Part 9 of Talencio’s Series, “Navigating 2026: The Top 10 Health Technology Trends Every Leader Should Watch”
The traditional healthcare system was built around encounters. Patients came in, clinicians gathered information, decisions were made and everyone moved on until the next visit.
Increasingly, technology is filling in what happens between those moments—and creating a much more continuous view of a patient’s health.
Heart rhythms. Glucose. Sleep. Movement. Blood pressure. Medication adherence. Mood. Rehabilitation progress. Some of it is collected continuously, some passively, and increasingly, algorithms are helping decide which signals deserve attention.
This may seem like a story about consumers and their devices, but it’s really a story about how care itself is changing.
Consider today’s experienced primary care physicians. When they entered medicine, a patient encounter was largely episodic: an office visit, a set of vitals, perhaps a lab test, followed by a treatment decision and another scheduled encounter.
Few envisioned a future in which caring for that patient could also mean interpreting remotely generated data, understanding algorithmic recommendations, responding to alerts, coordinating with technology-enabled care partners and determining how—and whether—to bill for activities occurring outside the exam room.
Nonetheless, that future has arrived.
A 2026 AMA and Medscape survey of more than 2,200 physicians in six countries found broad interest in wearable health information, but also significant concerns around payment, liability, evidence, and clinical integration. In the U.S., 77% of physicians saw potential advantages for patient care. But the gap between interest and operational reality is striking. Among the specialties surveyed, only 2% of primary care physicians said wearable data was currently integrated into their clinical workflows.¹
That gap is where one of health tech’s biggest opportunities—and responsibilities—now sits.
Continuous data creates continuous questions
The appeal of continuous health technology is easy to understand. Instead of assessing patients through intermittent snapshots, clinicians can spot patterns across hours, days, and months.
That can be transformational. It can identify deterioration earlier, help personalize treatment, reinforce healthy behaviors, and give patients greater agency in managing chronic disease.
But an always-on health system also creates questions an episodic system rarely had to answer:
- If a device detects something concerning at 2am, who’s responsible for acting on it? How quickly?
- Which alerts merit intervention?
- When does a signal become clinically actionable?
- If an algorithm suppresses an alert that ultimately mattered—or elevates dozens that do not—where does accountability reside among the clinician, health system, and technology developer?
These questions aren’t theoretical. In July, researchers studying continuous at-home vital-sign monitoring found a median of 74 alerts per patient per day before clinical filters were applied. Severity- and duration-based filtering reduced that figure by 84%, to five alerts per patient per day.²
Another recent study of remote monitoring embedded in pulmonary rehabilitation found strong patient acceptance but added roughly 45 minutes of staff workload per participant to respond to generated alerts.³
More information is valuable only if a care model can absorb it.
That makes thoughtful algorithms, escalation rules, staffing models, and workflow design as important to the product as the sensor itself.
It also creates a developing liability question. The AMA has emphasized that AI should support rather than replace physician judgment and that accountability, transparency and physician oversight remain essential as algorithms enter patient care.⁴ Its recent work defining physicians’ roles in a digital and AI-enabled health system similarly reflects how technology is reshaping responsibilities around clinical judgment, care coordination and technology stewardship.⁵
For health tech companies, this means product development cannot stop at “Can we detect it?” Teams also must ask: “What should happen when we do?”
Integration may be the harder innovation
There’s another complication. Even an excellent technology enters a healthcare environment that already has plenty of technology.
In a recent Serious Talent® Chat, Jon Fletcher, President and CEO of Presbyterian Homes & Services, put the challenge succinctly: “Integration is harder than innovation.”
Health systems already operate across layers of electronic medical records, pharmacy systems, billing platforms, scheduling applications, communications tools, and monitoring technologies. Adding one more application may technically solve a problem while operationally creating another.
As Fletcher noted, innovators must be crystal clear about what their technology integrates with and what the resulting cost model looks like. Simply saying “We have AI” is no longer a meaningful value proposition.
His observation aligns with what health system technology leaders are saying more broadly.
Healthcare IT News recently described interoperability and application sprawl as major obstacles to scaling AI and digital tools, with leaders increasingly focused on simplifying technology stacks and redesigning workflows rather than simply deploying additional applications.⁶ HIMSS has made a related point: the industry has gotten better at moving data, but moving information between systems is not the same as making it coherent, contextual and usable at the point of care.⁷
For technology companies, integration is increasingly part of the product.
A clinically sophisticated solution that creates another login, dashboard or inbox may struggle versus a technically inferior competitor that fits seamlessly with how clinicians already work.
Reimbursement is evolving with the care model
Payment models are beginning to acknowledge this new reality as well.
Traditional Medicare remote patient monitoring already recognizes distinct work associated with patient education and setup, connected-device data collection, and treatment management.⁸ CMS also added remote therapeutic monitoring codes for 2026 covering shorter monitoring periods and treatment-management activity—another indication that digital intervention is becoming part of reimbursable care rather than an accessory to it.⁹
An even bigger development arrived this summer.
CMS launched its 10-year ACCESS Model in July. It created an outcome-aligned payment approach for technology-supported care involving conditions such as hypertension, diabetes, chronic musculoskeletal pain, and depression. Rather than simply paying for discrete activities, the model is designed primarily around whether patients achieve defined health improvements.¹⁰
FDA is coordinating with that effort through its TEMPO pilot for digital health devices. Selected manufacturers can generate real-world evidence while their technology is used within ACCESS-supported care, linking regulatory learning, reimbursement, and patient outcomes in a way worth closely watching.¹¹
That convergence should matter to every health tech executive.
The question used to be: “How do we get reimbursed for the technology?” Now it’s: “How does our technology participate in a care model that gets reimbursed for producing a better result?”
Digital therapeutics make the human touch more important, not less
Digital therapeutics take this evolution one step further because software is not simply measuring the intervention. In some cases, software is part of the intervention.
That creates enormous potential for scale, particularly where access to traditional services is limited. But recent evidence also reinforces an important lesson: digital care doesn’t necessarily mean eliminating people.
A July randomized clinical trial involving breast cancer survivors found that a smartphone-delivered digital mental health treatment produced greater reductions in anxiety symptoms than a psychoeducation application. Among participants who initially struggled to engage with the intervention, adding human coaching increased application use.¹²
That’s telling for leaders designing the next generation of care models. Technology can amplify human expertise without replacing every human interaction.
Technology companies should analyze their technologies and the experiences they create, assessing which parts should be digital, which require a person, and how they should work together.
Across the ecosystem
These questions matter across health technology.
For medical device companies, the value proposition increasingly includes what happens to the data generated around the device and whether it can improve care after the patient leaves the clinical setting.
For diagnostics companies, longitudinal information can provide context that an individual test cannot, potentially creating earlier signals and richer understanding of disease progression.
For biopharmaceutical companies, continuous measurement is moving deeper into drug development. FDA announced a funding initiative this summer exploring technologies including actigraphy, photography, and contactless sensors to capture early manifestations of disease, enable remote clinical-trial data acquisition and develop digitally derived endpoints.¹³
And for digital health and DTx companies, success increasingly depends on proving that engagement translates into something stakeholders value clinically and economically—not merely demonstrating that consumers will download an app or clinicians find a technology interesting.
That distinction matters in a market where capital remains available but increasingly selective. U.S. digital health companies raised $7.4 billion during the first half of 2026 but deals worth $100 million or more accounted for nearly half of funding.¹⁴
Alert teams for an always-on health system
The most difficult barriers to continuous digital health may therefore prove organizational rather than technological.
These companies need:
- Product leaders who understand clinical workflow.
- Clinical leaders who can engage with data science.
- Regulatory leaders who understand products that keep learning and changing.
- Market-access teams that can connect reimbursement to outcomes.
- Integration experts who understand the realities of health-system infrastructure.
- Commercial leaders who articulate value without being enamored with the tech itself.
They also need people willing to wrestle with uncomfortable questions:
- Which data deserves a clinician’s attention?
- Who watches when the physician is not?
- What constitutes an appropriate response?
- How much automation is too much?
- When does continuous monitoring improve care, and when does it just create constant noise?
- Who assumes responsibility when technology becomes part of the clinical decision?
Those are not reasons to slow innovation. They’re the questions that responsible innovation now requires.
Consumer-centric, continuous digital health has the potential to make healthcare more proactive, personalized, and accessible. But its significance extends far beyond putting more information into consumers’ hands.
It’s changing where care happens, when care happens, who participates in delivering it—and what those people are responsible for once health information never really turns off.
For health tech leaders, understanding that larger transformation may be the difference between building an interesting technology and building something the system is truly ready to use.
Sources
1. American Medical Association, Which Specialties Lead the Way on Using Wearable Data for Care (July 8, 2026)
4. American Medical Association, AMA Policies to Ensure AI Supports—Not Replaces—Physician Judgment (June 10, 2026)
6. Healthcare IT News, A Big Challenge for Healthcare AI: Simplify the Stack (July 15, 2026)
7. HIMSS, Five AI Signals from HIMSS26 That Will Shape the Next Era of Healthcare (April 23, 2026)
8. Centers for Medicare & Medicaid Services, Remote Patient Monitoring (May 13, 2026)
9. Centers for Medicare & Medicaid Services, Therapy Services — CY 2026 Therapy Services Updates (March 10, 2026)
14. MedTech Dive, Large Funding Rounds Help Boost Digital Health Investment in H1 (July 17, 2026)
About the Author
Paula Norbom is the Founder and CEO of Talencio, an executive search and staffing firm serving health technology companies. She has worked in the health technology industry for over 30 years.