Many health systems have added operational technologies over the past several years. Yet for some leaders, it’s not clear these tools have made the work simpler — or that they’ve resolved the organization’s most pressing operational challenges.
Instead, operational complexities, inefficiencies and costs have only intensified. These challenges are forcing healthcare leaders to assess the state of their organizations’ operations, project their organization’s current and future operational needs and explore innovative enterprise-wide solutions.
Confronting healthcare’s increasing operational complexity was a central theme at the 2026 symplr Healthcare Operations Summit, held in partnership with Becker’s Healthcare. The event brought together C-suite and healthcare operations leaders from more than 100 leading healthcare organizations, collectively representing over 2,300 hospitals, 1.6 million employees and $477 billion in revenue.
Insights from the summit are summarized below.
Macro healthcare trends impacting operations
Four macro trends helped frame the summit’s discussions on the state of healthcare operations.
- Revenue fragility. Hospital operating margins are under tremendous pressure. While margins were already low in 2025, at 1.3%, they declined to -0.6% in early 2026. Rising expenses are a key factor contributing to low margins.
- Federal policy shock. The One Big Beautiful Bill Act is projected to cut about $1 trillion in Medicaid spending over the next 10 years, costing hospitals around $25 billion per year. Leaders expect this environment to worsen in 2027.
- Consolidation. Industry consolidation continues, with some health systems growing through mergers and acquisitions, and others divesting hospitals as part of strategic repositioning. Consolidation often results in technology sprawl, as different hospitals have different tech stacks and applications. This situation creates multi-year commitments to achieve integration
- AI adoption. Among physicians, adoption of ambient AI has been high, producing wins in terms of time savings, patient satisfaction, clinical retention and recruitment. However, the AI experience on the operational side has not kept pace — staff go from streamlined clinical documentation back to fragmented scheduling and operational workflows. That gap is driving growing interest among operational leaders in applying AI to achieve the kind of meaningful results clinicians are already experiencing.
View from the front lines: Operational inefficiency is increasing
The core work of healthcare is for clinicians to care for patients. Healthcare operations makes this possible through workforce development and management, provider data management, quality safety management, business analytics and forecasting, supply chain procurement, scheduling and other administrative tasks.
However, multiple challenges impede the success and efficiency of healthcare operations.
“We’re struggling with the same challenges as everyone else: access, capacity, technology adoption, supply chain, you name it,” said April Taylor, vice president and chief operating officer at The Johns Hopkins Hospital (Baltimore), a 1,100-bed academic medical center with more than 11,000 staff members.
Ms. Taylor offered several reasons why hospitals and health systems are struggling operationally. First, fragmented systems and processes result in silos, which increase inefficiency and make it difficult to operate efficiently as a collaborative, cohesive system.
Second, the structure, processes and culture of many healthcare organizations are embedded and difficult to change, causing organizations to continue to operate as they always have.
Third, years of well-intentioned digital innovation and transformation initiatives have often fallen short, resulting in partial implementation and only limited success. These initiatives have produced technology sprawl and organizations that are skeptical of the next technology initiative.
“With digital innovation and technology, the promise was there but it hasn’t gotten us to the fully simplified state we’re trying to get to,” Ms. Taylor said.
Part of the problem is that new technology gets added without retiring old solutions. And too often, it’s layered onto existing processes rather than prompting a rethink of the underlying workflows — effectively digitizing inefficiency.
“My take-home message is that the challenges organizations are experiencing are not technology problems; it is really a challenge with our operating model,” Ms. Taylor said.
Improve healthcare operations by solving specific problems
Healthcare operations leaders know the status quo isn’t working and are looking to make changes to improve operations at scale.
One strategy is to focus narrowly on identifying and solving one major operational pain point. Advocate Health, a nonprofit health system based in Charlotte, N.C., with 69 hospitals and 42,000 nurses — including 23,000 in acute care — took this approach.
Scheduling was a major pain point for nurse managers, who averaged spending six hours per day, every day, on scheduling and staffing challenges. Managers were navigating six different scheduling platforms, with some still choosing to use Excel or even paper for scheduling.
Meanwhile, while managers were juggling multiple time-consuming scheduling systems, nurses were increasingly demanding even greater scheduling flexibility — compounding the complexity of scheduling.
Advocate’s leaders first defined what they wanted in a new scheduling solution: reduced administrative burden for managers, easier scheduling for teammates — including self-scheduling — faster open-shift coverage without burdening leaders, controlled incentive pay and aligned time and attendance.
Leadership chose symplr to provide an AI-driven, enterprise-wide scheduling solution that would meet these needs and replace all previous scheduling platforms. The approach reflects a core belief in combining technology with human judgment.
“We know that humans plus AI are better than humans alone or AI alone,” said Katie Barr, Senior Vice President and Chief Nursing Informatics Officer at Advocate.
This strategy does not involve using AI broadly to solve all operational challenges; it involves initially pinpointing and solving one major problem, delivering significant impact for Advocate.
AI’s increasing potential for operational impact
While many digital transformations haven’t delivered their intended benefits, many healthcare operations leaders believe AI will.
“I do think AI is going to be a mechanism to help simplify healthcare going forward in all realms,” said Robert Bart, MD, chief medical information officer, University of Pittsburgh Medical Center (UPMC).
Healthcare leaders see AI as unlike any previous technologies. “I’ve seen a lot of fads come and go,” said Scott Sbihli, chief product officer at symplr. “I believe that AI is more transformational than anything that’s happened in technology.”
While ambient technology has shown success in clinical applications, it represents just a fraction of AI’s potential to reshape healthcare operations.
Dr. Bart suggested a lens for thinking about investments in AI solutions and platforms: Any AI initiative needs to improve the effectiveness or efficiency of care delivery —and translate into either a financial or an operational return on investment (ROI).
He offered an example of how AI can demonstrate operational efficiency and a positive ROI. Within the EHR there are “work queues.” Today, a work queue requires a human to move something from A to B to show a task has been completed. This might involve prior authorization, scheduling or another task.
At UPMC, there are around 23,000 work queues. Performing the tasks in these work queues takes considerable time and resources, at a considerable expense. It will be possible to have AI agents perform the tasks in these queues, streamlining operations and freeing people up for more valuable work.
“My goal is not to replace people,” Dr. Bart said. “It is to replace meaningless non-value-added work that adds a tax on the organization. It’s about making operations more efficient and more effective so we can get people doing tasks that are really important to care delivery.”
Among ways that AI can impact healthcare operations are streamlining workflows, improving the speed and quality of credentialing, expediting the revenue cycle and decreasing waste through, for example, less nursing overtime or need for agencies.
“AI is about humans. The technology supports them,” Mr. Sbihli said. “You want applications that keep the human in control and improve the quality and speed.”
Best practices in improving operations
During the summit, healthcare leaders stressed the importance of change management and involving front-line staff in any operational changes.
Technologies or initiatives often fail when they are imposed on staff. A better approach is to understand staff members’ situations, pain points and workflows and then work closely with staff on solutions. Keys to success include frequent communication that focuses on the “why” and the benefits behind changes or new technologies.
“Having the front lines understand the why helps adoption,” Ms. Barr said.
Other best practices include incorporating implementation science into every operational change, which includes de-implementing technologies that are no longer in use.
Finally, a best practice is not to implement a new technology and then to give up on it if it is not quickly producing the desired results, but to test, tweak and iterate.
While healthcare operations today are often fragmented, siloed and inefficient, it is increasingly possible to identify specific pain points where focused change management efforts and AI-based solutions can improve efficiency and deliver an operational and financial return.
To learn more about symplr, visit www.symplr.com.
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