Bridging Innovation and Practice in the Digital Health Era

Health care systems are racing to integrate digital tools and artificial intelligence into clinical practice. Yet as new technologies proliferate, a fundamental question remains: which innovations will actually work in the real world of patient care—and under what circumstances?

That question sits at the center of the work of Ariel Stern, PhD, Chair for Digital Health, Economics & Policy, Hasso Plattner Institute, University of Potsdam, and Adjunct Professor, Windreich Department of Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai. 

Her research not only explores how reimbursement, regulation, and operational realities shape the success or failure of technology-enabled health care delivery, but also is a guiding theme behind the new Harvard Medical School certificate program, Technology-Enabled Care Delivery: From Digital Medicine to AI, which she developed alongside collaborator William Gordon, MD, MBI, FAMIA, Staff Physician, Brigham and Women's Hospital.

Stern, who previously spent a decade on the faculty at Harvard Business School teaching health care innovation and business models, says that the conversation around AI in medicine often overlooks the practical realities that determine whether a technology is ever meaningfully integrated into care.

“Just because we have a totally brand-new, slick, AI-driven diagnostic algorithm that has gone through an FDA certification process and is now on the market doesn’t mean that it’s suddenly going to be magically adopted in every hospital and clinic in the country,” notes Stern. “Indeed, the reality is quite the opposite.”

Why Some Technologies Succeed—and Others Fail

Stern’s work examines why some technologies flourish while others stall, despite promising clinical potential. Health care innovation is never simply about inventing a better tool, she explains. Success depends on a complex ecosystem that includes regulation, reimbursement policies, clinical workflows, and the realities of how health care organizations operate.

“It’s not just a random subset of good ideas that folks have come up with,” Stern says. “The set of new health care technologies we get is meaningfully shaped by the regulatory environment, by what funding is available, and by the historical institutions and rigidities we have in our health care system.”

Understanding those forces is becoming increasingly important as AI and digital health tools proliferate.

Reimbursement Matters

While many technologies promise to improve efficiency, expand access, or enhance clinical decision-making, their ultimate impact often depends on factors beyond technical performance. One example is remote patient monitoring, an area that Stern has studied extensively.

Remote monitoring programs allow clinicians to track patients outside traditional care settings using tools such as home blood-pressure cuffs, smart scales, and continuous glucose monitors. While the technology itself has existed for years, adoption accelerated significantly in the United States during the past decade. According to Stern, reimbursement policy played a major role.

“The fact that we saw a real uptick in the use of remote patient monitoring in the early part of this decade is not a coincidence,” she says. “It’s a direct result of the fact that since early 2020, there have been codes in the United States that allow for the direct reimbursement of these services by clinicians.”

This example also illustrates a broader principle that runs through Stern’s work: technologies often succeed not simply because they are effective, but because the health care system creates conditions that make adoption feasible.

Beyond Innovation: The Operational Reality

Even when reimbursement pathways exist, adoption can remain challenging. Implementing digital health technologies often requires managing major operational changes inside clinics and hospitals.

“If you’re asking a doctor who runs a small practice to adopt remote patient monitoring, you’re asking them to make a pretty big software adoption decision,” says Stern. “You’re asking them to now deal with incoming data from devices that patients are using outside of the practice.”

For health care organizations, successful adoption requires much more than purchasing a new technology. New workflows must be created, staff members must be trained, and data must be integrated into existing systems in ways that support clinical decision-making rather than adding administrative burden. 

Clinicians also need systems that make the data usable in day-to-day care. “We need this data to be easily viewable and usable,” she says. “We need an interface that clinicians and their staff like to use, because they will have to do so daily.”
Stern’s research suggests that when implemented effectively, technology-enabled care can meaningfully change patient outcomes and health care utilization patterns. Her team has analyzed large medical claims datasets to study how care changes after practices adopt remote monitoring technologies.

For example, patients enrolled in hypertension monitoring programs may visit practices more frequently and become more adherent to medications, while experiencing fewer serious complications requiring hospitalization. “They’re being admitted to the hospital much less frequently for strokes and heart attacks, which is exactly what you’d want,” notes Stern, “but we also need to understand the implications for the use of other services.”

A New Knowledge Gap for Clinicians

At the same time, Stern cautions that health care leaders must evaluate technologies thoughtfully rather than assuming that every new digital or AI-based tool automatically creates value.

“We have all this new tech, we have all these new mechanisms for paying for it, and then we’ve got a bunch of clinicians with the best of intentions trying to figure out what makes sense for them, what makes sense for their patients, and what makes sense for their clinic or hospital,” she says.

That challenge has only intensified as AI tools have become more sophisticated and widespread. Clinicians today are being asked to evaluate technologies that often did not exist during their medical training. “Even the best doctors in the world would not have learned about many of these technologies during their medical training that they’re now being asked to consider in their day-to-day lives,” says Stern.

The challenge extends beyond knowing how technologies work. Increasingly, health care leaders must understand how technologies are regulated, what evidence supports their use, and how they fit into broader organizational goals.

Fulfilling the Promise of Digital Health Care 

Stern believes that the conversation around digital health often focuses too heavily on the technologies themselves. In her view, the more difficult questions concern implementation: how organizations evaluate evidence, how new tools fit into existing workflows, and whether reimbursement and operational structures support their use.

“What data do we need to collect so that we actually can generate evidence that these tools work—and, if so, under what circumstances and for which patient groups?” she says.

As health care organizations continue to adopt AI-enabled tools, remote monitoring platforms, and digital therapeutics, Stern argues that success will depend not only on technological innovation, but also on understanding how these technologies create value in real-world clinical settings. 

Increasingly, the most important questions for health care professionals may not be technological. Instead, they will be economic, organizational, and operational: Which innovations create value? For whom? Under what circumstances? And how can health care systems ensure that promising technologies translate into meaningful improvements in patient care?

“It’s no longer just about what the technologies are, but how they translate for me as a practitioner and participant,” says Stern. Answering those questions, she believes, will ultimately determine whether the digital transformation of health care fulfills its promise.

Written by: Alice McCarthy