https://www.healthleadersmedia.com/ceo/why-atlantic-healths-ceo-treating-innovation-cultural-shift?utm_source=HealthLeaders&utm_campaign=a4087c949a-EMAIL_CAMPAIGN_2026_05_28_01_19&utm_medium=email&utm_term=0_adc94e5966-a4087c949a-532959885&mc_cid=a4087c949a&mc_eid=71a6a1464f

Saad Ehtisham says the nonprofit health system is looking beyond typical ROI benchmarks for determining worthwhile investments in AI and digital tools for operational growth.

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KEY TAKEAWAYS

Atlantic Health views innovation as an organizational and cultural transformation effort rather than simply a technology initiative.

The system’s AI investments are focused on reducing friction across care delivery, including clinician documentation burden and patient scheduling delays.

CEO Saad Ehtisham sees workforce resilience and consumer access as long-term strategic returns, alongside traditional financial performance metrics.

For many health systems, innovation has become shorthand for digital expansion and AI deployment designed to create a return on investment. At Atlantic Health, president and CEO Saad Ehtisham frames that approach in another way.

“We’re looking at innovation much differently than most systems are and not as a tool, but as a cultural shift,” Ehtisham told HealthLeaders.

That philosophy is driving the New Jersey-based health system’s use of technology to improve workflows for clinicians while simplifying access for patients.

Investment, according to Ehtisham, is flowing into ambient listening tools, workflow automation, digital scheduling capabilities, and AI applications aimed at reducing friction across care delivery.

A Happier Workforce is a Better Workforce

One of Atlantic Health’s biggest strategic priorities involves workforce sustainability.

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The system has emphasized upskilling employees and encouraging leaders to think beyond traditional operational silos, Ehtisham highlighted. The organization wants managers and staff members to develop enterprise-level understanding that allows them to grow internally rather than looking for opportunities outside the system.

“What we want to do is make sure our team members don’t stay in the vertical expertise that they’re framed in, but they have the ability to cross-train into a different vertical and be able to grow in their acumen,” Ehtisham said.

Technology investments have become integral to that workforce strategy.

Atlantic Health recently piloted ambient listening tools that document physician-patient conversations during appointments. While many organizations evaluate those platforms through productivity or revenue gains, Ehtisham is more interested in the impact on clinician experience and long-term sustainability.

“How does that make our clinicians’ and physicians’ lives a lot easier and their flow throughout the day?” Ehtisham said. “Does that reduce their pajama time where they can spend more time with their families instead of having to be in their computers?”

Atlantic Health is also exploring agentic AI capabilities that can respond to certain administrative patient questions through Epic’s MyChart platform. The goal is to reduce after-hours inbox management that contributes to physician burnout.

“It is increasing the resilience of our physicians and that will in turn increase their ability to want to practice longer and want to be with the system,” Ehtisham said. “So that’s our ROI. And I don’t think you can put a dollar value on that. You probably could, you get a mathematician, you can quantify that through some algorithm. I would rather not.”

That same mindset has influenced nursing operations.

Atlantic Health has deployed robots capable of retrieving supplies and handling tasks that frequently pull nurses away from bedside care, Ehtisham noted.

“Twenty-five percent of the time our nursing or any nurse in any health system is spending is non-patient facing,” he said.

By supplementing those activities through automation, the system can allow its team members to focus on taking care of the patient and performing at the top of their license.

As Ehtisham puts it, staff are more likely to produce 150% output if they’re working at 90% of their capability from a resource intensity standpoint, and happier in what they do.

Pictured: Saad Ehtisham, president and CEO, Atlantic Health.

Opening the Digital Front Door Wider

Atlantic Health’s innovation strategy extends into consumer access.

One of the earliest operational changes implemented under Ehtisham involved measuring the next available appointment within 30 days across clinics and reducing delays that prevented patients from getting timely care.

“That was one operational lever we pulled early on,” he said.

According to Ehtisham, improving appointment access generated gains in consumer experience while contributing to stronger financial performance.

“We’re beginning to see it from consumer experience,” he said. “They’re much happier being able to get in when they want to be seen.”

The system is now experimenting with on-demand self-scheduling capabilities designed to better connect patients with its ambulatory infrastructure.

Atlantic Health continues to expand outpatient locations anchored around primary care as well. Many of those sites include rotating specialty services, imaging, laboratory capabilities, and physical therapy offerings intended to create centralized outpatient destinations.

The organization’s digital ambitions also include patient-facing AI applications.

Ehtisham said Atlantic Health is looking at developing its own version of Claude or ChatGPT, capable of guiding consumers toward the appropriate level of care based on conversations occurring through the platform. He envisions systems eventually using those interactions to direct patients toward physician appointments or virtual visits while simultaneously transferring relevant information into the clinical workflow before the encounter begins.

“We know consumers are going on those platforms and typing in, ‘I have this, what should I be?’” Ehtisham said. “That’s a platform that’s being engineered by non-healthcare providers systems. We’d rather get into that technology.”

Keeping Financial Discipline in Focus

Even as Atlantic Health expands technology investments, Ehtisham acknowledged the tension many health systems face when balancing the pursuit of innovation with financial realities.

“Healthcare is the only place where you bring in technology, the cost goes up versus going down,” he said. “We’re trying to invert that thinking.”

That influences how Atlantic Health approaches vendor relationships and operational deployment. Ehtisham said the system prefers working more deeply with select partners capable of improving workflows end-to-end, rather than as a one-off.

He pointed to operational throughput as one example. The organization is evaluating how technology can reduce bottlenecks beginning in the emergency department and continuing through inpatient discharge processes. Smoother patient flow can improve experience while generating financial yield through shorter lengths of stay, Ehtisham stressed.

“It starts creating this pipeline of revenue streams and future predicted models that’s going to be coming through market share that you’re going to be gaining over time,” he said. “It doesn’t happen overnight. But you have to commit to what you’re trying to do.”

Innovation can’t happen without resourcing though, which is why Atlantic Health has dedicated annual capital dollars specifically toward technology investments tied to operational improvements.

“It’s more of a derivative,” Ehtisham said. “You’ve got to generate so much operating margin in order to invest in that,” creating a direct link between financial discipline and innovation capacity.

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Last week, J.P. Morgan hosted its 44th annual healthcare conference, with over 500 companies and 8,000 people in attendance to discuss health system performance, pharmaceutical trends, and new AI offerings. 

The State of the Healthcare Industry in 2026

Health systems outline current performance, future plans

According to STAT, many health systems took a measured tone at this year’s conference, focusing largely on stability and consistency, especially in the face of significant Medicaid funding cuts from the One Big Beautiful Bill Act.

“For me, it’s been about stabilizing,” said Kevin Smith, CFO of SSM Health. “Taking a look at the operations, doing a lot of blocking and tackling. Getting back to the basics.”

Separately, Paul Rathbun, outgoing CFO at AdventHealth, said that “[i]t all begins and ends with consistent financial performance.” He also emphasized sustainability and the importance of a solid foundation to handle future uncertainty.

As hospitals and health systems face financial challenges, many are focusing on boosting efficiency and reducing expenses. For example, Intermountain Health is focusing on optimizing its supply chain and simplifying healthcare with value-based arrangements.

Some health systems, like CommonSpirit Health, are planning to sell some facilities to help boost finances and expand ambulatory networks. Providence is also considering selling some of its assets, potentially including some hospitals.

“We have 51 hospitals, most of which have No. 1 market share in their communities, but we do have a handful that we may have to find a different purpose or different sponsors for,” said Providence CFO Greg Hoffman.

Other health systems, like Mass General Brigham and Hackensack Meridian, are aiming to expand their partnerships with other providers or outside organizations. Currently, Mass General Brigham has a new ambulatory care venture with Tampa General Hospital, and Hackensack Meridian is planning to add 20 new primary care clinics in New Jersey with Amazon One Medical.

Top CMS officials meet with hospital, insurance leaders

At the conference, CMS Administrator Mehmet Oz, along with four top members of his staff, hosted an event with hundreds of top hospital and health insurance leaders to discuss the Trump administration’s healthcare policies.

During the event, Oz downplayed the potential impact of upcoming Medicaid cuts, saying that they won’t be felt for at least a year and a half. “The catastrophizing over the idea that it’s going to rip the guts out of the system, I don’t think that’s fair,” he said.

CMS leaders also discussed efforts to combat fraud, the Trump administration’s focus on deregulation, recent vaccine changes, and more. 

“The catastrophizing over the idea that it’s going to rip the guts out of the system, I don’t think that’s fair.” 

According to David Joyner, CEO of Hill Physicians Medical Group, the general mood among attendees was skeptical and pessimistic, particularly about cuts to Medicaid and the impact of declining Affordable Care Act membership. At the same time, people were curious and optimistic about CMS’ potential to promote new innovation and technology that could address some of the healthcare industry’s most persistent challenges. 

AI offerings continue to expand

AI was a large focus of the conference, with many organizations announcing new tools or collaborations.

At the conference, Anthropic announced Claude for Healthcare, a new AI model that includes HIPAA-ready infrastructure for enterprise customers, native integration to commonly used medical and scientific databases, and a model specifically trained for healthcare and life sciences tasks.

The new model follows Claude for Life Sciences, which was launched last October. Anthropic also announced new capabilities for life sciences, which ranged from preclinical research and development and regulatory affairs.

According to Eric Kauderer-Abrams, head of biology and life sciences at Anthropic, healthcare and life sciences are one of the company’s largest bets.

“Anthropic is a very natural fit for the healthcare and life sciences world because our identity as an AI company is built around safety and responsibility and rigor and reproducibility, and these are all the central tenants of the healthcare and life sciences industries,” Kauderer-Abrams said.

Currently, several healthcare organizations already use Anthropic’s Claude model, including Banner Health, Novo Nordisk, and AbbVie. At the conference, Elation Health announced that it integrated Claude into its EHR to create chart summaries and clinical insights.

Other AI companies at the conference also announced new expansion efforts. For example, Hippocratic AI, which develops patient-facing generative AI healthcare agent, said it acquired Grove AI, a startup that provides agentic AI for pharma research and development and clinical trial operations. According to Hippocratic, the acquisition will help it build its life sciences division and accelerate the use of generative and agentic AI in the biopharma and med tech sectors.

Separately, Open Evidence said it plans to move toward “medical super-intelligence” by building its AI platform on top of a group of specialist medical AI models (oncology, neurology, radiology, etc.) instead of a single centralized model.

Pharma companies discuss new products, drug pricing deals

According to Johnson & Johnson (J&J) CEO Joaquin Duato, 2026 should be a better financial year for the company as it focuses on three high-growth areas for its med tech business: cardiovascular, surgery, and vision. Currently, J&J has around a dozen upcoming product launches across its med tech and innovative medicine businesses, including its new Ottava Robotic Surgical System.

Separately, BioNTech, which is most known for developing a COVID-19 vaccine with Pfizer, is turning its attention to cancer treatment. The company has an $11 billion partnership with Bristol Myers Squibb for its bispecific PDL1-VEGF antibody.

Pharmaceutical leaders also discussed the “most favored nation” (MFN) deals they signed with the Trump administration to reduce the prices of certain prescription drugs.

Paul Hudson, CEO of Sanofi, said that while it may sound like everyone won with these deals, there were compromises from both sides.

“I would say the government got what it needed, and we worked very hard to make sure that we could still deliver what we think is an attractive investment thesis for the company without breaking stride,” Hudson said. “So it was a very difficult needle to thread. I don’t want to give the impression that there’s no impact from MFN, because the question for us is: Can we manage that and deliver an attractive long-range plan?”

Christopher Boerner, CEO of Bristol Myers Squibb, had a similar view. “​​I think what we did with the agreement we signed at the end of last year is find a way to balance the interest of the administration in ‘most-favored nation’ with, obviously, what’s best for the company, but importantly, how can we find ways to provide real value to patients?”

The digital health market ramps up

In 2025, digital health investments reached $14.2 billion in funding, a 35% increase from 2024 and the highest total since 2022. Last year, there were 26 megadeals, or those that raised over $100 million, and 15 new “unicorn” companies, or those valued at over $1 billion, up from just six in 2024.

Although the digital health market is still below its pandemic-era peak, there was significant growth in the market in 2025, largely driven by excitement around AI, according to analysts from Rock Health. The analysts also noted that there is a growing concentration of power in the digital health space, with certain companies having outsized influence.

“On one side, AI-native upstarts attracted huge rounds at unprecedented speed, a handful of companies broke the IPO drought, and private equity made major moves, signaling real bets on an emerging ‘winner’ class,” wrote Rock Health analysts Megan Zweig, Jacqueline Kimmell, and Maddie Knowles. However, on the other side, “… many companies are still grappling with valuation overhangs from prior cycles while operating in a more competitive market.”

https://juliolatorremd.substack.com/p/the-slow-death-of-epic-systems?utm_source=multiple-personal-recommendations-email&utm_medium=email&triedRedirect=true

The software monopoly that powers American hospitals wasn’t built for the data, speed, or intelligence the future of medicine demands.

Epic Systems is an American privately held healthcare software company, founded by Judy Faulkner in 1979, and has grown into the largest electronic health record (EHR) vendor by market share, covering over half of all hospital patients in the U.S.

Epic dominates American healthcare today. But so did Kodak in photography and GE in industry. Its software runs the country’s hospitals, determines the workflows clinicians, nurses and clinical support staff use, and shapes what data gets captured (or more often, what gets lost). It also serves as the front door for healthcare data for the patients it serves. Dominance has never guaranteed a future. Epic’s position reflects the architecture of the past, not the one emerging now.

More importantly, the sheer volume of activity occurring in these hospitals means they are collectively running thousands of experiments, mini clinical trials, and critical observations daily. The stakes are enormous: billions of dollars in drug discovery, the efficiency of clinical trials (currently plagued by poor recruitment and high costs), and the potential for better, personalized care. The data generated in these environments is the single most valuable, untapped resource in all of medicine.

However, this monumental source of value is being throttled by outdated infrastructure, and it shows. It’s hard to imagine a world where AI is used to its full potential in healthcare while Epic is still running the show. The ideas are oppositional at their core.

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The Massive Data Problem

Technology is accelerating faster than any legacy system can keep up with. AI is reshaping every major industry, and healthcare will be forced to catch up. However, this essential transformation is structurally incompatible with the dominant system of record.

To put it bluntly: Epic has a data problem. A massive data problem. Not just imperfect data — structurally flawed data. What Epic captures is fragmented, delayed, and riddled with inconsistencies. Diagnoses become billing codes that distort reality. Interventions like intubations, pressor starts, and ventilator changes appear hours late, if at all. Outcomes are incomplete or missing. What remains isn’t a clinical record in any meaningful sense but a billing ledger dressed up as documentation. No model can learn reliably from that.

But the deeper problem is the data Epic never sees. Some of the most valuable information in modern medicine: continuous monitoring streams, ventilator logs, infusion pump data… never enters the EHR in a structured or analyzable form. In many cases, it isn’t captured at all.

I recently brought Roon (a well-known engineer at OpenAI) and Richard Hanania (a public intellectual/cultural critic)—both advisors in my new venture, in full disclosure—to one of the largest academic medical centers in the country. Both watched torrents of millisecond-scale data spill off monitors. Streams that could reveal what’s happening in the brain, heart, and vasculature. Valuable data… all vanished instantly. None of it logged. None of it stored. None of it correlated with outcomes. Roon captured this shock in a viral post on X/Twitter, essentially describing how hospitals are filled with catastrophic events like sudden cardiac death, yet we save none of the time-series data that could teach us how to prevent the next one. His shock distilled what people in technology grasp immediately and what healthcare has normalized: industries where human life isn’t exactly top of mind record everything; hospitals, where the stakes are life and death, learn almost nothing from themselves.

In Silicon Valley, losing data like this is unthinkable. In healthcare, it barely registers.

Epic was never built to ingest or learn from this scale of data. It was built to satisfy billing requirements, regulatory checklists, and documentation workflows. That is the beginning and end of its architecture. It is not a learning system, much less an AI system. It is not even a modern data system. And that is the root of Epic’s downfall.

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The Cultural and Financial Moat

Epic is famous for its internal commandments — principles Judy Faulkner wrote decades ago:

• Do not acquire.
• Do not be acquired.
• Do not raise outside capital.

(If you haven’t heard it, the latest Acquired podcast episode on Epic is essential listening)

But the same rules that built its empire now limit what it can become. What was once a strategic strength is now its ceiling.

The next era of healthcare software demands investments that were unnecessary when the EHR was the center of gravity. Building AI-native infrastructure: real-time data pipelines, device integrations, large-scale compute, continuous model training, semantic normalization — requires not millions but tens of billions of dollars. Most companies facing that kind of leap can raise capital, acquire talent, or merge with partners. Epic has ruled all of those options out.

Epic’s formidable market share is anchored by a massive customer sunk cost. With implementation fees often exceeding a billion dollars for large systems, the financial and political inertia makes replacing the EHR functionally unthinkable. However, this commitment only forces customers to defend an obsolete data architecture. By preventing them from adopting novel solutions, this inertia doesn’t protect Epic’s long-term viability, it simply guarantees a widening technical gap between the EHR and the transformative potential of AI.

A company optimized for slow, controlled expansion cannot transform itself into an AI-scale enterprise without violating the principles that define it. The culture that kept Epic dominant is the culture that prevents it from catching the next wave. Epic will continue to excel at documentation, billing, and compliance — but those strengths are anchored in the past. The future belongs to systems that learn, and Epic was never designed to learn.

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The Shift to Middleware

Meanwhile, the broader economy is being held up by AI. The world’s largest tech companies are pouring staggering sums into compute, data centers, and model training. And all that compute needs rich, complex, high-value data to train on.

Healthcare is the only remaining frontier of that scale.

No other industry generates so much information while analyzing so little of it. No other sector represents nearly 20% of U.S. GDP yet still runs on fragmented workflows and manual processes. And the incentives here are unmatched: improving patient outcomes, reducing costs, eliminating inefficiency, accelerating drug development, modeling disease trajectories, and eventually automating the more repetitive layers of care. There’s even an irony: the very infrastructure needed to enable learning health systems would also finally make billing more accurate.

I’m not writing this to showcase some utopian vision of AI curing all disease. It’s the practical use of technology we already possess. Our limitation isn’t the models; it’s the missing data.

A handful of companies have bet their trillion-dollar valuations on this: OpenAI, Google, Amazon, Nvidia, Apple, Oracle. They are spending hundreds of billions a year on AI infrastructure and need high-volume, high-quality datasets to justify that investment. Healthcare produces oceans of exactly that kind of data, and most of it evaporates. The companies that learn to capture and structure it will define the next layer of healthcare infrastructure. Whether they integrate with Epic, build around it, or replace it is almost secondary.

What matters is that none of them are waiting for Epic.

Clinicians won’t either. Once tools exist that unify the data hospitals already generate, reduce workload, eliminate administrative drag, and answer the questions clinicians actually ask — What happened? Why did it happen? What should we do now? — the center of gravity will shift. Clinicians will live inside those tools, not inside an interface built for billing.

Epic can still exist, but it doesn’t need to function as healthcare’s operating system. There’s precedent for this in every major industry: the core orchestration/data layer eventually recedes into the background while workflow and data intelligence move up the stack. At that point, the EHR becomes background infrastructure or middleware. The intelligence/workflow layer becomes the real operating system. Epic will undoubtedly resist this shift, yet its attempts to maintain total control of the clinician interface will ultimately collide with the utility and data gravity of AI-native systems.

Epic becomes the backend: essential, invisible, and no longer the place where the practice of medicine occurs.

Regulatory modernization around HIPAA, interoperability, and data liquidity will be essential, but that is a conversation for another essay.

Epic isn’t vanishing tomorrow. Large institutions rarely do. But its relevance is eroding in the only domain that will matter over the next decade: the ability to harness data at a scale and fidelity that makes AI transformative. It can keep its commandments, preserve its culture, and reject outside capital — it just can’t do all that and remain the central platform of hospital data in an AI-native future.