo. But they survive because they remove work instead of adding it.

The Question That Should Come First

When I talk to people building healthcare applications, the first question I ask is: What step are you removing to make the physician’s day smoother? Not which new steps are you adding or innovations you plan to introduce. But what existing burden are you eliminating?

If someone cannot explain it in under ten seconds, then that product will probably fail, as it is not made for a clinical environment. Clinicians are not looking for new tools; they are looking for you to get rid of the extra burden. They are already drowning in the massive sea of logins, too many tabs, and a lot of systems that were supposed to ease things up, but instead ended up being more complicated.

The industry spends trillions on healthcare every year. Two decades of health IT investment haven’t bent the cost curve. And apps keep piling up in the graveyard because builders keep solving for the demo instead of the day.

The real solution is not new or better technology. You need to be in the clinic to understand the clinician’s daily workflow, to study the real on-goings, and track the number of clicks. Then develop something that actually reduces this burden.

That’s what product providers will actually keep using.

About Hitesh Agarwal
Hitesh Agarwal is the Founder and CEO of Tech Exactly, a software development company that builds compliant, interoperable, and scalable healthtech products and AI systems. With over a decade of experience delivering digital health solutions, he works closely with healthcare organizations navigating EHR integration, FHIR adoption, and regulatory compliance.

Clinical trials have grown more complex than ever before. Protocols are becoming more specialized, endpoints more refined, and eligibility criteria narrower and more precise. At the same time, development programs are expected to move faster and operate with greater efficiency. Despite this dual pressure, feasibility projections often rely on high-level estimates or investigator recall rather than validated assessments of patients who truly meet protocol criteria in a real-world clinical setting. 

When projected patient populations fail to emerge or sites underperform, the consequences extend beyond delayed timelines. Protocol amendments, operational strain, stressed site relationships, and escalating costs follow. As protocol complexity increases, the risk of designing studies without a clear understanding of real-world care patterns becomes harder to ignore.

Real-world data (RWD) offers a meaningful opportunity to close this gap, but only when it is integrated thoughtfully and early in the development process.

Moving from Retrospective Insight to Proactive Design

For years, RWD has played an important role in post-marketing research and evidence generation. Increasingly, its greatest impact is realized earlier in development, where it can inform protocol design, feasibility planning, and evidence strategy before studies begin.

Real-world analyses are often introduced once new signals emerge during study execution, whether related to enrollment velocity, shifting standard of care, unexpected interim trends, competitive trial dynamics or the need for contextual evidence. At that point, the ability to influence study design is limited, and adjustments become tactical rather than strategic. A more effective approach is to embed real-world insights before protocol finalization and use it to stress-test assumptions around eligibility criteria, endpoint definitions, and projected enrollment rates under real-world conditions.

Longitudinal clinical data, particularly when electronic health records are combined with complementary data sources such as claims, can reveal insights that prevalence estimates alone may miss. Prior lines of therapy, laboratory trends, disease severity markers, referral pathways, and comorbidities all influence whether a patient is realistically eligible and likely to enroll. Viewing the full treatment journey allows teams to assess whether inclusion and exclusion criteria align with how disease is diagnosed and managed during routine clinical practice.

When applied early, these insights help reduce the risk of overestimating the truly eligible populations and help prevent downstream feasibility gaps during study execution.

Precision in Site and Patient Strategy

While historical enrollment performance remains a valuable indicator, past success does not guarantee that a site currently treats patients who meet highly specific eligibility requirements.

Real-world insight allows sponsors to evaluate feasibility at the patient-level. Rather than solely relying on aggregate performance metrics, teams can assess whether a site actively manages patients who match the study criteria. This distinction is crucial as competition for eligible participants intensifies.

Advanced modeling approaches allow teams to simulate enrollment scenarios before a study begins. By examining patient funnels, referral dynamics, and treatment pathways, sponsors can better anticipate how many patients are likely not only to qualify, but to enroll and remain on study. This represents a shift from directional forecasting to data-informed feasibility planning grounded in how care is delivered in practice.

“By scaling the site insights derived from real-world data, we’re better able to select sites that enroll patients aligned with our trial criteria,” Emily Carter, AbbVie

Data Quality, Infrastructure, and Global Realities

The promise of RWD is significant, but its value depends on the integrity of the underlying data. Incomplete documentation, inconsistent coding, limited linkage across datasets, and gaps in longitudinal continuity can restrict the reliability of insights. Advanced analytics and machine learning can enhance harmonization and help scale the curation of unstructured clinical information, but no methodology can overcome fundamentally poor data quality.

“Real world data is an essential part of our development lifecycle when it comes to generating evidence. One of the main challenges is data quality. You can have as much data as you want, but if quality is poor, you can apply your AI and everything to be garbage in, garbage out,” Alex Asiimwe, PhD, Gilead Sciences

Beyond quality considerations, infrastructure fragmentation remains a challenge. Many organizations operate across functional silos, license datasets independently, and lack standardized frameworks for sharing and integrating insights across teams. Global development further complicates the landscape. Robust data sources may be available in certain regions, while others lack comparable depth or accessibility. Matching feasibility modeling with geographic strategy requires careful coordination and a realistic assessment of data availability.

Speed is another critical factor. Insight generation must align with development timelines. If analyses take months to complete, their ability to shape protocol decisions diminishes. Scalable infrastructure, clear governance, and embedded workflows are essential to ensure that real-world insights inform decisions when they matter most.

Fit-for-Purpose Integration and Cross-Functional Alignment

Ultimately, the question is not whether to use real-world data, but when and how to apply it appropriately. While regulatory openness has grown, RWD should be integrated for clear, fit-for-purpose reasons and guided by scientific rationale, not momentum. That requires cross-functional integration across clinical, epidemiology, regulatory, and operations to weigh trade-offs, ethics, and feasibility.

RWD is not a replacement for randomized trials, but it can strengthen development by reducing uncertainty and supporting study design with clinical reality. As the industry evolves, designing trials for the real world is increasingly essential to generating evidence that is both rigorous and operationally achievable.

About Ashley Daigneau 

Ashley Daigneau is head of clinical trials at Verana Health, where she oversees the strategy and execution of innovative clinical research solutions leveraging real-world data. Ashley has more than 15 years of experience supporting the development of real-world evidence strategies and overseeing clinical study execution.

Specialty medications are expanding what is clinically possible, but not without a price. The affordability gap on these therapies continues to widen, placing sustained pressure on health plan budgets. U.S. prescription drug spending reached approximately $467 billion in 2024, with projections exceeding $556 billion by the end of 2026. As costs rise, employers and pharmacy benefit managers (PBMs) face increasing pressure to ensure that high-cost therapies remain both clinically appropriate and financially sustainable.

To address pharmaceutical affordability, employers are increasingly turning to technology-enabled savings strategies. Two commonly considered approaches are alternative funding programs (AFPs) and in-benefit optimization. AFPs are designed to address high-cost specialty therapies through alternative sourcing pathways, often unlocking meaningful savings in concentrated areas of spend. In-benefit optimization focuses on reducing waste within existing pharmacy benefit structures, enabling more consistent, system-wide cost control.

To determine which platforms best promote financial optimization, employers should first understand the operational steps to reduce pharmaceutical spending and identify how different analytics-powered systems address them. 

The Operational Blueprint for Cost Reduction

To operationalize meaningful savings, PBMs should consider the following steps, many of which are incorporated into algorithm-driven optimization strategies:

1. Recognize specialty spend concentrations: Identify which limited quantities of drugs or therapies are driving disproportionate expenses and validate whether each case is appropriate and necessary.
2. Evaluate structure for inefficiencies: Use analytics to identify duplication, overlapping treatment, regimen complexity, and oversupply to determine avoidable refill occurrence.
3. Stress-test disruptions: Assess time-to-therapy, interfacing burden, and risk of discontinuity when implementing spending reduction pathways.
4. Prioritize prescriber operations: Implement scalable margin protections that benefit clinical workflows and support clinician operations.
5. Ensure regulatory adherence: Certify financial pathways are defensible to auditors, members, regulators, and clinicians.
6. Look beyond financial outcomes: Track adherence, continuity, complaints, and escalations to support patient well-being within savings pathways.

Implementing the included steps will help PBMs to establish secure, defensible savings. Yet pre-established spending reduction technologies and pathways can make these steps feel more achievable. For this reason, plan sponsors often consider structured cost-reduction platforms designed to address high-cost specialty spending, such as AFPs.

Understanding the Role of AFPs

AFPs are one way to address disproportionate drug spend across pharmaceutical markets. By leveraging alternative sourcing pathways, these programs can reduce costs for select therapies, particularly where traditional benefit structures offer limited flexibility. In many cases, AFPs coordinate access through manufacturer patient assistance programs (PAPs) or other external mechanisms to improve affordability for members. This option reduces patient out-of-pocket costs while enabling recipients to afford medications for life-saving or chronic conditions. 

Implementing AFPs requires thoughtful coordination across stakeholders, including pharmacies, manufacturers, and support programs. These models often introduce additional documentation, communication, and process considerations that plan sponsors should evaluate alongside potential savings.

When applied with clear guardrails, AFPs can serve as an effective component within a broader cost management strategy, particularly for high-cost, high-impact therapies.

In-benefit optimization focuses on identifying and resolving inefficiencies within existing pharmacy workflows.

Technology-Enabled Savings Within the Benefit

In-benefit optimization allows PBMs to prioritize savings within their existing workflows. This approach leverages a unified platform to address common sources of excess spend to eliminate waste and inefficiencies.

Most drug and waste inefficiencies occur in a few areas within pharmaceutical channels. Duplicative or overlapping therapies are common sources, often aggravated by oversupply, early refills, and unused medications. There are also many opportunities for lower-cost medications through in-network channels that are often missed. 

Prescription adherence can also prove detrimental for employer margins. If a patient’s regimen is overly complex, they are unlikely to follow their medication routine. By identifying where certain drug outcomes overlap with algorithm-guided recommendations, PBMs can eliminate unnecessary therapy use and achieve cost reductions without deviating from normal pharmacy pathways or extending services to multiple points of contact.

Automated drug-spend intelligence platforms that integrate in-benefit optimization directly into prescriber workflows eliminate redundant administrative tasks that exacerbate workloads. This approach allows plan sponsors to automatically optimize pricing in context of availability, policy changes, and updated drug costs.

Both AFPs and in-benefit optimization offer viable ways to establish savings. When PBMs apply clear guardrails, they can leverage both approaches concurrently to help operationalize each outlined step for margin protection. Layering both approaches using drug-spend intelligence platforms allows PBMs to address small specialty spend concentrations and achieve long-term, sustainable cost management.

Guardrails for Sustainable Drug Cost Strategies

Whether employers rely on in-benefit optimization, AFPs, or a hybrid model, they should ensure their chosen method meets several non-negotiable sustainable savings requirements to preserve defensibility.

The non-negotiables: 

• Preserves continuity of therapy and regimen.
• Eases prescriber administrative workload.
• Operates within outlined compliance boundaries.
• Creates clear, documented savings.

When employers use available technology to achieve sustainable spending reductions that meet these requirements, benefit sponsors can confidently remain compliant while defending their margins.

Designing the Right Savings Strategy

With the affordability crisis squeezing margins across all stakeholders, plan sponsors must implement cost-saving strategies. In-benefit optimization addresses each cost-management step by implementing digital tools that work within pharmaceutical workflows to reduce costs. AFPs provide targeted solutions for high-cost therapies, while in-benefit optimization delivers broader, system-level efficiency by addressing waste within existing workflows.

Both options have the potential to create measurable savings when plan sponsors apply them with clear guardrails. When plan sponsors layer data-driven optimization strategies with clear guardrails, they can achieve sustainable cost control, improve member experience, and support long-term benefit stability. 

About Ryan Czado, PharmD, MBA,  

Ryan Czado, PharmD, MBA, is a pharmacy benefits expert with a background spanning PBMs, health plan consulting, and employer benefits strategy. With leadership roles at Express Scripts, Minuteman Health, Deloitte, and Lockton, Ryan has helped organizations streamline pharmacy programs and reduce costs. As Chief Pharmacy Officer at RazorMetrics, he focuses on simplifying prescription decisions to optimize healthcare spending.  

What You Should Know

• Healthcare intelligence leader Health Catalyst has signed a definitive agreement to divest its mid-revenue cycle business unit, Vitalware, LLC, to Med-Metrix for $147M in cash.
• The transaction allows Health Catalyst to shed a non-core financial software asset and sharpen its corporate focus on driving cost, clinical, and consumer performance improvements.
• The $147M cash injection, combined with existing capital, will be deployed to fully repay and terminate Health Catalyst’s $160 million senior secured term loan facility.
• Vitalware is a recognized mid-revenue cycle leader that generated approximately $37 million in revenue during fiscal year 2025.
• The corporate separation frees up long-term financial flexibility, allowing Health Catalyst to accelerate its core technology and healthcare AI roadmap.

Focus Over Fragmentation: Why Health Catalyst Is Divesting Vitalware for $147M

The healthcare technology and enterprise software landscape is working through an intensive phase of structural realignment. Over the past decade, many digital health vendors sought to build expansive, multi-categorical platforms by acquiring adjacent software business units across clinical, operational, and financial silos. However, running a highly fragmented portfolio often dilutes an organization’s core engineering focus and ties up valuable capital in distinct software categories that require separate research and development pipelines.

In a macroeconomic market that increasingly penalizes operational complexity, healthcare leaders are realizing that enterprise success requires deep domain conviction rather than broad, disconnected offerings. For technology provider organizations, long-term sustainability means shedding non-core business segments to maximize capital flexibility, clear outstanding debt, and aggressively fund specialized artificial intelligence frameworks that return immediate, measurable value to customers.

To streamline its operational profile and fully back its long-term corporate roadmap, healthcare intelligence pioneer Health Catalyst, Inc. has announced a definitive agreement to divest Vitalware, LLC and its associated mid-revenue cycle business unit. The business will be acquired by technology-enabled revenue cycle specialist Med-Metrix for a total consideration of $147M in cash. Expected to close in 2026 pending standard regulatory waiting periods, the transaction represents a calculated corporate pivot designed to accelerate Health Catalyst’s core clinical transformation.

Deleveraging the Balance Sheet to Accelerate the Core AI Roadmap

Vitalware by Health Catalyst has long operated as a highly respected suite of mid-revenue cycle solutions, providing hospitals with specialized data models and applied AI to manage coding compliance, chargemaster tasks, charge capture, and federal price transparency rules. The business unit achieved best-in-KLAS status and captured approximately $37 million in revenue during fiscal year 2025. Yet, financial operations represent an administrative category entirely distinct from the data-driven clinical and operational improvement initiatives that form the historical identity of Health Catalyst’s platform.

By divesting this segment to Med-Metrix—a company explicitly structured to invest deeply in dedicated revenue cycle management—Health Catalyst immediately strengthens its financial flexibility. The company plans to merge the $147 million in net cash proceeds with existing cash on hand to fully repay and terminate its outstanding senior secured term loan facility. This financial maneuver wipes out approximately $160 million in outstanding principal debt as of March 31, 2026, alongside associated interest obligations and prepayment costs, structurally cleaning the corporate balance sheet.

Ben Albert, CEO of Health Catalyst, highlighted the strategic necessity of the transaction, calling it a significant step forward for the enterprise. Albert noted that by concentrating the business precisely around the clinical environments where they maintain the deepest conviction, the company can deploy a lean capital structure optimized to sustain its long-term growth priorities.

Monetizing a Moat of $2.8 Billion in Documented Outcomes

Once free of its legacy debt obligations, Health Catalyst’s core strategy will focus heavily on scaling its proprietary healthcare improvement data engine. Built on 18 years of historical tracking and backed by $2.8 billion in validated, documented outcomes, this core platform allows health systems to move seamlessly from raw data silos to confident, prioritized actions. The freed-up capital will directly fund an aggressive, clinical AI roadmap designed to enable hospital networks to autonomously turn their localized data lakes into clear operational improvements across cost, clinical care, and consumer engagement performance.

To complete the transaction, Raymond James acted as the exclusive financial advisor to Health Catalyst, with Latham & Watkins LLP providing outside legal counsel. Additional statutory disclosures surrounding the cash divestiture have been filed via a Form 8-K with the Securities and Exchange Commission.

What You Should Know

• Philips and WellSpan Health have announced a seven-year strategic alliance establishing a comprehensive research, co-development, and advanced imaging platform across Central Pennsylvania and Northern Maryland.
• Moving past standard vendor transactions, the agreement marks the first joint innovation and research strategy between Philips and a U.S. community health system.
• The research framework focuses on validating AI and digital tools to optimize hospital throughput, cost, and workflow efficiency, directly supporting WellSpan’s goal to reclaim over 500,000 hours of workforce time annually.
• The enterprise commercial agreement establishes Philips as the preferred vendor across all major imaging modalities (CT, MR, digital X-ray, ultrasound, and image-guided therapy) spanning all 12 WellSpan hospitals, diagnostic centers, and ambulatory surgery sites.
• A core feature of the partnership is a unified technology lifecycle management blueprint that coordinates equipment, specialized training, and software upgrades under a single framework to eliminate regional patient access gaps.

Shifting the Innovation Axis: Why Philips Partnered with WellSpan Health on a 7-Year EHR-Neutral Alliance

The operational environment for regional healthcare delivery systems is working through an intensive structural transformation. Historically, cutting-edge clinical research, advanced artificial intelligence validation, and medical device co-development have been heavily concentrated within a handful of massive, highly funded urban academic medical centers. Yet, this centralized innovation blueprint introduces an acute mismatch with the realities of American medicine: community health networks are where the overwhelming majority of the population actually goes to receive care.

Today, these regional networks face severe administrative headwinds, characterized by compressed operating margins, an escalating chronic care burden, and profound clinician burnout. When community systems are forced to act as passive buyers—purchasing disconnected tech stack solutions that require constant custom integrations—data fragmentation worsens, and valuable staffing hours are lost to administrative tasks. To ensure long-term viability, progressive community provider networks must shift from being passive software adopters to active co-creators of enterprise-grade technology.

To dismantle this legacy procurement model and place regional care networks at the center of medical technology evolution, Philips and regional clinical powerhouse WellSpan Health have announced a landmark seven-year strategic alliance. Encompassing all 12 WellSpan hospitals, alongside its complete footprint of diagnostic imaging and ambulatory surgery centers, the alliance establishes a scalable, AI-driven, platform-based framework designed to drive measurable improvements across patient care quality, workflow efficiency, and technology lifecycle management.

Eliminating the Efficiency Drain: Reclaiming 500,000 Workforce Hours

The definitive cornerstone of the Philips-WellSpan alliance is a deeply integrated research agreement and joint innovation strategy—marking the first partnership of its kind between Philips and a U.S. community healthcare provider. Rather than deploying uncalibrated, off-the-shelf generative applications, WellSpan will actively pull from Philips’ global R&D pipeline to design, validate, and build next-generation medical intelligence products.

The primary metric guiding this collaborative research is the aggressive removal of workforce friction. The joint teams will systematically analyze how embedded AI and digital orchestration software impact imaging throughput, case-mix costs, and point-of-care charting times. This structural optimization is engineered to fulfill WellSpan’s explicit enterprise goal: reclaiming more than 500,000 hours of workforce time every single year.

Roxanna Gapstur, Ph.D., R.N., President and CEO of WellSpan Health, emphasized that as the system’s clinical capabilities have scaled, leadership has assumed a responsibility to be highly intentional regarding technology lifecycle support. Gapstur noted that this alliance builds a coordinated infrastructure that advances digital, AI-enabled care while demonstrating that community health networks belong at the very center of healthcare innovation.

Unifying Lifecycle Management to Eradicate Regional Access Gaps

On a commercial scale, the agreement designates Philips as WellSpan’s preferred enterprise vendor across all core diagnostic imaging and image-guided therapy modalities, including CT, MR, digital X-ray, and ultrasound. This comprehensive standard ensures a smooth, uniform experience for clinicians and patients across the entirety of Central Pennsylvania and Northern Maryland.

Importantly, the relationship moves beyond traditional purchasing to focus heavily on a coordinated approach to technology lifecycle management. WellSpan and Philips will manage all hardware acquisitions, enterprise service agreements, clinical training modules, and software upgrade paths under a single unified framework. By synchronizing these updates, the health system can guarantee consistent imaging availability across all regional facilities, eliminate historical gaps in patient access, and build a stable database foundation for subsequent algorithmic tools.

Roy Jakobs, CEO of Royal Philips, stated that combining Philips’ health technology leadership with WellSpan’s deep clinical expertise creates an ideal mechanism to deliver measurable operational gains. The platform-based approach supports frontline clinicians in their daily tasks while actively shaping the future of global care delivery.

What You Should Know

• Virtual cardiometabolic provider Vida Health has finalized a nationwide partnership with grocery technology leader Instacart to integrate category-specific grocery stipends into virtual chronic care delivery.
• The collaboration utilizes Instacart Health Fresh Funds to provide members with direct financial stipends dedicated exclusively to purchasing dietitian-approved, nutritious groceries.
• The initiative directly targets the social determinants of health (SDOH), leveraging Instacart’s logistics network which reaches 98% of U.S. households—including 95% of low-income, low-access food deserts.
• Guided by a multidisciplinary team of obesity medicine-certified physicians and registered dietitians, the program delivers culturally sensitive meal plans accounting for budget constraints across more than 25 distinct backgrounds.
• Future infrastructure phases plan to make Vida’s clinical meal plans directly shoppable via the Instacart Marketplace while establishing direct employer subsidization channels within enterprise benefit packages.

Prescribing the Pantry: Why Vida Health and Instacart Are Unifying Food Stipends and EHR Nutrition Loops

The clinical management of chronic cardiometabolic diseases across the United States has arrived at a critical operational crossroads. For decades, the traditional healthcare apparatus has treated metabolic instability, obesity, type 2 diabetes, and severe hypertension through highly isolated, clinical interventions. Frontline physicians and registered dietitians frequently deliver expert nutritional advice during brief patient encounters, advising vulnerable individuals to radically alter their dietary choices. However, once a patient leaves the virtual or brick-and-mortar clinic, this advice routinely collides with harsh socioeconomic realities.

In underserved areas, rural communities, and urban food deserts, accessing fresh, nutritious food is a significant structural barrier. When clinical guidance is completely disconnected from real-world food access, patient compliance drops. Individuals are forced to default back to affordable, processed, ultra-palatables that worsen their metabolic conditions. For self-insured employers, commercial health plans, and risk-bearing provider organizations, this fragmentation leads to an unmanaged cost spiral—driving up avoidable emergency department visits, accelerating chronic disease progression, and eroding the return on digital health investments.

To close this gap between clinical intent and daily nutrition, value-based virtual provider Vida Health has announced a comprehensive nationwide partnership with Instacart. By integrating Instacart Health Fresh Funds directly into its virtual cardiometabolic workflows, Vida is transforming passive medical advice into a highly accessible, financially incentivized system of action.

Activating Fresh Funds to Bypass the Food Desert Barrier

The core operational mechanism driving the Vida-Instacart partnership is the deployment of Instacart Health Fresh Funds. These are category-specific grocery stipends provided to Vida members, allowing them to instantly purchase the exact dietary recommendations outlined by their care teams. Rather than forcing low-income or food-insecure individuals to absorb the high out-of-pocket costs of specialized diets, this stipend architecture lowers the financial barriers that historically derail nutritional adherence.

This logistical workflow is supported by Instacart’s extensive North American delivery network, which connects with more than 2,200 retail banners representing nearly 100,000 local stores. Instacart’s infrastructure reaches more than 98% of all U.S. households, crucially including 95% of areas formally designated as low-income and low-access food deserts. By pairing same-day home delivery with flexible, destination-restricted funds, the collaboration removes the geographic and transportation barriers that commonly impede rural and underserved patient populations.

Amy Mushlin, Chief Clinical and Member Service Officer at Vida Health, emphasized that building healthy lifestyle habits demands far more than raw clinical information. It requires empathetic, culturally relevant guidance combined with immediate, physical access to nutritious options. By syncing with Instacart, the specific adjustments suggested by dietitians and health coaches become instantly actionable at the point of purchase, allowing members to safely execute impactful lifestyle modifications.

Culturally Grounded Navigation and the Value-Based Continuum

Vida’s virtual cardiometabolic platform functions on a whole-person, multidisciplinary care model delivered in both English and Spanish across all 50 states and Washington, D.C.. Its clinical network—comprising obesity medicine-certified physicians, registered dietitians, licensed therapists, and expert coaches—is engineered to manage patients across the complete acuity spectrum. To ensure long-term engagement, Vida’s dietitians design culturally sensitive nutritional pathways that incorporate flavor profiles and culinary traditions spanning more than 25 distinct cultural and ethnic backgrounds while adjusting for localized store availability and household budget realities.

The integration with Instacart is systematically designed to scale across multiple strategic phases. The initial rollout focuses heavily on immediate member activation and engagement, linking Vida’s clinical protocols directly to Instacart’s online ordering network. Subsequent deployment phases will allow dietitian-developed, disease-specific meal plans to be directly shoppable with a single click inside the app. Furthermore, the organizations are actively exploring employer-subsidized food access models to integrate these programs directly into commercial enterprise benefit structures. This maps out a future where personalized nutrition support and grocery logistics function as unified components of enterprise cardiometabolic care.

As health systems continue expanding through acquisitions and partnerships, many find themselves racing to bring new practices onto shared EHR platforms. The motivation is clear: unify care, streamline operations, and unlock value across the enterprise. But beneath that strategic vision lies a messy operational reality – one that too often gets overlooked until it’s too late.

At the center of this challenge is legacy data.

For every practice or partner brought into the fold, there’s a trail of applications, contracts, and patient data that needs to be rationalized and retained. Done right, this process supports compliance, reduces risk, and keeps the onboarding timeline on track. Done haphazardly, it leads to costly delays, redundant systems, and compliance vulnerabilities that can unravel even the best-laid integration plans.

Many health systems underestimate the complexity of legacy data management during onboarding. And that misstep can cost more than just money. It can erode trust, stall growth, and expose organizations to serious regulatory risk.

The overlooked first step: contract review

When a new practice is acquired, attention typically goes straight to clinical integration. But before a single data extract is ordered or archive strategy is discussed, the first priority should be reviewing contracts tied to legacy applications. Too often, organizations skip this step and unknowingly target systems that can’t be sunset for years due to termination clauses or data release restrictions.

Worse, some vendors use this confusion to their advantage. Ordering the wrong type of data extract, or missing critical deadlines, can trigger auto-renewals that lock systems in place far longer than planned.

Application inventory management is a smart investment

To prevent these costly missteps, leading organizations are investing in application inventory management tools. These platforms track everything from contract terms to data ownership to rationalization decisions. Having this centralized visibility not only supports strategic planning, it also saves time and resources during transitions by preventing unnecessary projects or duplicate efforts.

Even avoiding a single contract renewal that didn’t need to happen can pay for the system.

A missed opportunity for compliance and cost control

Surprisingly, many health systems still lack comprehensive data retention policies. And even when they exist, enforcement is often inconsistent across departments or application types. This results in over-retention of unnecessary data, under-retention of key records, and a lot of gray area when it comes time to archive.

Done well, data retention policies guide smarter, more cost-effective archiving decisions. Not every legacy system needs a full clinical archive. In some cases, a small subset of documents or a limited dataset is all that’s required to meet regulatory requirements. But you can’t make that call without a clear policy in place.

A mature retention strategy also supports compliance with evolving regulations, including the Cures Act. With growing pressure to provide patients with access to all their health data, no matter where it originated, organizations must define and enforce retention standards that align with both internal policy and external expectations.

It’s about the patient, too

While compliance and cost control might be top priorities, the patient experience must also be considered. More patients expect access to historical records than ever before. In some cases, health systems are choosing to retain certain data beyond required timeframes simply because it helps patients tell a more complete health story.

That may feel counterintuitive after talking about cost control, but the balance is possible. It starts with defining what’s most important to the organization and choosing a data management strategy that supports those goals.

Standardization: The path to scale

As health systems grow, they need onboarding processes that don’t reinvent the wheel every time. That means building a repeatable playbook for how to handle legacy data from contract review to archive execution. The more standardized the approach, the faster and more affordable the onboarding.

This is especially critical for systems leveraging Community Connect, where consistency across sites matters for both operations and compliance. Standard workflows, clear decision points, and trusted data partners can dramatically reduce the lift required from internal teams.

Choose experience

Finally, while onboarding might seem like a job for internal teams, legacy data management is not the place to experiment. The stakes are too high. Organizations should work with partners who understand the nuances of clinical, financial, and operational data and who have done it before, at scale.

It’s not just about flipping the switch on a new EHR. It’s about protecting your organization from hidden costs, regulatory exposure, and the operational drag that comes from ignoring the data left behind.

Growth is good. But scalable, compliant growth requires a plan. And that plan needs to start with legacy data.

About Dave Lamar

Dave Lamar is Chief Growth Officer of MediQuant, a leading provider of enterprise data archive technology for the healthcare industry. Since joining the company in 2017, Dave has redefined projects and services for increased revenue, helped to integrate and reframe the services provided by new acquisitions for a comprehensive offering, and guided the opportunity for the firm to win the largest assignment in MediQuant history with the Department of Defense

What You Should Know

• Value-based obesity management leader Ilant Health has closed a $15M Series A funding round led by Cornucopian Capital, elevating its total funding footprint past $22 million.
• The financing round features strategic participation from naturalX, Peakbridge, Semcap AI, Evidenced, Operator Partners, and existing investors Celtic, LifeX, and AlphaLab.
• Founded by former McKinsey and Molina Healthcare executive Elina Onitskansky, the company bypasses fragmented weight-loss apps to deliver an integrated, value-based cardiometabolic care platform.
• Early clinical deployments document that Ilant members achieve a 15% average weight loss—outperforming the 5.8% benchmark typically recorded in uncalibrated, real-world settings.
• To bring structural transparency to corporate pharmacy spend, Ilant leverages direct contracting and transparent pricing frameworks through integrations with pharmaceutical leaders Eli Lilly and Novo Nordisk.

Defeating the GLP-1 Cost Spiral: Why Ilant Health Raised $15M to Scale Outcomes-as-a-Service

The commercial healthcare benefit ecosystem is currently confronting an unsustainable economic dilemma. The rapid rise and explosive consumer demand for GLP-1 receptor agonist weight-loss therapies have left self-insured employers and health plans trapped in a severe fiscal squeeze. Corporate benefits directors face a difficult choice: they must either expand open-ended access to these premium specialty medications and watch their pharmaceutical spend spike dramatically, or heavily restrict coverage and face compounding long-term chronic disease liabilities and structural health plan attrition.

The underlying issue stems from a persistent focus on transaction-oriented point solutions that treat obesity in isolation from broader cardiometabolic health. Traditional weight-loss programs frequently operate under a one-size-fits-all model centered entirely on drug access, failing to integrate baseline clinical, behavioral, and personal data inputs. Without continuous, data-driven optimization or multi-modal lifestyle support, real-world GLP-1 adherence rates drop, leading to an average real-world weight reduction of just 5.8%. For enterprise organizations, this fragmented approach represents a broken system—one where employers pay premium prices for uncoordinated care while chronic disease markers continue to slide.

To eliminate this data fragmentation and introduce a precise, outcomes-driven framework for metabolic care, value-based obesity treatment pioneer  Ilant Health has finalized a $15M Series A financing round. Led by Cornucopian Capital, with prominent participation from naturalX, Peakbridge, Semcap AI, Evidenced, Operator Partners, and existing backers Celtic, LifeX, and AlphaLab, the round brings Ilant’s total capitalization to more than $22 million. The capital injection will be used to fuel rapid market expansion, scale its precision analytics engine, and deliver integrated obesity care across a growing network of employer and health plan partners.

Precision Matching and the “Outcomes-as-a-Service” Mandate

Founded by Elina Onitskansky, an alumnus of McKinsey and former executive at Molina Healthcare, Ilant Health functions as a comprehensive, technology-enabled entry point for individuals navigating complex metabolic conditions. Moving past generic digital weight-loss programs, Ilant delivers a precision-matched care model that evaluates every patient across clinical, behavioral, and personal variables. The platform automatically builds an individualized treatment roadmap that combines intensive behavioral therapy, metabolic medications (spanning both GLP-1 and non-GLP-1 options), and bariatric surgical pathways to simultaneously optimize nutrition, physical movement, and stress management.

By deploying data analytics to match members with the specific clinical interventions most likely to trigger a personal response, Ilant systematically avoids ineffective care. The performance data surrounding this model shows significant improvements over standard care: members enrolled in Ilant achieve an average weight loss of 15%. This clinical success is accompanied by major improvements in holistic patient metrics, including an average of two additional self-reported mentally healthy days per month.

Aryeh Ganz, Founder and Managing Partner of Cornucopian Capital, highlighted the strategic shift underwritten by this model, stating that the next generation of category-defining digital health enterprises must deliver “outcomes as a service” rather than just standalone tools or medication access. Ganz noted that the future of cardiometabolic care will be won by platforms capable of aligning clinical rigor with verified economic value, matching the right treatment option to the right patient at the optimal point of intervention.

Bending the Pharmacy Cost Curve via Direct Contracting

The primary commercial moat for enterprise clients adopting Ilant sits within the platform’s direct, transparent integration with major pharmaceutical manufacturing networks. In November 2025, Ilant established direct contracting and transparent pricing solutions for obesity medications through Eli Lilly’s Employer Connect program, alongside active operational collaborations with Novo Nordisk. These manufacturer alignments give enterprise benefit managers clear visibility and control over their pharmacy budgets, offering predictable, transparent medication pricing paired with flexible benefit design options.

Kenneth L. Gardner, Director of Growth, Benefit Operations, emphasized that Ilant’s precision-based, data-driven approach immediately distinguished it from medication-only models. By running advanced population health analyses, Ilant isolates exactly which corporate members are positioned to derive the highest clinical and financial benefit from specific therapies. This targeted tracking gives benefits teams deep confidence in both patient experience and immediate return on investment (ROI), ensuring that chronic care delivery bends the employer’s long-term spend curve.

Healthcare is moving toward models that reward outcomes, continuity, and population health management, yet disparities in access to specialized care continue to persist. And while community hospitals are central to closing this gap, they are being inundated with technologies that promise to transform care yet are structurally difficult to translate from large academic medical centers to smaller ones. 

Rural hospitals operate with lower patient volumes and thinner margins, practical realities that force patients to travel long distances for specialty diagnostics and procedures, particularly in oncology, pulmonary medicine, and cardiovascular care.

It is not a failure of commitment. It is a question of feasibility.

A platform that works well in a high-volume referral center can falter locally if it requires specialized staffing, unpredictable scheduling, or capital risk that smaller systems cannot absorb. Hospital leaders, therefore, need a practical way to determine which advanced technologies truly belong in their environment. 

Four questions can help distinguish innovations that look compelling in demonstrations from those that can succeed in daily practice.

1. Can We Deliver This Consistently, Not Occasionally?

Advanced diagnostics only improve outcomes if patients can reliably access them. Programs that rely on visiting specialists, limited scheduling blocks, or fragile staffing models rarely achieve sustained utilization. When availability is uncertain, referring physicians continue to send patients elsewhere.

A strong indicator of success is the ability to offer the procedure on a predictable schedule using local staff. Programs that must be canceled frequently or require complex coordination often fail to gain momentum. Leaders should also evaluate turnaround times. If patients wait significantly longer locally than at regional centers, referral leakage will persist.

Consistency builds confidence among clinicians and patients alike.

2. Does It Fit Our Workforce Reality?

Many advanced technologies were developed for large institutions with subspecialized teams. Community hospitals must assess whether existing clinicians can safely and efficiently adopt the technology.

Programs are far more viable when they can be staffed by current physicians and care teams following structured training, rather than requiring recruitment of scarce specialists. Dependence on a small number of highly specialized individuals introduces significant continuity risk.

Successful implementations typically allow clinicians to reach proficiency within months and maintain competence through routine use. Technologies that require frequent practice to remain safe can be difficult to sustain in lower-volume settings.

The key question is whether expertise can be maintained, not just acquired.

3. Will Patient Volume Support Long-Term Viability?

Without the referral base of major academic centers, community hospitals must realistically assess local demand. One useful benchmark is outbound referrals. If a hospital regularly transfers patients elsewhere for a specific diagnostic or procedure, recapturing a portion of that volume may support a local program.

Low volumes create cascading challenges. Per-procedure costs rise, clinicians struggle to maintain proficiency, equipment sits idle, and scheduling becomes inefficient. Over time, an underutilized program can strain finances and erode confidence.

Technologies addressing common conditions with clear local prevalence tend to be more sustainable than highly specialized services.

4. Does It Strengthen Local Care or Fragment It?

Not every advanced capability should be decentralized. Some complex interventions are best concentrated at tertiary centers. However, technologies that anchor care locally can strengthen continuity and patient retention. Early diagnostics are especially valuable because they often determine where subsequent treatment will occur.

A positive indicator is the ability for patients to move from diagnosis to treatment within the same regional network or through coordinated partnerships. If most patients still require immediate transfer elsewhere, the local benefit may be limited.

Programs that reinforce relationships with primary care physicians and local specialists tend to generate durable referral patterns.

A Practical Definition of Innovation

For community hospitals, innovation is not about acquiring the most advanced tool available anywhere. It is about expanding what can be delivered safely, reliably, and sustainably for the population they serve.

When the right technologies are implemented thoughtfully:

• Patients avoid long travel for critical diagnostics
• Diseases are detected earlier
• Care fragmentation decreases
• Hospitals retain patients who might otherwise leave the system
• Financial sustainability improves

In these cases, access and economics reinforce one another.

Why This Matters Now

Scalable innovations that spread to the broader healthcare landscape improve access and benefit communities. Community hospitals do not need every new technology. They need the right ones, those aligned with their workforce, patient base, and operational realities.

When advanced capabilities become feasible at the community scale, the impact extends well beyond individual procedures. Hospitals strengthen their role as regional anchors of care, patients receive services closer to home, and innovation fulfills its most important promise: improving outcomes for more people, not just those living near major medical centers.

About Jian Zhang 

Jian Zhang is the founder and CEO of Noah Medical. Prior to founding Noah Medical in 2018, he co-founded two other startups, was employee #2 at Auris Health (which was acquired by Johnson & Johnson for $5.7 billion), and previously worked at Intuitive Surgical. 

More than 180 rural hospitals in the United States have closed since 2005, according to the Chartis Center for Rural Health, while providers spend over $25 billion annually on claims adjudication, with nearly $18 billion of that tied to claims that are ultimately paid, according to Premier Inc.

That’s not a demand problem. It’s an administrative one. And increasingly, it’s a technology infrastructure problem tied to how work is managed, measured, and automated.

And for rural hospitals operating with limited staff and thin margins, that level of inefficiency isn’t just costly; it’s unsustainable.

The Work Behind Getting Paid

In most healthcare organizations, a claim isn’t processed once and paid; it’s worked over and over again.

It gets handed off, corrected, resubmitted, and appealed. Each of those touch points requires human time, and each one introduces delay and cost. According to the Council for Affordable Quality Healthcare (CAQH), administrative transactions in healthcare still cost the system tens of billions annually, with a sizable portion being driven by manual processes.

Even more concerning, a large share of denied claims that ultimately get paid requires intervention, meaning that much of the work happening inside financial operations is rework, not value creation, as highlighted in the Premier analysis.

That’s where a lot of margins disappear.

Why Rural Hospitals Feel It First and Hardest

Large health systems can absorb inefficiency. Rural hospitals can’t.

Nearly half of rural hospitals are operating at a financial loss, and many are at risk of closure due to sustained margin pressure, according to the Chartis Center report.

When you have smaller teams, fewer specialists, and less redundancy, every extra touch matters. Administrative staff aren’t just processing claims; they’re juggling eligibility issues, documentation gaps, payer requirements, and follow-up.

There’s no buffer.

In larger systems, inefficiency is expensive. In rural hospitals, it’s existential.

Complexity Is Growing Faster Than Capacity

Payers are continuing to increase requirements, which means more edits, more prior authorizations, and more documentation specificity. A 2024 American Medical Association survey found that physicians complete an average of 43 prior authorizations per week with many reporting delays that directly impact care delivery.

At the same time, systems remain fragmented, and workflows are rarely aligned across the financial lifecycle. The result is simply more work per claim. Not more reimbursement. Not better outcomes. Just more effort required to get paid.

Where AI Fits and Where It Doesn’t

There’s a lot of discussion right now about AI solving administrative burden in healthcare. But in practice, AI is not a replacement for the people doing this work, especially in rural hospitals.

The reality is that a substantial percentage of the issues that require human intervention are tied to nuance. Documentation context, payer-specific rules, and incomplete information aren’t problems you can fully automate.

Beyond automating repetitive tasks, AI is increasingly being used to improve visibility—helping organizations analyze claims data, identify patterns, and enhance payment accuracy across workflows, as outlined by McKinsey & Company

But resolution still requires human judgment.

In rural hospitals, the goal isn’t to replace people. That’s not realistic, and it’s not the right objective. The goal is to reduce the amount of unnecessary work those people are being asked to do so they can focus on more high-value work.

AI works best as a force multiplier, helping teams focus on what actually requires expertise instead of chasing preventable problems.

The Real Opportunity: Reducing the Work, Not Just Automating It

Too often, the focus is on how to process work faster. The better question is, why does the work exist in the first place?

If a claim is touched multiple times before it’s paid, speeding up those touches doesn’t solve the problem. It just accelerates inefficiency.

The opportunity is to reduce the number of touches altogether.

That starts with understanding where work is being created, where breakdowns are happening, where rework is being introduced, and where effort is being duplicated. From there, organizations can begin to redesign workflows to prevent issues instead of reacting to them.

That’s where both operational discipline and technology need to come together.

What’s at Stake

Rural hospitals aren’t just healthcare providers; they’re access points for entire communities.

When they close, patients don’t just lose convenience, they lose access. The Chartis Center for Rural Health continues to warn that rural hospital closures create care deserts, forcing patients to travel significantly farther for essential services.

We’re investing heavily in clinical innovation and AI across healthcare. But if the administrative side of the system continues to erode financial stability, those investments won’t matter for the organizations that can’t afford to stay open.

Administrative complexity is not a secondary issue. It’s a structural one. Until we address it by reducing unnecessary work, improving visibility, and supporting the people doing the work, rural hospitals will continue to operate at a disadvantage they can’t overcome.

About Matt Seefeld
Matt Seefeld, CEO of MedEvolve, is a healthcare executive with more than 25 years of experience in the assessment, design, and implementation of process improvement programs and technology development for the healthcare revenue cycle. He focuses on reducing administrative complexity and improving operational performance across healthcare organizations.

What You Should Know

• A new survey by the Deloitte Center for Health Solutions reveals that 62% of diagnostics manufacturer executives believe future growth depends entirely on adopting a business-to-business-to-consumer (B2B2C) operational model.
• The research highlights an immediate strategic disconnect: while providers rank test ordering as their single greatest clinical friction point, manufacturers mistakenly over-index on results interpretation as the primary challenge.
• Rising consumerization is reshaping the market landscape, with 76% of provider respondents stating that consumer- and patient-initiated testing demands will fundamentally alter diagnostics over the next three years.
• Interoperability remains an acute infrastructure hurdle; 74% of healthcare providers admit that their current database systems are completely disconnected and un-integrated across the end-to-end diagnostic journey.
• To survive the expansion of home diagnostics and wearables, manufacturers must embed AI natively within EHR workflows, automate prior authorizations, and deliver highly personalized, visual data context directly to consumers.

The B2B2C Migration: Why Diagnostics Manufacturers Must Shift from Product Vendors to Workflow Partners

The global diagnostics manufacturing sector is currently navigating an aggressive, multi-directional market disruption. On the consumer front, patients are rapidly adopting sophisticated, distributed health tools—utilizing virtual healthcare portals, direct-to-consumer (DTC) self-ordered testing, digital health applications, and advanced wearable sensors to independently track, interpret, and manage their baseline biological data. Concurrently, traditional healthcare providers—encompassing independent commercial laboratories, hospital systems, and imaging facilities—are under intense operational pressure to deliver faster, highly streamlined, and deeply personalized clinical experiences or risk permanently losing market share to agile, consumer-focused tech entrants.

While these shifts point directly toward a data-driven, consumer-centric, and personalized ecosystem, legacy clinical models will not vanish overnight. Traditional healthcare providers still generate the dominant share of core revenue for diagnostics manufacturers. The pressing strategic question for corporate boards is no longer how to bypass the traditional system, but how manufacturers can actively equip their core provider customers to survive and compete in a consumer-driven marketplace.

To assess industry readiness for this transition, the Deloitte Center for Health Solutions conducted parallel surveys of 50 diagnostics manufacturer executives and 50 healthcare provider executives, supplemented by 20 in-depth interviews with industry leaders. The findings reveal a stark reality: 62% of manufacturers recognize that future growth hinges on a next-generation B2B2C blueprint. However, deep structural disconnects in stakeholder engagement, workflow integration, and consumer personalization threaten to stall this critical evolution.

Dissecting the Three Core Provider Disconnects

Before manufacturers can capture the emerging B2B2C opportunity, they must re-engineer how they interact with their primary healthcare provider customers. Deloitte’s research exposes three critical disconnects where manufacturer strategies are misaligned with localized provider realities:

1. The Problem-Solving Disconnect: In the study, providers explicitly identified test ordering as the single heaviest friction point in their daily clinical pipeline. Manufacturers, conversely, focused their innovation efforts on result interpretation. To bridge this gap, forward-looking manufacturers must look past physical diagnostic kits to expand their offerings into automated software and workflow services.
2. The Stakeholder Disconnect: Surveyed manufacturers stated that their primary account contacts remain hospital procurement offices and channel partners—the traditional buyers who execute contracts. Providers, however, counter that the individuals who actually command clinical adoption and long-term utilization are ordering clinicians, lab directors, and service-line leaders. Manufacturers are over-investing in procurement relationships while under-investing in the clinical stakeholders who dictate actual product adoption.
3. The Engagement Disconnect: Providers heavily prioritized peer-to-peer clinical education, medical conferences, and intuitive, digital self-service web portals to research technology independently. Manufacturers, by contrast, continue to deploy high-frequency field sales teams, an outreach method that several provider interviewees described as overly frequent and lacking clinical value.

Harnessing Platform-Based AI and Interoperable Moats

The urgency to fix these engagement gaps is accelerating. 76% of provider respondents state that consumer-initiated testing demands will radically transform the diagnostics footprint over the next three years. Furthermore, 92% of providers are already actively offering or exploring patient-initiated testing pathways, compared to just 70% of manufacturers—proving that frontline clinics are absorbing the brunt of changing consumer behaviors.

As testing decentralizes into the home and retail environments, providers are becoming nodes in a distributed care network. Consumers expect visual, contextually clear results that move past raw numbers to outline actionable next steps. To help providers scale this level of personalization, manufacturers must prioritize comprehensive data and workflow integration. Currently, the tech stack is highly fragmented: 74% of providers report that their backend systems are entirely un-integrated across the end-to-end diagnostic journey.

This data isolation creates a significant entry point for platform-integrated Artificial Intelligence. Rather than deploying isolated, standalone algorithms, the competitive advantage belongs to integrated platforms that connect data across revenue cycles, automated prior authorizations, and native EHR workflows. 66% of provider executives state that personalized workflow integration will be exceptionally important over the next three to five years. Manufacturers that embed their testing infrastructure within these automated loops can capture a continuous, longitudinal view of patient health extending far beyond the clinical encounter. Those that resist this integration risk being relegated to interchangeable commodity test vendors with zero visibility into consumer behavior and no influence over future diagnostic decisions.

Every year, there are roughly 33.5 million hospital admissions, 155 million emergency department visits, and hundreds of millions of outpatient encounters across the United States. At the same time, healthcare spending has reached $4.9 trillion annually. When patient data, especially for such a large number of healthcare consumers, is fragmented across multiple applications, vendors, and systems, the effect is exponential. It is multiplied across every encounter, every workflow, and every decision, impacting not only quality of care and the patient experience, but also hospital performance and the bottom line. 

As a result, EHR interoperability is becoming central to how healthcare organizations think about sustainability, efficiency, and care delivery at scale. While industry conversations have traditionally focused on interoperability as only a regulatory requirement or technical milestone, the shift is becoming more apparent. 

This shift is also reflected in how healthcare leaders are approaching their technology environments. In a 2026 CHIME survey, nearly 90% of healthcare CIOs reported that vendor consolidation is a priority within their interoperability strategy. There is broad alignment around the need to simplify environments and reduce fragmentation. At the same time, interoperability is still often being approached as something layered onto existing systems rather than a capability built into their EHR core. 

Shifting Interoperability from Project to Infrastructure

Interoperability isn’t a new need or a new concept; for years, health system IT departments have advanced compatibility through interfaces, integrations, and incremental improvements. This approach wasn’t wrong; in fact, it has enabled meaningful progress for more than a decade, and has expanded the ability for healthcare organizations to exchange data across systems. But, each additional connection requires implementation, ongoing maintenance, governance, and costs. Over time, these connections and improvements have also introduced significant complexity to systems that can and should be simple. 

That complexity has caused many health IT leaders to shift how they think about interoperability to the point that it is no longer viewed solely as a series of projects that somehow connect together. Instead, it is increasingly viewed as a continuous capability that must both be sustained and scaled. Despite this new focus on interoperability, only 16% of CHIME respondents reported that interoperability is capable through the core of their EHR system, highlighting the gap between strategic intent and architectural reality.  

Data Says That the Roadblocks are Resulting in Dollar Signs

This dynamic isn’t about knowledge, skill, institutional support, or desire; instead, data points to cost. Healthcare leaders report that the financial burden of integration and ongoing maintenance remains a primary barrier to achieving interoperability at scale, and more than 47% of CHIME respondents cited cost as their biggest obstacle. Even as organizations invest in new technologies and standards, the underlying model can make it difficult to achieve progress without adding complexity. 

Foundational Challenges are Keeping Interoperability at Bay

Cost may be the primary barrier slowing down interoperability for most health IT leaders, but it is  not the only one. The foundational challenges of interoperability have remained consistent and it shows in the data. Vendor unwillingness and delays impact more than 42% of CHIME respondents working towards interoperability, lack of standardization stands in the way for 26% and IT staffing and internal resource constraints block the path for another 37%. In addition to these challenges, 47% of CHIME respondents ranked data silos and system fragmentation as a top concern when it comes to achieving interoperability.

These are not new issues, nor are they the result of a lack of effort. Instead, they reflect the way healthcare technology has evolved over time, typically in response to immediate needs rather than long-term architectural alignment with the hospital’s needs and goals. 

The impact of these challenges becomes clearer when viewed at scale. Across millions of patient encounters each year, fragmented data can contribute to repeated testing, delays in information access, and increased administrative burden. These all contribute to increased financial pressure over time, a pressure made worse by the mounting cost of uncompensated care.  

Since 2000, hospitals have provided nearly $745 billion in uncompensated care. While many factors contribute to this, inefficiencies tied to disconnected systems remain monumental to the broader equation. 

Interoperability as an Enabler of Outcomes

Looking past these challenges, the direction forward is increasingly clear, Interoperability is about connecting systems to enable positive outcomes. In the CHIME survey, 58% of CIOs cited improved care coordination as the most important potential result of interoperability, while 37% pointed to patient safety improvements and cost reduction.

When interoperability functions as intended, it becomes part of the background, a silent partner that seamlessly supports the end goal for all clinicians and patients; the right data in the right hands at the right time. Clinicians need access to complete and timely information. Organizations can reduce duplication and streamline workflows. Patients experience more coordinated care across settings. In this way, interoperability facilitates essential infrastructure of all clinical decisions and outcomes.

The industry has already made significant progress: standards continue to evolve, technologies are advancing, and strategic alignment is stronger than it has been in the past. The next phase of interoperability builds on this progress by establishing these advancements as the foundational core of the EHR and supporting clinical delivery at the point of care. 

As healthcare continues to evolve, the alignment between strategy and architecture will play an increasingly important role. Interoperability is required to be embedded, supported, and sustained as part of the core system. That is where the full value can be realized across the entire care continuum.

About Sandra Johnson

As Senior Vice President of Client Services, Sandra Johnson is responsible for delivering healthcare IT solutions and managing the customer experience to ensure CliniComp’s technology is continuously evolving to meet the changing needs within the healthcare community. Sandra oversees all aspects of the customer lifecycle including account & project management, application support, clinical services, cybersecurity, and learning & development for our global customer base.

What You Should Know

• Wearable technology leader ŌURA has officially launched Oura Ring 5, re-engineering its mechanical and electrical architecture to create a device that is 40% smaller than its predecessor.
• Moving past passive metrics, the latest software update introduces Health Radar, a clinical expansion featuring background tracking of blood pressure signals, nighttime blood pressure drops, and 30-day rolling respiratory data.
• For individuals managing anti-obesity medications, the application debuts GLP-1 Insights, unifying dosing schedules, subjective side-effect metrics, and weight profiles with continuous sleep and biometric tracking.
• The company is building out a connected care infrastructure by integrating an on-demand, AI-enabled clinical triage layer via Counsel Health, allowing users in 43 U.S. states to text licensed physicians directly inside the app.
• Oura Ring 5 is constructed from non-allergenic titanium with an extra-strong physical vapor deposition scratch coating, retails starting at $399, and begins shipping globally on June 4, 2026.

Beyond Awareness to Action: Oura Ring 5 Unveils Proactive Health Radar and Connected Care Pathways

The global consumer wearable sector has reached a critical structural turning point. For the past decade, the market has been dominated by wrist-worn smartwatches that primarily functioned as descriptive biometric scorecards—tracking raw daily step counts, capturing broad heart rate zones, and archiving basic sleep metrics. However, as consumers grapple with complex chronic conditions, rising healthcare costs, and expanding insurance navigation hurdles, the demand for technology has fundamentally shifted.

Modern users are no longer satisfied with passive digital tracking that simply tells them they slept poorly or exercised frequently. They demand proactive, predictive intelligence capable of converting raw biometric noise into structured, clinical systems of action. Furthermore, as behavioral medicine increasingly merges with medical weight management therapies, the hardware housing these insights must evolve past bulky screens to deliver highly discreet, continuous, and lifestyle-integrated forms.

To dismantle the traditional boundaries separating consumer electronics from proactive health optimization, smart ring pioneer ŌURA has announced the global launch of Oura Ring 5. Built on twelve years of categorical engineering, the device combines a massive architectural miniaturization with a comprehensive ecosystem of clinical health records, real-time activity tracking, and on-demand physician integration.

Miniaturizing the Pulse: The Re-Engineered Architecture

The core engineering triumph of Oura Ring 5 centers on a comprehensive overhaul of its underlying hardware parameters, achieving a 40% reduction in total size compared to Oura Ring 4 to establish itself as the world’s smallest smart ring. To construct this thinned, lightweight, non-allergenic titanium silhouette without sacrificing structural data accuracy, ŌURA re-engineered its mechanical, electrical, optical, and battery geometries from the ground up.

The ring’s upgraded biometric signal layer integrates low-profile sensor domes for optimal skin contact, high-efficiency LEDs, and twelve dedicated signal pathways. This advanced hardware baseline guarantees a clean, continuous optical reading across diverse finger structures and skin tones. Crucially, the finger remains the optimal location for consumer biometric sensing. The local digital arteries deliver a clear pulse signal that is up to 100 times stronger than signals captured at the wrist, enabling Oura Ring 5 to track real-world cardiovascular indicators with a level of precision that legacy smartwatches cannot replicate.

Pricing & Availability

Crafted to withstand uninterrupted daily wear, the device features an extra-strong physical vapor deposition (PVD) coating for advanced scratch resistance, along with a dust- and waterproof rating up to 100 meters. Pre-orders open immediately, starting at $399 for base finishes (Silver and Black) and $499 for premium finishes (including modern Gold and Deep Rose), with global shipping scheduled to commence on June 4, 2026.

Activating the Health Radar: Blood Pressure Signals and Sleep Regularity

Alongside the miniaturized hardware, ŌURA has rolled out a sophisticated suite of preventative clinical software applications. Leading this transformation is Health Radar, a proactive monitoring matrix engineered in collaboration with more than 40 in-house medical doctors and Ph.D. scientists. Health Radar continuously analyzes background biometric signals to surface anomalous physiological patterns long before they escalate into acute medical issues.

The primary clinical focus of the radar is the trackable measurement of Blood Pressure Signals. Cardiovascular strain is notoriously invisible during daily activity, obscured by stress, movement, and caffeine consumption. Oura Ring 5 solves this tracking dilemma by monitoring blood pressure patterns during sleep, a critical resting state when the human cardiovascular system outlines its truest condition. The app monitors nighttime dipping trends—alerting users when their biometrics point to a persistent lack of nocturnal blood pressure reduction, which serves as a vital early indicator of long-term cardiovascular risk. Users can also log manual cuff measurements directly into the interface to align real-world diagnostic numbers with their ongoing physiological data streams.

To further expand its sleep and respiratory diagnostics, the platform integrates a 30-day rolling analysis of Nighttime Breathing disturbances. To transition these insights into direct medical care, ŌURA has partnered with home-health respiratory giant ResMed. Members documenting elevated respiratory interruptions can instantly access trusted diagnostic education, complete validated sleep assessments, and connect directly with independent medical professionals to evaluate potential home care pathways.

Hardwiring Care Delivery and GLP-1 Adherence Tools

Oura Ring 5 is positioning itself to serve as a primary, interoperable data link for connected care. Through its newly deployed Health Records module, the platform merges clinical data with daily wearable signals into a single, privacy-first longitudinal record. In the United States, members can securely sync eligible provider portals to import verified diagnoses, active medications, lab metrics, and allergen profiles. This function delivers a direct preview of ŌURA’s commitment under the Centers for Medicare & Medicaid Services (CMS) Health Technology Ecosystem pledge to seamlessly link interoperable clinical infrastructure with everyday biological signals.

To bridge the gap between algorithmic insight and direct medical intervention, the app has embedded an on-demand, AI-enabled clinical triage layer in partnership with Counsel Health. The integration combines specialized medical language models with a dedicated network of licensed physicians. Members can ask complex health questions and receive clinical guidance from certified providers within minutes natively inside the app, a capability launching across 43 U.S. states.

Concurrently, the platform has launched GLP-1 Insights to address the rapid rise of metabolic medication self-management. Instead of forcing patients to manage their therapy across disconnected apps, Oura integrates dosing records, user side-effect logs, and weight tracking directly with core biometric signals like sleep, readiness, activity, and metabolic stress. Through subsequent Lab Uploads, members can import blood biomarker results straight into the app, positioning hard lab data alongside continuous wearable trends for an exhaustive view of metabolic health.