In this week's The Winning Edge webinar, sponsored by FinThrive, panelists discussed how revenue cycle teams are using Ai across the enterprise, reducing administrative inefficiency and opening up opportunities to improve clinical care.
Health systems and hospitals are scoring some early and significant wins in applying AI to revenue cycle management. Executives hope to continue that momentum as they apply the technology to clinical and payer relations.
Stephen Rinaldi, SVP and Chief Revenue Officer at UNC Health, says the North Carolina-based health system is leveraging AI across the RCM spectrum, including appointment and referral matching, patient financial eligibility and verification, and coding. They're also training the technology on denials and prior authorizations.
In short, AI is giving executives an opportunity to show just what goes into the revenue cycle management process.
"A lot of people think of revenue cycle as [just] being billing, even though it's the smallest piece of what happens in the revenue cycle," he says. "You have to take a step back and realize that it's [also] patient access and registration, as well as clinical documentation improvement, or utilization management and review, and partnership with providers, which is part of revenue cycle. It's at the elbow and it's side by side."
Rinaldi took part in this week’s The Winning Edge webinar, titled “Revolutionizing Revenue Cycle Management With AI" and sponsored by FinThrive. He and John Landy, FinThrive’s Chief Technology Officer, discussed how AI – particularly generative and agentic tools – is addressing key pain points in RCM and opening the door to new strategies.
Together, Rinaldi and Landy outlined five key areas in which AI is now being used:
Reviewing payer-provider and managed care contracts. Many of those contracts are thousands of pages long and revised often, making it difficult for healthcare leaders to stay on top of those programs. Providers are now using AI to review those contracts and point out everything from deliverables to discrepancies.
Prior authorizations. A process often fraught with back-and-forth phone calls and e-mails is ripe for improvement. AI can be used to identify when and where prior authorizations are required, help clinicians with the information needed for prior auths and even draft the correspondence to the payer.
Denials and underpayments. A key pain point in healthcare, according to Rinaldi. Providers can use AI to anticipate and address denials and underpayments, working with clinicians to improve care processes and reduce any opportunities for denials. In addition, AI can be used to track payer trends to better understand when and why denials and underpayments are issued, again in hopes of avoiding them.
Cash flow forecasts. RCM executives need to be able to determine cash flow over key time periods, such as 30, 60 and 90 days in advance, to react quickly in the event of an emergency and to chart the organization's financial health. Some are now using AI to analyze and chart that data, giving leadership more insight at a time when economic uncertainty is a daily concern.
Patient financial forecasting. Both Rinaldi and Landy pointed to this as an area for future growth. RCM departments are using AI now to analyze a patient's financial health, ranging from insurance coverage to ability to pay. Rinaldi points out these tools could help RCM staff work with patients to better identify when they might qualify for financial assistance or medical debt forgiveness.
Both Rinaldi and Landy see Ai helping to improve collaboration between the RCM team and clinicians, especially as the technology is used to plot disease identification and diagnosis and care pathways. Adding RCM to that process, they said, can help predict and address payer interventions and pinpoint opportunities for reimbursement.
"We've got to have the positions at the table, our tech partners and our revenue cycle leaders, in order to drive the organization forward," Rinaldi says.
But Rinaldi also says the increased availability and use of AI by consumers will drive RCM strategies. Patients will use AI, he says, to shop around for care, comparing prices and data on provider quality and reviews. Healthcare organizations will not only need to beef up their transparency and patient portals, but be prepared to have some delicate conversations around cost of care.
"We have to recognize that often that first person that a patient interacts with is a revenue cycle person, whether it's coming up to the ED, calling for an appointment, or showing up for an ambulatory test," he says. "We'll have to balance the sensitivities that are occurring around that."
Seattle Children's Hospital CIO Zafar Chaudry says an enterprise-wide deployment of a new tool will save millions in recruitment and retention costs, not to mention reducing stress and burnout and improving the clinical encounter.
The value of an ambient AI solution is often thought of in terms of soft ROI. But Zafar Chaudry sees some very solid savings – as in millions of dollars – when you figure out the true benefit of reduced clinician burnout and stress.
“Recruitment and retention is the value proposition,” says the SVP, Chief Digital Officer and Chief AI and Information Officer at Seattle Children’s Hospital. “It’s really hard to train clinicians, and [pediatric care] is a very expensive specialty.”
Dozens of specialties, to be exact. Seattle Children’s recently partnered with Abridge to expand an ambient AI platform across 18 of those pediatric specialties, giving doctors a tool designed to capture their interactions and transcribe the relevant data into the medical record.
For Chaudry, the tool very specifically targets clinician stress and burnout, buttressing the hospital against the rising tide of workforce depletion and hiring challenges. And that, to him, is as valuable as the improved clinical outcomes it will eventually produce.
“If we have 15% turnover, we can bring that down to 8% for every physician we don't lose and we retain,” he says. “And if we hire a new physician, it's a year's worth of work before they're really embedded in the health system. And a year's salary of a physician could be quite hard.”
“So we're doing this a lot from a recruitment, retention, [and] cost avoidance potential,” he continues. “And that's how we're justifying this: If you spend X amount and you can keep three docs … that's $3 million you didn't spend [along with] the recruitment process. We use an external company. They charge us 30% of the first year's salary just to find a person for you. So that's 300K a pop in money you would spend trying to find replacements because people left because you didn't give them the tools.”
“Even if you're bringing in $100K a year per specialty, and we have so many specialties, that's already millions,” Chaudry continues. “So the product is going to easily pay for itself over a three-year period. I would suspect in three years it's going to be cost-neutral and in five years it’s going to be positive.”
Measuring Clinical, RCM Benefits
The enterprise-wide expansion of the Abridge platform comes after a successful 90-day, 50-clinician pilot, during which those clinicians reported a 79% average reduction in documentation – a key pain point for any clinician wanting to spend less time in front of the computer and more time in front of the patient.
Chaudry says 83% of the clinicians involved in the pilot were “more than satisfied” with the ability of the technology to accurately capture the encounter, and 75% saw improvements in the quality of data-capture. They were especially impressed by the tool’s ability to catch pediatric-specific terms and transcribe accurately.
Now, the value of a good AI tool for clinicians is of course far more than reduced stress and burnout. Noting that it will take at least 12 months of data to measure the benefits, Chaudry sees the ROI for revenue cycle management in a tool that also mines the clinical encounter for coding opportunities, leading to improved reimbursements.
As well, the AI tool creates a standardized process for transcription, allowing the hospital to move away from the challenges associated with each clinician’s note-taking style.
“Some of our clinicians like to write 15 pages of notes and some of them write half a page, and it's really hard to get that consistency,” Chaudry notes, adding that the hospital hopes to have at least 80% of its clinicians on the platform.
Then there are the well-documented clinical and patient benefits. Taking clinicians away from the computer means they’re in front of the patient – or, in this case, the patient, the patient’s family and caregivers, grandparents and siblings, all of which can offer clues to clinical care and opportunities to improve that care. That benefits the clinician as well as patient engagement and satisfaction.
With an average of only 10-12 minutes per patient, Chaudry says, that time has to be given more value.
“This gives you more clinically focused patient time, and that's super important to our docs,” he says. “It also gives you an overall better patient experience because, you know, as a patient, I don't like watching people's backs.”
This week’s The Winning Edge webinar, sponsored by FinThrive, will take a closer look at how revenue cycle management leaders are embracing AI to improve efficiency and operations and collaborate on a better patient experience.
AI has the potential to significantly change revenue cycle management. How it’s implemented, integrated and monitored is crucial.
Integrating AI into revenue cycle operations is not a new idea, inasmuch as AI has been around for quite some time. But where healthcare executives in the past have talked about predictive analytics and automation, this new wave of technology focuses on generative AI, and large language models. More accurately, new platforms and tools are gathering in and assessing larger and more disparate amounts of data and generating pathways for data use and development.
Rinaldi and Casarella, along with FinThrive Chief Technology Officer John Landy, will discuss how leading healthcare organizations are deploying and managing AI to take on critical pain points such as denials and prior authorizations. They’ll discuss how data is used and monitored, how those processes have changed, and how today’s RCM teams are affected by these new processes.
Aside from the benefits and potential, we’ll also take a look at what happens when AI isn’t integrated or managed properly, and how an effective and comprehensive governance strategy is critical to success.
We’ll also talk about new ideas, like ambient AI and agentic AI, including bots, and explore how they might affect RCM. And we’ll take a look at how AI is helping the RCM department collaborate with other departments, such as clinical care, to improve overall care.
Join us at 1 p.m. Tuesday for this fascinating discussion into the future of revenue cycle management.
At the HealthLeaders Revenue Cycle Technology Mastermind forum this week in Savannah, RCM executives talked of how the technology is giving them a new profile — and compelling them to work more closely with clinical and administrative leaders.
Revenue cycle executives who are integrating the latest AI tools are seeing challenges that have less to do about technology and more to do about workflows.
In short, AI is creating a culture change. And that needs to be addressed well before anyone starts talking about deliverables and ROI.
That was one of the big takeaways from the HealthLeaders Revenue Cycle Technology Mastermind forum, an in-person event held Wednesday in Savannah just before the HealthLeaders Revenue Cycle Technology Exchange. The forum brought together executives from nine health systems to discuss the latest strategies and roadblocks, as well as debate new ideas like ambient AI integration, clinical and administrative collaboration and patient engagement.
The consensus was that AI is changing RCM and will be instrumental in boosting efficiency and outcomes, but making sure everyone is on the same page is a much harder task. That ranges from training (and in some cases retraining) RCM staff to manage new workflows and expectations, to working with clinical, financial and administrative leaders to define the ROI of a new tool to more than one department.
"It's about changing the old idea that revenue cycle management is just about the money," noted Allyson Keller, VP of the Patient Connection Center at Piedmont Healthcare.
In many cases, AI has raised the profile of the RCM department by highlighting how it can improve the health system's bottom line. But as RCM leaders integrate the technology into traditional workflows to improve operations, they're finding new challenges in marrying that potential with the health system's overall strategy. For example, the pace of change has been accelerated, so that five-year plans are unrealistic and are being replaced by one- to, at most, three-year plans.
That shortened time frame means executives need to be nimble in evaluating new technology. Short-term ROI is crucial, and that often means looking for rev cycle value in a clinical tool or talking with clinical leaders about how a tool that benefits the rev cycle can also add value to clinical operations.
That's a challenge. Joann Ferguson, the Henry Ford Health System's VP of Revenue Cycle, and Beth Carlson, VP of the Revenue Cycle and Chief Revenue Cycle Officer at WVU Medicine, echoed more than one executive in saying it's important to have clinical advisors as part of the RCM team, while Steve Kos, Senior Director of Revenue Cycle Application Support at Jacksonville, Florida-based Baptist Health and others spoke of the value of revenue cycle informaticists (and the difference between them and clinical informaticists). Without those connections, they said, it's often difficult to get in front of clinical leaders.
Part of the problem is that healthcare delivery has long been siloed. Finance and revenue cycle executives focus on the money, IT sticks to technology, and clinicians focus on what they do best. Lynn Ansley, VP of Revenue Cycle Management at the Moffitt Cancer Center, said clinicians often don't understand how to navigate the financial or administrative spaces, just as RCM execs don't necessarily understand clinical workflows.
But AI is changing that paradigm. It's enabling – some might say forcing – disparate parts of the hospital enterprise to work with each other. Clinical leaders need to know how the latest tech tool of platform not only improves clinical workflows and outcomes, but also how it impacts IT and RCM. To that end, an ambient AI tool that can also capture coding opportunities and improve patient handoffs would have value to multiple departments and catch the attention of the CFO and CEO.
And as AI takes away the traditional tasks associated with RCM, it's prompting RCM leaders to develop new job descriptions for their staff, including taking on more patient-facing tasks. The idea that AI can help clinicians reduce their time in front of the computer and spend more time with their patients also applies, in part, to RCM leaders and their staff. And that opens up opportunities to work not only with clinicians, but with payers to reduce denials and improve prior authorizations, even work with patients and understanding and managing their financial obligations.
RCM executives at the Mastermind forum were quick to point out that while AI can and does help with data-crunching and problem-solving, it doesn't replace the need to audit the technology or its outcomes. That ‘human in the lop' is just as important in RCM as it is in the clinical space.
But it does redefine RCM. Evan Martin, VP of Revenue Cycle Management at ZoomCare, pointed out that AI is taking what has always been a transactional process and is giving it a human face to the patient. No longer is RCM confined to the back offices of the hospital, and no longer are RCM leaders and staff relegated to number-crunching.
At the end of the day, one attendee noted, this is all about making better decisions for patient care.
Long considered the IT chief, CIOs are taking on new responsibilities and participating in long-term strategy. But can they earn the CEO's trust to set those priorities?
Today's CIOs are being asked to handle more than just IT, yet many feel they're not on the same page as their CEOs in developing strategic priorities.
That's the gist of a new report from digital security company Netskope, which calls on CIOs and CEOs to align their innovation and technology priorities to make sure the health system is headed in the right direction.
"The CIO role is evolving faster than many organizations are prepared for," Netskope's chief digital and information officer, Mike Anderson, said in a press release accompanying the survey. "CIOs are expanding their remit to own operations and business functions in a way that was not the case even a few years ago. Yet many don't feel fully aligned with their CEOs or empowered to make long-term decisions."
According to the survey, 34% of CIOs say they're significantly more involved with long-term priorities that expand beyond IT, and one of every three executives is being asked to lead the health system on initiatives like AI development, including human capital planning, digital innovation and operational resilience.
Yet at the same time, 34% of CIOs surveyed say they don't feel empowered by the CEO to make long-term IT strategy decisions, and 39% say they and the CEO aren't aligned on those strategies.
Solving that disconnect is the focus of HealthLeaders' newest exchange, the Chief Digital Executive Exchange (CDEX), taking place December 3-4 in Washington D.C. The invitation-only event will bring together CIOs from leading health systems and hospitals across the country to discuss collaboration to advance IT and innovation strategies, and it will feature panel sessions with CEOs, CFOs and other C-Suite executives.
The idea that the CIOs role in healthcare is evolving isn't a new concept. Top executives have been talking about this evolution for the past few years, driven in large part by the advances of AI and the need to embrace new ideas, like digital health and virtual care, to effect healthcare transformation.
To improve alignment between CIOs and their CEOs, the Netskope study suggests six topics of conversation:
Cost. CEOs are often unsure of the cost behind IT and innovation upgrades, and while the CFO should play a part in this discussion, it's up to the CIO to explain the rationale behind these improvements. At the same time, the CIO has to be clear that digital investment and transformation isn't just a fad or a search for the next shiny thing, and that investment in technology leads to improved operations and outcomes.
Risk. In today's uncertain healthcare environment, CEOs want to make sure they're plotting the right course for the organization. They need clear and sensible advice from their CIOs.
Innovation. Here's the sweet spot for CIOs, and where CEOs often are confused. Some executives confuse innovation for complexity, and immediately think in terms of increased cost and risk. It's important for CIOs to get in front of this, explaining where technology can be used and where workflows can be impacted.
People. A popular topic in these workforce-challenged times, and a key area where AI can make a difference. CIOs need to set the stage for their CEOs, explaining how strategic use of AI can address staffing pain points, improve efficiency and workplace morale and even raise the bar on recruitment.
Measurement. CIOs are the technology experts, and CEOs need to look to them to understand how that technology is evaluated. Is the organization getting all it can get from the EHR? Are digital health and virtual care platforms providing the right ROI? And more importantly, is technology supporting or standing in the way of clinical care?
The IT Estate. This dates back to the idea that different parts of the healthcare enterprise are siloed, with a C-Suite executive in charge of just one part of the whole and no one getting in anyone else's way. That philosophy is changing: True healthcare transformation depends on collaboration across the C-Suite, and that means the CIO has to let the CEO into what's often called the "black box" of IT.
Ambient AI tools are proving their value in reducing clinician stress and documentation burden, but there are risks to using them. A new study offers some tips on how to make sure they're governed and used effectively and safely.
Ambient AI tools may be all the rage in healthcare these days, but that rapid adoption may be exposing healthcare providers to risk.
A new study out of Columbia University finds that AI scribes are proving their value in reducing clinician stress and burnout by easing documentation burdens. But that potential should be weighed against the risk of documentation errors, privacy concerns and a lack of transparency.
"Moving forward, we must balance innovation with safeguards through rigorous validation, transparency, clear regulations, and thoughtful implementation to protect patient safety and uphold clinical integrity," the study, conducted by Maxim Topaz and Zhihong Zhang of Columbia University and Laura Maria Peltonan of the University of Eastern Finland and posted in Nature, concludes. "The key question is not whether to adopt these tools but how to do so responsibly, ensuring they enhance care without eroding trust."
The concern isn't new to healthcare. The rapid embrace of AI by healthcare providers has come side-by-side with concerns that governance is falling behind, and that providers are putting their organizations at risk by using new tools without first establishing the proper guardrails.
That's especially true of AI scribes, which capture PHI during the doctor-patient visit and could be putting that data at risk.
Aside from HIPAA concerns, healthcare executives need to make sure patient consent is baked into the process, as well as transparency about how the technology works, why it's being used and measures taken to protect patients and data.
4 Key Concerns
The study cites four concerns related to scribes:
Hallucinations. AI tools can generate inaccurate or even fictitious content, such as creating non-existent diagnoses or case studies. That's especially true if a scribe isn't trained on the language of a particular specialty.
Omissions. A scribe might not be able to track all of the conversation, especially if there are multiple speakers speaking at once, and might miss vital information.
Misinterpretations. Some AI scribes may not be trained to understand medical jargon, or to understand context related to a specialty like pediatrics or mental health. They also can't track non-verbal communications, including gestures and visual signs of discomfort or stress. Finally, they might not be trained to pick up on social determinants of health, yet another key element in care management.
Misidentifying speakers. If there are several people in the room (such as during a pediatric exam), the scribe might not be able to keep up with who's talking. And according to the study, speech recognition systems underlying AI scribes might have had difficulty with African American speakers, resulting in higher error rates.
One key concern is that ambient scribes aren't equipped to differentiate what should go into the medical record and what can be left out. The study cited research that indicated roughly half of patient problems and 21% of care interventions discussed by home healthcare nurses and patients don't make it into the EHR.
"These gaps occurred for various reasons, including problems being outside the scope of practice for the conversing clinicians or issues not deemed severe enough to warrant documentation," the researchers noted. "This raises critical questions about how AI scribes might change documentation patterns. Will these systems document everything discussed, potentially creating information overload? Or will they selectively filter information based on unclear criteria? Either approach presents challenges. Comprehensive documentation might capture previously missed information but could also clutter the medical record with less clinically relevant details."
"Conversely, if AI scribes apply filtering algorithms, they might perpetuate or even exacerbate existing documentation gaps without the contextual understanding that human clinicians possess," they continued. "These risks may disproportionately affect vulnerable populations who are less able to engage in effective self-advocacy."
Other Issues
There are other concerns as well.
"Compounding the issue is the ‘black box' nature of these systems," Topaz and his colleagues reported. "The underlying neural network algorithms are not constrained by established medical knowledge, making it difficult to understand how they arrive at specific conclusions or predict when errors might occur. This lack of transparency makes it challenging to identify potential biases within the system and ultimately ensure the reliability of generated documentation."
"Emerging explainability techniques, such as attention visualization (which highlights which parts of conversations most influenced specific documentation decisions) and SHapley Additive exPlanations (SHAP) frameworks (which identify key linguistic features that trigger certain AI outputs), offer promising approaches to enhance AI transparency; however, their effectiveness and practical implementation for clinical documentation systems require further validation."
Finally, AI tools may be leading to increased expectations – as seen in several health systems that found physicians weren't finding significant benefits in using them. According to the study, ‘healthcare organizations may respond by increasing patient volume expectations based on promised efficiency gains, creating a workload paradox where modest time savings are offset by greater demands and the cognitive burden of reviewing AI-generated errors."
As well, the study points out that clinicians might also become too dependent on scribes, "potentially compromising their professional judgment and independence in clinical decision-making."
Making Sure Governance Is Front and Center
The key, then, is to make sure the guardrails are in place for the use of AI scribes in clinical care. To that end, the study offers five recommendations:
Establish rigorous validation standards. Use independent, standardized metrics for accuracy, completeness and time saved.
Mandate transparency. Make sure vendors are disclosing how these tools work, what data they're using, and their limitations, including biases, and insist on regular reporting of error rates.
Develop clear regulatory frameworks. Define responsibility and accountability when errors are found, and set clear expectations for correcting errors.
Implement thoughtful clinical protocols. Establish robust training programs, quality assurance processes and patient consent protocols for the use of AI scribes. Training programs should include how clinicians audit their content, monitor for errors, verify clinical accuracy and edit while maintaining accuracy.
Invest in research. Set aside funding to support independent research around the long-term impacts of AI scribes on quality, clinical decision-making and communication, including discipline and specialty-specific evaluations.
With pandemic-era telehealth and Hospital at Home waivers expiring, executives are curtailing or ending some virtual care services. Supporters, meanwhile, are lobbying to extend those flexibilities or make them permanent.
Health system and hospital leaders are cutting telehealth and Hospital at Home programs following the expiration of pandemic-era CMS waivers, but that doesn't necessarily mean those programs are gone for good.
Healthcare leaders say they're looking only at short-term strategies as advocates, led by the American Telemedicine Association and the Alliance for Connected Care, lobby Congress to reinstate the waivers in any spending bill to end the federal shutdown. And while aiming to restore the waivers for the time being, the ultimate goal of advocates is to make those freedoms permanent.
For now, however, telehealth policy reverts to pre-COVID rules.
Originating site. The waiver allowed for telehealth services to be delivered at any U.S. location, including the patient's home. Restrictions are now back in place, limiting telehealth to certain locations, including the provider's office, hospital, SNF, and home if the patient is receiving home dialysis for end-stage renal disease (ESRD), treatment for substance use disorder (SUD) or diagnosis, evaluation and treatment for a mental health disorder (provided the in-person visit requirement is met).
Geographic restrictions. The waiver eliminated those restrictions. Now, telehealth services are limited to a rural health professional shortage area or a county not included in a Metropolitan Statistical Area. Exceptions are made for patients with ESRD receiving dialysis at home or at a hospital or critical-access hospital-based renal dialysis facility, as well as patients receiving diagnosis, evaluation or treatment for an acute stroke, those receiving for SUD or a co-occurring mental health disorder, and those receiving diagnosis, evaluation and treatment for a mental health disorder (provided the in-person visit requirement is met).
Audio-only visits (such as via telephone). These were allowed through the waiver for any clinically appropriate telehealth services. Now, they're limited only to patients receiving telehealth services at home if the care provider has the technology to conduct an audio-visual visit but the patient can't or won't use video.
Provider types. The waiver expanded the list of healthcare providers able to bill Medicare for the use of telehealth to include occupational therapists, physical therapists, speech and language pathologists and audiologists, among others. Now that list is limited to physicians, PAs, NPs, clinical nurse specialists, nurse-midwives, clinical psychologists, clinical social workers, registered dietitians or nutrition professionals, certified registered nurse anesthetists, marriage or family therapists and mental health counselors.
Federally Qualified Health Centers (FQHCs) and Rural Health Centers (RHCs) as a distant site. The waiver enabled FQHCs and RHCs to bill Medicare for telehealth services as eligible distant sites. This is no longer allowed.
In-Person Mental Health Treatment. The waiver enabled mental healthcare providers to use telehealth without first conducting an in-person assessment with the patient. Now, an in-person visit is required for patients receiving diagnosis, evaluation or treatment for a mental health disorder before telehealth can be used. That visit must take place within six months prior to the first telehealth visit and every 12 months thereafter while the patient is receiving treatment. An exception can be made if the provider and patient agree that the risks of an in-patient visit outweigh the benefits and the provider documents that decision in the patient's medical record.
CMS has also updated its guidance on Medicare telehealth claims during the ongoing shutdown.
According to the Center for Connected Policy, the guidance, released on October 1, directs Medicare Administrative Contractors (MACs) to implement a temporary claims hold, which can last as long as 10 business days.
"The hold is meant to prevent a large reprocessing of claims if Congress acts after the statutory expiration date, which was September 30, 2025," CCHP reports. "CMS also suggested that without further Congressional action, providers that deliver telehealth services and are now not eligible for Medicare payment as of October 1, 2025, may want to provide patients with an Advance Beneficiary Notice of Noncoverage."
Why Were the Waivers Enacted?
The waivers were launched during the height of the COVID-19 pandemic in 2020 to boost telehealth coverage and access by giving providers more opportunities to use virtual care. That increase, in part, helped fuel a surge in telehealth programs that carried over into the post-pandemic era.
Advocates say the waivers are crucial to enabling health systems and hospitals, especially those in rural and underserved regions, to improve access and clinical outcomes. Without them, it's expected that many providers will scale back their telehealth services or even end them altogether.
In letters to Congressional leaders and President Trump, ATA Action, the ATA's lobbying arm, called for both the telehealth waivers and the Acute Hospital Care at Home (AHCaH) waiver to be reinstated, saying healthcare providers have been building strong programs since they were enacted in 2020.
"Most providers and hospital systems are taking calculated risks to continue care during this time, but long-term continuity depends on action by our telehealth champions in Washington to restore these flexibilities and ensure retroactive reimbursement," said Kyle Zebley, ATA Action's executive director and the ATA's senior vice president of public policy. "Medicare patients woke up this morning without telehealth coverage for the first time since the pandemic, five years ago. Our healthcare services are regressing, falling woefully short for millions of patients in need."
The Hospital at Home Waiver
Roughly 400 health systems and hospitals were participating in CMS' AHCaH model as of September 30. Some have shut down their programs or let them lie dormant after patients transitioned out.
"Like many other healthcare organizations across the country, all of our patients who were receiving hospital at home care have been either appropriately discharged to outpatient status or transferred to brick-and-mortar inpatient care," the health system said in a statement to HealthLeaders. "Extension of the waiver, or even better a permanent authorization, is essential to allow our patients to continue to have access to this program that has improved patient outcomes, expanded access for rural communities and enabled greater flexibility in how care is delivered."
Others, especially larger organizations, say they'll continue with a model that they feel is a key element to the future of healthcare.
Executives at Mass General Brigham, one of the front-runners in the acute care at home movement, have also altered their program.
"While there continues to be strong bipartisan support for the Acute Hospital Care at Home Waiver extension, it is unfortunate that the timing of its expiration was tied to the broader government funding debate," a spokesperson said in an e-mail to HealthLeaders. "Fortunately, the steps we have taken over the last year have enabled us to pivot our operations to provide advanced care at home for patients after a hospital stay during this pause. This framework enables us to support patients outside of the inpatient waiver while maintaining the structure we need to provide exceptional acute care in the home."
"The future of healthcare is in the home and we are invested in our efforts to see this through," the spokesperson continued. "We will continue to advocate for a multi-year waiver extension to reduce the capacity strain on our brick-and-mortar hospitals and ensure our patients receive this safe, effective and exemplary care where they want it, surrounded by their family and loved ones."
The concept has a lot of supporters, and studies are showing the value in delivering acute-level care at home. MGB, for instance, has published reports noting clinical and financial benefits in caring for patients in their homes instead of a hospital, and the health system's announcement that it will continue the program points to an opportunity to show that this strategy can survive beyond the waivers.
But he also noted that the CMS model isn't perfect.
"I don't think that the way it's structured now is necessarily that way it will be structured forever," he said. "We need more of a critical mass of information" to prove what works and what doesn't.
"Research shows that hospital at home models yield positive health outcomes," the Bipartisan Policy Center stated in an August 2024 report calling for continued support for the program. That report cited a small study which found that the program led to shorter hospital stays, lower readmission rates, fewer diagnostic tests, and lower costs compared to patients admitted to the hospital for the same health concerns.
"Initial data show promise, including the potential for cost savings," the report added. "But more research is needed on patient and caregiver experiences, access and patient selection, the cost impact on Medicare and Medicaid, hospital expenses, and service delivery across diverse populations. Research is also needed on whether the relatively small number of hospitals participating is nonrepresentative and unique. … Congress needs more clarity about the likely financial effects of the model if it were to move from a model with low uptake, which is the case today, to something that would be implemented on a larger scale."
Health systems and hospitals conduct extensive reviews of any new AI tool before putting them to use. Through at least one and sometimes several different committees, they ask questions about everything from value to workflow effects.
Healthcare leaders are putting new AI tools through a rigorous review process before they’re tested in the healthcare setting. In many settings those tools pass through a series of committees, who evaluate the technology for cost, usability, workflow effects and, of course, ROI.
James Blum, MD-CDH-E, Chief Health Information Officer at University of Iowa Health Care, takes this a step further. Any pilot using AI, he says, should be good enough to publish as a study and stand up to peer review.
Here’s what healthcare leaders are asking of their AI tools:
This week’s The Winning Edge webinar focused on the backbone of the healthcare ecosystem, and how AI is being asked to make data management easier for healthcare leaders.
Healthcare organizations are dealing with massive amounts of data, clinical and financial, structured and unstructured. And while AI may be the tool to manage that data, there’s a lot of work that goes into setting up the rules and guardrails.
HealthLeaders’ The Winning Edge took on that hot-button issue this week with an in-depth discussion about data management from two renowned experts. Roopa Foulger, VP of Digital and Innovation Development at OSF HealthCare, and Sarah Pletcher, MD, MHCDS, Chief Digital Health Officer and SVP and Executive Medical Director of Strategic Innovation at Houston Methodist, laid out how their health systems are managing data and governing data usage.
It’s not an easy task. Ironically, while AI may eventually take away all the heavy lifting for data management, right now there’s a lot of complexity.
“Where the data was acted on or how the data was inputted has a meaning depending on where it is in the clinical workflow,” Foulger notes. “We're just scratching the tip of the iceberg in terms of how we're going to leverage that data clinically and financially.”
CommonSpirit Health CIO Daniel Barchi says AI development over the next five years won't focus on better technology, but on healthcare leaders finding the right way to use the tools to make healthcare more efficient.
The CIO of the nation's second largest nonprofit health system says AI governance isn't a revolutionary concept. It's a strategy built on how the industry has embraced new ideas and technologies in the past.
"It's important to remember that clinicians, hospitals and health systems have been caring for patients for many, many years through many advances in technology and many changes in clinical care," says Daniel Barchi, EVP and CIO of CommonSpirit Health, the Chicago-based network of 142 hospitals and more than 700 care sites spread across 21 states. "And if we hew to the guiding principles that clinicians have and that we as caregivers should aspire to have, we can apply those same ground rules, guiding principles and vision to AI in the same way that we've used other advanced tools safely."
Daniel Barchi, EVP and CIO of CommonSpirit Health. Photo courtesy CommonSpirit Health.
That's not to say that AI isn't causing problems with its rapid adoption, but Barchi says healthcare executives need to temper their concerns with a little common sense. They've been down this road before.
"Our goal is to make sure that we use it in the most efficient way for how fully it's developed at this point," he says. "And [we] use it as broadly as possible, with the proviso that we always have a clinician between the AI and the patient."
Reviewing AI Use Cases
CommonSpirit Health has a three-tiered approach to AI governance. Barchi says the health system runs any AI projects first through data management and patient advisory councils, then through the enterprise data and AI governance committee (EDAG), before finally going before the IT executive steering committee. Some 200 tools have made it through review and are now being used with the health system.
But there have been some that didn't make the cut.
"We've rejected 15 use cases for different reasons," he says. "Whether we didn't feel that they were clinically efficacious, [or] we were concerned about the ways that a third-party company might be using data, [or] whether or they were concerns about algorithmic bias."
Most, if not all, of those rejections come out of the EDAG committee, which meets every two weeks and is comprised of roughly 30 members, including ethicists, medical informaticists and representatives from legal, innovation, finance, clinical (including nursing), IT and cybersecurity departments.
"These people come together and evaluate every AI initiative that we have and determine if there are risks, if we're using data appropriately, if there are risks of algorithmic bias, what the upside is and whether we should approve it for use clinically and operationally in our health system," Barchi says.
Analyzing Agentic AI
He says he's particularly interested in how agentic AI evolves.
"We're creating the capability for tools to surface information, analyze it, make decisions and interact with others in ways that are very similar to what many of our colleagues do with data today," he says. "And management of these AI tools in agentic AI is almost akin to managing a team of workers. Thinking of this not as a technical process, but as a management challenge and a way to use operational efficiency safely is the next frontier for us as health system leaders."
"I anticipate over the next five years many of the advances and adoption of AI are not contingent on AI getting better," he adds. "It's health leaders thinking more intuitively about how AI can make our processes more efficient."
Which ties back to the idea that AI will replace doctors and nurses. Barchi says that isn't about to happen, as healthcare is still based on human interactions. But he does believe that healthcare organizations using AI will replace those who aren't on the bandwagon, and those using AI will become better at delivering healthcare.
"Physicians, nurses and other clinicians are more likely to be more thoughtful caregivers, because they can focus on the patient in front of them and allow AI to do more of the work behind them," he says. "And I've seen clinicians be very open-minded [about] what AI can provide them, whether it's data or insight, because they know at the end of the day, their overarching objective is improving the health of the patient in front of them."
That concept will also apply to patients using AI.
"We are better patients when we're better informed about our own health conditions," Barchi says. "We'll never be as educated as the neurosurgeon who's caring for us, but we have better insights to what he or she shares with us by being more educated and using AI and other tools to gain insight about the ways we might help with our own caregiving."
Charting a Future for AI
Looking ahead, Barchi sees AI evolving in two directions. He expects new tools and programs to be integrated directly into existing technology platforms like the EHR, so that workflows aren't negatively affected. He also believes that healthcare organizations will develop the capabilities to create their own AI tools.
"We'll simply adopt them in a way that nobody would go off and buy aftermarket parts for a car if you can buy them with the car itself," he points out. "And so yes, there will always be point solutions, but I think those are going to be fewer and more far between and developed internally. And then much of what we get from AI is simply going to be embedded in the tools that we buy and it's going to be harder for standalone companies to try to sell point solutions that are not embedded in our core platforms."
And he sees AI helping healthcare move out of the hospital, clinic and doctor's office and into the home.
"AI will begin to assimilate data and make inferences about our healthcare long before we as patients think about a clinical condition," he says. "It might monitor the number of times we open the refrigerator, the number of steps that we take, the way that we sleep, our online patterns, and look for patterns in a way that might inform an emerging condition long before you even begin to feel it physically."
