ATA Nexus 2026: Why Virtual Care Needs Enterprise Orchestration, Not More Point Solutions

At ATA Nexus in Orlando, hosted by the American Telemedicine Association, I had the chance to connect with healthcare leaders and hear from experts and innovators on scale, trust, ROI, and the operational work still standing between virtual care and connected care.

Healthcare is a domain we at Avaya are deeply invested in. Many of the nation’s largest hospitals and health systems depend on Avaya for enterprise critical communications infrastructure and modern contact center as a service (CCaaS) solutions that support patient experience, clinical workflows, and care team coordination.

What stood out to me most was how practical the conversations were. Across sessions on hybrid care, virtual nursing, AI, remote patient monitoring, health IT policy, emergency escalation, and financial storytelling, the focus was on what it takes to make virtual care models scalable, trusted, connected, and financially sustainable. 

Scale Needs Infrastructure

In a roundtable on scaling telehealth programs, the medical director for telehealth and virtual care at MaineHealth, opened with a deceptively simple question: “What does scale mean?”

The room did not land on one answer. Some people went straight to volume, utilization, reimbursement, and sustainability. Others talked about repeatable workflows, governance, staffing, documentation, support models, and whether a program can move from one site to another without starting over.

She shared one example from MaineHealth: a virtual nursing program with more than 20,000 encounters. The volume was there, but workflows still varied across entities. She contrasted that with a multidisciplinary liver transplant intake workflow that runs only a few times a month, but has enough documentation, consistency, and portability to work across clinics.

The manager of the National Tele-Neurology Program at the U.S. Department of Veterans Affairs brought in the national specialty-care view. His team supports rural hospitals with neurologists located across the country. He described the goal as operating as though the specialist is “1,000 feet away,” even when the provider may be physically located thousands of miles from the patient site.

For me, the thread across those examples was infrastructure. Scale showed up less as a size question and more as a repeatability question: 

• Can the workflow travel? 
• Can teams support it? 
• Can data follow it? 
• Can the model hold up across different sites, staffing structures, and care settings?

Virtual care can start with a program, a device, a call, a referral, or an AI-supported workflow. Scaling it requires the infrastructure to connect people, data, workflows, communications, and decisions across the enterprise. 

Specialized Tools Still Need to Work Together

The industry is not moving away from point solutions anytime soon. In healthcare, there will always be specialized tools for telehealth, remote patient monitoring, virtual nursing, ambient documentation, imaging, scheduling, referrals, and condition-specific care. The problem I heard at ATA Nexus was the operational burden of stitching them together.

In one roundtable, a speaker described the “iPad corral” that can build up when every virtual care use case comes with its own device, platform, or workaround. Another talked about programs that looked promising at launch, only to end up with technology sitting unused because adoption never followed.

On the main stage, Rachel Feinman, Senior Vice President of Innovation, Ventures, and Digital Solutions at Tampa General Hospital and Managing Director of TGH Ventures, put it bluntly during the digital health investment panel. Too many startups, she said, still come in with some version of: “I integrate with your EHR, and basically if you just give me all this data, I’ll solve this one problem for you.”

Her point was that health systems hear that pitch constantly. Many can now build narrow AI tools or workflow agents themselves, so outside vendors need to bring more than a single-feature fix. They need to solve a broader workflow problem, move faster than the health system could on its own, or connect into a larger operating model.

That is where openness becomes less of a product feature and more of an operating requirement. Health systems will keep using specialized tools, but those tools need a way to connect into the broader workflow, data, and communication environment around them. Without that connective layer, every new solution risks becoming another place where work, context, and accountability get stuck and siloed. 

AI Trust Depends on Workflow Design

The AI conversations at ATA Nexus kept coming back to oversight, escalation, validation, and trust.

One example came from the digital health platform, Friendi.fi, which discussed AI-supported engagement workflows for behavioral health and autistic young adults. In response to a question about when automated interactions should escalate to a human reviewer, the company described its model as “human-on-the-loop, not in the loop.” Its workflow starts with AI-drafted messages, uses a proprietary safety and quality model to score interactions, and routes the smaller set of higher-risk conversations to human reviewers.

That distinction fits the reality that many healthcare organizations are working through now. Some AI-supported workflows need human review before action. Others need human supervision with clear escalation triggers. The design depends on risk, clinical context, patient population, and the consequences of getting it wrong.

The same question surfaced on the main stage during a federal health policy discussion with Thomas Keane, MD, National Coordinator for Health Information Technology at the Office of the National Coordinator for Health Information Technology. Dr. Keane described AI oversight through two lenses: autonomy and criticality. A tool that is highly autonomous and makes high-stakes clinical decisions requires a different governance posture than a tool helping summarize notes or support lower-risk administrative work.

For me, “human in the loop” felt too broad to stand on its own. Healthcare leaders need to define who reviews, who escalates, who documents, who audits, and who owns the decision when AI is part of the workflow.

Avaya’s tandem care concept gives that discussion a useful frame: AI, automation, and human expertise working together in the same workflow, with context, oversight, and clear handoffs built into the experience. 

Care Teams Need Context, Not Just Data

Context surfaced across ATA Nexus in almost every AI and virtual care discussion I joined. Speakers talked about how much patient information now exists across EHRs, remote monitoring platforms, wearable devices, outreach programs, payer systems, referral workflows, care teams, and communication channels.

The challenge is carrying enough context forward for clinicians, care teams, outreach staff, and AI-supported workflows to make informed decisions. 

A presentation from Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo raised one practical example: Patients who used a hotline had about a 90% follow-up visitation rate, compared with about 78% for patients who completed an online course. What stuck with me was the discussion around everything behind those numbers. 

• Did the patient have reliable broadband? 
• Did they prefer talking to a person? 
• Had prior outreach already failed? 
• Was transportation an issue? 
• Was a caregiver involved?
• Was any of this context documented in the EHR?

Those details help care teams understand who may need outreach, which channel is most likely to work, what barriers may be getting in the way, and what should happen after the interaction.

ROI is Where Virtual Care Strategy Gets Tested

The last session I attended at ATA Nexus focused on financial storytelling, a topic that immediately caught my attention as a former health journalist who has written extensively about Medicare, Medicaid, and the complexities of paying for care.

The chief medical officer of the MedStar Telehealth Innovation Center and AVP of Virtual Care at Ochsner Health led a practical discussion on one of virtual care’s hardest questions: how do you prove the value?

They noted that some programs, such as tele-stroke, are easier to justify because the need and coverage model are clear. Larger infrastructure investments, such as virtual ICU or virtual nursing technology stacks, are harder because value shows up across workforce capacity, quality, patient experience, and operational reliability.

The advice throughout the session was to stay specific. Broad claims around metrics like length of stay can weaken the case when multiple initiatives across a health system may influence the same outcome. Speakers encouraged organizations to focus on the part of the workflow their program can directly impact and to account for the operational work required to support it.

That work extends far beyond the technology itself. Security reviews, workflow redesign, training, support, network readiness, analytics, device management, and internal labor all shape the real cost and sustainability of a program.

The phrase “vendor math” came up more than once. Health systems often discount ROI models that overlook the implementation burden on their side. One participant referenced roughly 200 hours spent building a single business case. Another described an 18-month effort to justify a command-center and virtual nursing investment that still had not received approval.

Those conversations felt relevant for any organization modernizing healthcare infrastructure while balancing operational priorities, implementation realities, and long-term sustainability. I previously wrote about some of those modernization considerations in How Federal Grants Can Support Critical Communications Infrastructure Modernization. 

Virtual Care Orchestration is the Next Enterprise Layer

Outcome-aligned payment models (OAPs) make orchestration a business issue. In these models, reimbursement is tied less to individual services and more to whether care improves access, quality, coordination, cost, or patient outcomes.

That came through in ATA Nexus conversations about the Centers for Medicare & Medicaid Services (CMS) ACCESS Model, a 10-year accountable care model focused on improving specialty care access and coordination for traditional Medicare patients. The first participants are expected to begin in July 2026, with additional application cycles planned over the life of the model.

As Abe Sutton, JD, Director of the Center for Medicare and Medicaid Innovation and Deputy Administrator at CMS, explained in an AMA interview about ACCESS: “Technology can support that,” but participating organizations will be required to share data back “to help manage that relationship with the patient.”

That is where coordination becomes orchestration. When payment depends on outcomes, organizations need to show what happened after the first interaction: 

• Was the patient reached? 
• Was the referral completed? 
• Did the care team have the right information? 
• Was the next step documented? 

That is the enterprise case for orchestration. Hospitals and health systems have already invested in many tools that support virtual care. The next layer is the infrastructure that helps those tools work together across workflows, teams, communications, data, and AI.

For Avaya, that means helping healthcare organizations modernize the communications and workflow infrastructure behind connected care.

Learn more about Avaya Infinity and Avaya Nexus.