Healthcare is built on patient engagement. But when that engagement breaks down, patients don’t get the care they need, and regional practices are hit with the dual loss of time and money.
Patient no-shows and late cancellations remain one of the biggest and most persistent revenue leaks for regional practices. Each year, no-shows cost U.S. healthcare providers roughly $150 billion. Regional practices that lack the scale of larger health systems are hit especially hard by this loss of money and efficiency.
But no-shows don’t have to be a consistent revenue drain. Regional practices are redefining the patient experience by adopting automated, two-way communication systems. These systems can boost patient engagement, save practices time and money, and ensure patients get the care they need.
Old Systems, New Expectations
No-shows often come down to unmet patient expectations. So much of our world has become seamless. Think about the last time you booked a flight or shopped for a product online. The process is easy and intuitive. Healthcare systems, however, have not kept pace with changing expectations.
We see this in a national no-show rate of 18%. Patients expect personalized, streamlined experiences, but healthcare communication systems don’t meet these expectations.
According to research, traditional healthcare communications fail patients in three important ways. First, patients feel overwhelmed by communications, yet they still often don’t get the specific information they need. Next, patients feel frustrated when they have to call in response to an appointment reminder. And finally, patients feel messages are not meant for them personally. The same research has shown long waiting times, seeing different doctors for appointments, transportation issues, and fear of hospitals are among the most common reasons for no-shows. Other reasons include scheduling conflicts and miscommunication with medical staff.
The bottom line is that healthcare is struggling to keep up with modern patient expectations. If your cellphone carrier can send personalized communications when you need them the most, why can’t your doctor?
This is why many regional practices are turning to automated communication systems to close the gap between patient expectations and experience.
Automate Engagement, Boost Appointment Adherence
We’ve seen the results when healthcare practices shift from one-way reminder calls and manual follow-ups to two-way, automated, multi-channel communications. When regional practices adopt an automated, proactive approach to patient communication, appointment adherence improves and no-show numbers drop, strengthening patient-provider connections. These communication systems tailor reminders to individual patients using their preferred language and communication channel.
The results are clear. Studies show that telephone reminders can reduce no-shows from 21% to 7%. Reminders are even more effective when they are personalized and delivered when and how individual patients need them the most.
Research has also shown how practices can enhance patient reminders by mixing up content and format, simplifying information, and including specifics such as clinic locations and contact information. Most importantly, the study recommends personalizing reminders to individuals and letting patients control the reminders.
AI-powered engagement systems can help regional practices reach patients in their preferred language using their preferred channel, whether that is a text, phone call, or email. Automated systems also let patients cancel, ask questions, or reschedule at their convenience, reducing the communication barriers between patient and practice.
Automated patient management systems are an efficient way for regional practices to give patients exactly what they need to keep their appointments. Reminders that include specific information about tests or procedures can help alleviate anxiety that cause no-shows. Data analysis can also help practices tailor messages with specialized information for patients who might need a greater level of engagement to keep appointments.
Patients aren’t the only ones benefiting from automated engagement. Staff no longer have to spend valuable time making reminder calls, leaving voicemails, or contacting patients after a no-show. They are free to focus on the more complex parts of their jobs best suited to their training and expertise.
Stronger Patient Engagement, Better Care for Everyone
Reducing no-shows creates a positive ripple effect across regional practices. When more patients keep their appointments, they get the care they need. When practices’ schedules are more stable, they can see more patients, increase efficiency, and save money too often lost to no-shows. Boosting patient engagement with timely, personalized reminders breaks down barriers between patients and practices, benefiting both.
Simply put, if a patient gets the information they need when and how they need it, if they can seamlessly confirm and reschedule, they are more likely to keep that appointment. And in healthcare, that is a win-win.
The Centers for Medicare & Medicaid Services (CMS) is taking action, it announced, to protect Medicare beneficiaries and taxpayer dollars through implementation of a six-month, nationwide data-driven moratoria on new Medicare enrollment for hospices and home health agencies (HHAs).
The moratoria will allow CMS to temporarily halt the influx of new providers into these high-risk categories—a key source of fraudulent activity. Today’s move continues the Trump Administration’s crackdown on fraud, waste, and abuse in the Medicare program by stopping improper billing and preventing bad actors from entering the system.
“We’ve seen systemic and deeply troubling fraud in the hospice and home health space, with bad actors exploiting some of our most vulnerable Medicare patients and stealing money from the American taxpayer,” said CMS Administrator Dr. Mehmet Oz. “Today we’re shutting the door on fraud—preventing new bad actors from entering Medicare while we aggressively identify, investigate, and remove those already exploiting them. This is about protecting patients, restoring integrity, and safeguarding taxpayer dollars.”
During the six-month moratoria, CMS will intensify targeted investigations, deploy advanced data analytics, and accelerate the removal of hospice and HHA providers from the Medicare program that are suspected of committing fraud. This nationwide approach will also eliminate the ability of bad actor operators to evade detection by simply shifting across state lines. In addition, the moratoria will apply to all applications for initial Medicare enrollment and certain changes in majority ownership, which are frequently used to obscure control by bad actors. The moratoria will not impact current enrollments, and existing providers can continue to deliver services to Medicare beneficiaries.
CMS’ announcement follows its earlier notice of a similar moratorium to prevent fraudulent Medicare billing by certain durable medical equipment, prosthetics, orthotics, and supplies (DMEPOS) companies. With three separate moratoria now in place, CMS has taken some of the most significant fraud prevention actions in the agency’s history.
The moratoria are part of CMS’ ongoing efforts to stop fraud before it starts, using data-driven prevention and real-time enforcement as part of a coordinated federal approach. Recent CMS action has included the suspension of payments to 773 hospices and 23 HHAs suspected of fraud in Los Angeles alone, representing $70 million in suspended funds thus far.
Additional CMS work to crush fraud in the hospice and HHA areas has included:
Revoking or deactivating hundreds of hospices and HHAs engaged in improper or fraudulent activity;
Conducting nationwide hospice site visits to verify operations and identify suspicious activity;
Heightened oversight of newly enrolled Medicare hospice providers in states with elevated fraud risk, including Arizona, California, Georgia, Ohio, Nevada, and Texas;
Launching a new, publicly available hospice scoring system to increase transparency and identify providers with troubling patterns of utilization, quality, or compliance;
Implementing enhanced enrollment screening measures for high-risk HHAs, including site verification of reported practice locations and fingerprinting-based background checks; and
Expanding a demonstration project that allows pre- and post-claim review of HHA claims in Florida, Illinois, Oklahoma, Ohio, North Carolina, and Texas to stop improper payments before they occur.
Additional information on the Hospice and Home Health Agency moratoria can be found via the Federal Register at: https://www.federalregister.gov/
New survey data from the American Medical Association (AMA) show physicians are pervasively skeptical that meaningful change will occur—reflecting years of similar commitments that have failed to produce lasting improvements.
In June 2025, after successful engagement from the Trump administration to address widespread concerns from patients and physicians, roughly 60 health insurers pledged to streamline, simplify, and reduce prior authorization requirements, with implementation deadlines spanning 2025 through 2027. Ahead of the first major deadline, the AMA surveyed 1,000 practicing physicians to assess whether these commitments are likely to deliver meaningful improvements for patients and physicians.
Physician skepticism is grounded in experience. As part of the 2025 pledge, insurers committed to ensuring that all medical necessity denials would be reviewed by a licensed and qualified clinician. Yet only one in four physicians (24%) report that such reviews are consistently conducted by appropriately qualified clinicians. In addition, just 16% of physicians who participate in peer-to-peer reviews say the health plan representative often or always has the appropriate qualifications.
“Physician trust in voluntary insurer pledges is deeply eroded after years of unfulfilled promises,” said AMA President Bobby Mukkamala, M.D. “Physicians are especially frustrated when so-called peer-to-peer reviews are conducted by individuals who lack the appropriate clinical expertise to evaluate a patient’s care. When only a third of physicians expect meaningful impact—and so few report that health plan reviewers are appropriately qualified—it highlights a credibility gap that won’t be closed with vague or partial measures. Rebuilding trust will require sustained, transparent, and measurable action to streamline prior authorization and keep it clinically focused and patient-centered. Anything less risks reinforcing the skepticism these pledges were meant to address.”
The AMA survey shows how much work insurers still must do and highlights ongoing concerns that prior authorization delays care, disrupts treatment, and harms patient outcomes.
Patient Harm — More than one in four physicians (26%) report that prior authorization has led to a serious adverse event, including hospitalization, permanent impairment, or death.
Delayed Care — More than nine in 10 physicians (95%) say prior authorization delays access to necessary care.
Disrupted Care — Nearly four in five physicians (79%) report that patients abandon treatment due to authorization challenges.
Poor Outcomes — More than nine in 10 physicians (92%) say prior authorization negatively affects clinical outcomes.
Prior authorization also continues to place significant strain on physician practices, driving high volumes of requests and denials, consuming clinical and administrative time, and contributing to widespread burnout. As administrative demands intensify, resources are increasingly diverted from patient care to manage an inefficient process.
Added Burden — Physicians complete an average of 40 prior authorizations per week, and nearly one in three (32%) report that requests are often or always denied.
Physician Burnout — More than nine in 10 physicians (94%) say prior authorization contributes to burnout.
Denial Trend — Three-quarters of physicians (74%) report that denials have increased over the past five years, and six in 10 express concern that augmented intelligence (AI) may further increase denial rates.
Diverted Time and Resources — Prior authorization consumes an average of 13 hours of physician and staff time each week, and two in five physicians (40%) employ staff dedicated exclusively to prior authorization tasks.
Beyond its impact on patients and physician practices, prior authorization also drives inefficiencies and unnecessary costs across the health system.
Wasted Health Resources — More than four in five physicians (88%) report that prior authorization increases overall health care utilization, contributing to waste rather than savings. Physicians cite ineffective initial treatments (75%), additional office visits (73%), urgent or emergency care (47%), and hospitalizations (32%) as consequences of prior authorization requirements.
Physicians also report consistently high administrative burden with prior authorization across all major health insurers. UnitedHealthcare (75%) tops the ranks for “high” or “extremely high” burden, followed by Humana (65%), Anthem/Elevance (61%), Aetna (61%), Cigna (59%), and Blue Cross Blue Shield (56%).
The AMA continues to work on every front in support of prior authorization reforms that prioritize patients’ access to necessary care and reduce administrative burdens for physicians. The AMA looks forward to continuing to work with the Trump administration, Congress and health insurers on this critical issue. To learn more about prior authorization challenges experienced by patients, physicians, and employers, go to FixPriorAuth.org.
Healthcare organizations have rapidly adopted artificial intelligence across clinical decision support, diagnostics, revenue cycle management, and operational systems.
AI tools are now embedded across many hospital environments, promising better clinical outcomes, decreased administrative burden, and smarter use of healthcare data.
But as adoption accelerates, oversight continues advancing rapidly.
Regulators are increasingly scrutinizing how AI is developed, validated, and deployed in healthcare, making AI governance a new compliance focus for health system leaders. Healthcare executives and boards must urgently manage the operational, legal, and regulatory obligations that accompany AI adoption.
AI Is No Longer Solely an IT Decision
Historically, new technologies in healthcare have often been treated primarily as IT decisions. Artificial intelligence changes that dynamic. AI systems influence clinical decision making, patient risk scoring, workflow prioritization, and reimbursement. Their effect goes beyond technology deployment to clinical accountability along with regulatory oversight.
This shift demands comprehensive oversight.
Effective AI oversight now demands coordination across compliance, legal, clinical leadership, risk management, and IT teams. Health systems must begin asking foundational questions about the algorithms they deploy:
How was the model trained and validated?
What data sources were used, and are they representative of the patient population?
How frequently should models be monitored or recalibrated?
Who is accountable if AI recommendations influence clinical outcomes?
Without formal governance structures in place, health systems risk deploying tools they cannot fully explain or defend during regulatory review.
Regulators Are Catching Up
Oversight advances alongside AI adoption. In the United States, the FDA has already begun developing guidance frameworks for AI-enabled medical software and adaptive algorithms, signaling greater regulatory attention to the lifecycle management of AI systems.
This signals accountability for algorithm development, testing, monitoring, and documentation. This means AI systems may require similar documentation, validation, and performance monitoring as medical devices. Many hospitals lack readiness for this operational rigor.
The Hidden Operational Workload
One of the most common mistakes health systems make is underestimating the operational effort required to govern AI effectively. This includes committing time to oversight, establishing new processes, and allocating resources to promote ongoing compliance and risk mitigation.
Deploying an algorithm is only the starting point. Responsible AI programs require regular oversight, including:
Algorithm validation and revalidation
Bias monitoring and performance tracking
Documentation of model training data and updates
Clinical review and oversight structures
Audit trails that support regulatory inspection
Each item needs dedicated governance and clear accountability. Without them, AI meant to improve efficiency can add complexity and risk.
AI Is Becoming Part of Clinical Infrastructure
Many healthcare leaders still view AI as a pilot initiative or innovation program. Increasingly, however, AI tools are becoming embedded within everyday clinical processes. If algorithms help determine triage priorities, diagnostic interpretation, or patient risk stratification, they effectively become part of the organization’s clinical infrastructure.
This reality heightens the stakes.
Boards and executives are realizing AI oversight is fundamental. As systems affect care and decisions, governance becomes a strategic and safety-critical responsibility.
Preparing for the Next Phase of AI Adoption
The next phase of AI adoption in healthcare may be defined less by technological capability and more by governance maturity.
Health systems that establish structured oversight programs early will be better able to scale innovation while continuing regulatory readiness.
Essential steps include:
Setting up formal AI governance committees that include clinical, compliance, legal, and IT leaders
Creating model validation and lifecycle management processes
Deploying monitoring tools to evaluate accuracy and bias
Developing documentation standards that support regulatory review
Ensuring executive leadership and boards understand their oversight responsibilities
Organizations that move from reactive compliance to forward-looking governance will be better prepared for the emerging regulatory landscape in healthcare AI. AI is growing essential to healthcare delivery. Governance must evolve accordingly. Treating AI oversight as core compliance, not solely a technical matter, is vital to health innovation.
Medication review is a routine part of long-term care. So, why isn’t deprescription more common? The reality is that turning standard reviews into meaningful change is difficult. Complicated medication regimens typically don’t change until there is problem—a safety issue, a non-adherence problem, cascading side effect prescriptions, or an adverse reaction.
Residents often arrive with multiple chronic conditions, a long list of accumulated prescriptions, and treatment plans shaped by different providers spread across various networks. As those layers build, long-term care facilities are faced with a new polypharmacy patient, with concurrent use of five or more medications, with a very real need to review the overall treatment plan for safety and sustainability in practice.
To be clear, polypharmacy is not an automatic sign of poor care. Residents may need a multi-drug prescribing approach to manage cardiovascular disease, diabetes, pain, depression, sleep issues, or cognitive decline and another set to address side effects of the medications. Trouble starts when prescription lists expand without enough review, coordination, or follow-up. At that point, prescriptions intended to support residents can instead put their health at risk.
Older adults are particularly vulnerable to the medication burden effect. Age-related changes in metabolism, kidney function, and body composition alter how the body metabolizes drugs. Frailty, dementia, and swallowing difficulties can add more complications. Layer several therapies together, and the risk of interactions, duplication, and adverse drug events rises quickly.
Complexity Builds Faster in Resident Care Settings
Pharmacists and prescribers know what to look for. They are trained to spot therapeutic duplication, unnecessary layering, medication cascades, and therapies that may raise the risk of confusion, side effects, fall risk, or poor adherence. The problem is that awareness alone doesn’t reduce the day-to-day burden of treatment.
A 2024 cross-sectional study in BMC Geriatrics of 67,531 older adults using facility-based care services found an average of seven prescriptions per patient, with polypharmacy and potentially inappropriate drug treatments frequently observed across the study population. Those findings show how quickly medication burden can become a safety issue and a day-to-day management challenge.
For caregivers, that creates a practical problem. A treatment plan may be clinically sound on paper, yet still fail if it becomes too costly, complex, or difficult to maintain. When that happens, the effects can manifest as missed doses, avoidable complications, greater staff involvement, and added strain on residents and families. Identifying those issues is only the first step. The more important challenge is converting that insight into completed, provider-approved changes.
Addressing Prescription Drug Cost Earlier Improves Follow-Through
A 2024 study in the American Journal of Health-System Pharmacy found that lower-cost alternatives accounted for 67.2% of real-time prescription benefit alerts, and prescribers selected those alternatives 32% of the time. When an alternative was chosen, prescription fill rates rose 15%, and patients saved an average of $27.77 per month on copay costs.
Affordability becomes much easier to manage when the prescribers are involved and can avoid shifting the burden to patients. For long-term care organizations, that has clear implications. Stronger support models help pharmacists and prescribers identify lower-cost options, reduce unnecessary duplication, and complete provider-approved changes earlier in the process.
The most effective support gives physicians a clearer path to act on optimization opportunities while preserving their clinical judgment. Technology that surfaces lower-cost alternatives, supports medication switching, offers deprescribing opportunities, and flags duplications helps physicians close the loop on standard medication review to meaningful change. And more importantly, the support works best when it fits within their usual clinic workflows.
Where Better Medication Management Begins
Safer medication management depends on turning reviews into timely, provider-approved changes. When care teams have better support to evaluate clinically appropriate alternatives early and act before complexity builds, they’re in a stronger position to reduce burden, support adherence, and protect residents from avoidable harm. In long-term care, medication review is only the starting point. What matters is whether this review leads to change.
By Michelle Barlow, RN, BSN, Director of Product Management Home Health, Homecare Homebase.
Home-based care clinicians are under growing strain, with recent reports showing that 40% of nurses intend to leave the workforce by 2029. Time lost on redundant administrative tasks only adds to this strain.
Care providers spend significant bandwidth on ineffective documentation, with 79% reporting time lost to unproductive charting, time that could otherwise be spent with patients.
In home-based care, time spent on inefficient administrative work can lead to reduced visits, delayed appointments, and fewer patients reached. As agencies work to relieve that burden, many are looking for practical ways to return time to clinicians without disrupting care delivery
Emerging software designed for healthcare, such as AI-driven clinical documentation platforms, can offer a path forward. Still, providers in highly regulated settings remain cautious about adopting tools that interact with sensitive patient information. In home-based care, adoption will depend not just on what AI can do, but on whether it is implemented with the right safeguards. Home-based care agencies should therefore implement AI that prioritizes compliance and clinician judgment, while reducing documentation burden.
Reimagining Documentation to Restore Time for Care
In home-based care, workforce shortages are a contributor to access to care limitations. Since documentation can play a significant role in clinician burnout, integrating AI documentation tools into an agency’s current software stack may help providers prioritize care and open up more capacity to help new patients. Doing so may help avoid an infrastructure overhaul that would further disrupt care delivery.
When effectively layered, these systems can save up to 30%-50% of a nurse’s bedside documentation time by generating draft language or structured suggestions for the Outcome and Assessment Information Set (OASIS) responses based on contemporaneous clinical inputs. AI can also play a constructive role in the revenue cycle, identifying missing claim information and automating eligibility, freeing more time for hands-on patient care.
Yet, there are certain concerns around whether AI will draft documentation for clinician review or independently determine a response. The former approach, where the clinician remains responsible for evaluating, editing, and confirming the final record, is what is needed in today’s healthcare environment to maintain high-quality, individualized care as well as regulatory compliance. Without this emphasis on accountability, automation will lack effectiveness.
Balancing Automation with Accountability
Given patient privacy concerns and stringent HIPAA regulations in decentralized environments, many agencies hesitate to adopt AI that interacts with clinical record systems. Organizations may delay pilots or even pause the adoption of low-risk tools altogether due to regulatory concerns, which can stall the use of workflow-support tools that could ease documentation burden. To address these concerns, agencies should implement solutions that focus on compliance. These approaches should include deliberate safeguards that promote transparency and preserve clinician oversight.
AI in home-based care must support clinician-led, human-in-the-loop processes to maintain compliance. This often looks like care providers monitoring AI-generated summaries and outputs to determine whether they are consistent with source data, suppress unsupported inferences, and avoid hallucinations not grounded in clinical records. Providers are expected to evaluate the suggested documentation content, make any necessary modifications, and confirm the final response.
These systems should also be based on interoperable, clinically meaningful data points. In home-based care, timely visibility into events such as hospital admissions, discharges, and other material changes in patient status. Without that access, AI may be limited in its ability to support preventive intervention or care coordination. At the same time, agencies need to ensure patient data is handled in ways that protect privacy and support compliance, while reducing biased recommendations and security breaches. When these conditions are met, organizations can help improve output accuracy, strengthen audit defensibility, and maintain consistency across records, all without compromising clinician judgment.
Putting Clinicians First in the Age of AI
In home-based settings, patients are medically fragile and reliant on coordinated assistance. Even slight disruptions in timing or service could trigger avoidable hospitalization. Home-based agencies cannot afford the effects of staffing shortages caused by the nurse burnout epidemic. To elevate patient care, home-based organizations should prioritize integrating solutions that ease administrative burden where appropriate and return time to the clinicians delivering care.
Integrating these intelligent systems is not about replacing clinical judgment, but about supporting agencies with tools that reduce unnecessary documentation burden and help reduce burnout. By implementing human-in-the-loop practices alongside AI outputs, home-based agencies can better prioritize provider well-being and, in turn, help patients receive the care they need.
Revenue risk no longer begins and ends with managing denials. It now touches every stage of the revenue cycle — from documentation, charge capture, and coding to billing and denials management — and healthcare organizations relying on reactive, manual, and siloed oversight approaches are paying the price. In an environment defined by financial pressure, heightened regulatory scrutiny, and increasingly AI-powered payer behavior, reactive approaches are no longer enough.
Today, MDaudit, an award-winning, AI-powered continuous risk-monitoring platform. launches “Revenue Integrity Redefined,” a campaign that charts a clear path forward for revenue cycle leaders navigating today’s financial uncertainty. The campaign launches with a flagship video and a suite of supporting resources, including an assessment tool that helps organizations benchmark their revenue integrity maturity across denial prevention, audit readiness, cross-functional alignment, and technology enablement.
Why It Matters: The Stakes Have Never Been Higher
The financial pressures facing healthcare providers are not abstract — they are measurable, accelerating, and compounding. MDaudit’s 2025 annual Benchmark Report documents the scale of the challenge:
Coding-related denials increased by as much as 26%
Medicare Advantage average denied amounts rose 20%
Medical necessity and RFI denial amounts increased by 70%
Payer audit volume and dollars at risk rose 30%
Initial response times for claims take more than a month across all claim types
These trends reach far beyond the revenue cycle team. They affect operating margins, forecasting accuracy, workforce planning, and capital investment decisions — making revenue integrity a C-suite and board-level concern.
Ritesh Ramesh
“Denials are rising, payer audits are expanding, and reimbursement timelines are longer than ever,” said Ritesh Ramesh, Chief Executive Officer of MDaudit. “The weight these realities place on everyone who touches the revenue cycle is enormous. The path forward is integrity in compliance documentation, coding, and billing practices, enabled by real-time data and AI-powered technologies, and trusted partnerships chosen to support revenue cycle teams.”
Compounding these pressures is an accelerating AI arms race between payers and providers. Payers are automating denials faster than ever, while providers scramble to keep pace.
Health system CFOs across the country are confronting the same paradox: AI is simultaneously the problem and the solution with the highest potential. How quickly organizations can move past theoretical conversations and execute actions to deliver ROI with AI may define their financial health for years to come.
MDaudit’s Answer: Meaningful, Not Artificial, AI
MDaudit was built for this moment. Rather than layering AI on as an afterthought, MDaudit embeds intelligence as a horizontal layer woven throughout the platform. The result is the Meaningful AI framework — a deliberate, outcomes-driven approach designed to deliver measurable ROI, not automation for its own sake.
MDaudit’s AI-powered solutions below delivered more than $500 million in ROI across its customer base in 2025. These solutions have done the heavy analytical lifting and leveraging of automation, while keeping humans in the loop.
These solutions include:
Payer Audit Workflow automatically extracts and organizes information needed from Additional Documentation Requests (ADRs) with SmartScan.ai, which compresses a process that once took days into minutes — accelerating provider response times and reducing administrative strain. Customers retained over 375 million in total revenues in 2025 by responding to payers in a timely and efficient manner
eValuator applies AI-powered rules to interrogate pre-bill charges across facilities, specialties, and multiple EHR and billing systems — surfacing encounters that require correction before a claim is ever submitted. The result: net revenue capture, stronger compliance posture, and costly denials prevented before they start. Customers have driven a total financial impact of more than 140 million in 2025 by taking a proactive approach with eValuator to ensure coding integrity
AI Assist democratizes access to strategic insights across the entire organization. Users at every level — including the C-suite — can ask questions in plain English and receive answers instantly, without reliance on report writers or technical interpreters. Data-driven decision-making becomes accessible to everyone who needs it.
“The most important questions for health systems implementing AI are: Is this technology reliable, secure, and meaningful to drive ROI? MDaudit has taken a first principles approach to these questions while developing our solutions,” said Ramesh.
Revenue Integrity Redefined: From Reactive to Confident Control
Modern revenue integrity unites revenue growth and risk mitigation into a single, connected framework. With real-time data, AI, and automated workflows, leaders gain early visibility into risk, clearer performance insights, and the ability to intervene before issues escalate into financial loss or regulatory exposure.
The strongest outcomes emerge when silos between compliance, coding, revenue cycle, and clinical teams are broken down, and when objective data drives prioritization, accountability, and cross-functional alignment.
MDaudit case studies across multiple health systems consistently demonstrate what that looks like in practice: expanded audit coverage without proportional staffing increases, measurable improvements in coding accuracy, significant reductions in denials, early identification of multimillion-dollar risk exposure, and increased executive visibility through defensible benchmarking.
This is revenue integrity redefined.
“Organizations that treat revenue integrity as a mission-critical capability supported by continuous monitoring and intelligent automation are better positioned to navigate payer complexity, workforce shortages, and regulatory expansion,” said Ramesh. “By moving from reacting to denials to anticipating risk, from defending audits to preventing them, and from fragmented oversight to confident control, MDaudit empowers revenue cycle teams to achieve outcomes that matter.”
Availity, the nation’s largest healthcare network connecting payers, providers, and technology partners, today unveiled Availity Extend, a new way to build automation and AI on the Availity network. Availity Extend lets organizations securely empower automated workflows by leveraging Availity’s existing connectivity, payer integrations, and trusted security framework, coordinating execution with live network data and logic, rather than relying on copied or externalized data.
With AI and automation already widely deployed across healthcare operations, the real constraint is not intelligence, but whether those systems can execute across governed, real?world workflows. Fragmentation—critical information and decision logic spread across organizations and systems that must remain tightly aligned—continues to limit scale, speed, and reliability. Automation only works at scale when it operates with full context and within trusted frameworks.
With Availity Extend, automation operates within existing identity, security, and compliance frameworks, with full auditability by design.
“AI in healthcare can’t stay confined to individual systems—it needs to operate across the workflows that directly connect payers, providers, and partners,” said Russ Thomas, Chief Executive Officer of Availity. “Availity Extend is designed to make that possible in a way that reflects how healthcare actually works: across organizations, within trusted frameworks, and at national scale.”
Making the Network Buildable
For more than 25 years, Availity has provided the neutral trust layer connecting payers and providers across core operational workflows, powering more than half of all U.S. healthcare activity each year. Today, the Availity network directly connects more than 4,000 payers and 3.5 million providers, with direct connectivity into payer systems, providing deeper access to payer logic, earlier in the workflow, where decisions can be made more accurately and efficiently.
Availity Extend builds on that foundation by providing a governed, network-connected way to develop and orchestrate automation across the Availity network. Through a standardized activation layer, payers and technology partners can coordinate end?to?end automation and agent?driven workflows in alignment with existing network logic, connectivity, and controls.
“Organizations across healthcare are investing heavily in automation and AI,” said Sean Barrett, Chief Product Officer of Availity. “Availity Extend allows those investments to focus on real operational outcomes—without recreating foundational connectivity or governance.”
What Differentiates Availity Extend
Coordinated workflows, not point?to?point APIs. Availity Extend enables end?to?end execution that maintains context across payer and provider workflows—producing completed outcomes rather than disconnected data exchanges.
Live network context, not replicated data. Because Availity Extend coordinates with live network data and logic, workflows stay aligned with real?time requirements and controls already enforced across the Availity network. Organizations can coordinate eligibility, authorization, clinical data, claims, and payment steps within a single automated workflow—without expanding access or introducing new data permissions.
Intelligence that compounds over time. Organizations that build on Availity Extend benefit from network?level insights that accumulate with use—informing automated and AI?driven workflows across real healthcare interactions.
Security and governance by design. All automation runs within Availity’s existing security, identity, and governance framework—the same framework that governs more than half of U.S. healthcare administrative transactions each year.
Looking Ahead
Availity Extend marks a shift from connecting healthcare systems to enabling real action by making the Availity network buildable, allowing automation and AI, including agent?driven workflows, to move from isolated use cases to coordinated, system?level execution, where governance, context and trust are enforced by design. Availity Extend is how that future becomes real.
Availity Extend is being rolled out with an initial set of content and customers in the first half of 2026, with broader availability planned later in the year.
The Centers for Medicare & Medicaid Services (CMS) is taking action, it announced, to protect Medicare beneficiaries and taxpayer dollars through implementation of a six-month, nationwide data-driven moratoria on new Medicare enrollment for hospices and home health agencies (HHAs).
New survey data from the American Medical Association (AMA) show physicians are pervasively skeptical that meaningful change will occur—reflecting 
By Gilda D’Incerti, Founder and CEO, 
