Patient engagement has become a defining factor in care delivery as healthcare organizations face growing pressure to improve access, operational efficiency and the overall patient experience simultaneously. Digital health connectivity tools that support scheduling, communication and automation are playing an increasingly important role in addressing challenges such as no shows, administrative burden and fragmented care journeys.
We spoke with David Edwards, Chief Technology Officer at Relatient, to explore how health & care organizations are approaching connectivity, the practical role of AI and why operational efficiency remains central to building sustainable, patient-centered systems.
What will be the key driver of digital health in 2026?
This will be the year of technology connectivity. The digital health landscape is broad, and providers and vendors are increasingly intersecting to form partnerships that strengthen how systems work together. While much of the attention is on AI, the real differentiator in 2026 will be the quality of APIs and plug-and-play integrations. Organizations that connect industry-leading solutions across multiple domains will gain the greatest advantage. By building connectivity tech stacks that are both flexible and aligned to their unique operational needs, health organizations can create a more cohesive and effective digital ecosystem.
How is AI transforming healthcare interactions?
While AI has been around in healthcare for decades, specifically in the area of machine learning, the rising popularity of LLMs is creating some very interesting opportunities for innovation. Ambient listening, for example, aims to solve a growing problem where clinicians are increasingly burdened by documentation demands. This technology will enable patients and clinicians to spend more time having meaningful conversations by making software conform to human behavior rather than humans conforming to software. Voice AI such as Relatient’s Dash is a similar kind of innovation in that it fundamentally changes the way we interact with software. This type of agentic AI technology is quite compelling when it integrates with systems of record, such as EHRs and PMs. The software agent is able to understand intention and manage context throughout the dialog, ultimately carrying out an appropriate transaction with the underlying system of record, such as rescheduling an appointment. Without this level of context and connectivity, voice AI is little more than interesting technology.
What challenges and opportunities exist in healthcare technology adoption?
My primary concern is the slower pace of innovation stemming from the strong grip of incumbent EHR and PM providers. Particularly among larger vendors, these systems are broad in functionality and just good enough to keep emerging innovators from competing for share of wallet. In many respects, it is easier and less costly for a health system to work with a single vendor as opposed to pursuing best-of-breed systems. But the tradeoff is a marketplace that will not produce the best possible innovation. Expecting a single vendor to provide optimal solutions in all areas is unrealistic. Competition drives innovation. The movers and shakers in healthcare must demand better.
How do lessons from other industries apply to healthcare technology?
An interesting observation after being a CTO for a number of years is that the nature of the problems you solve tends to be very similar across industries. Even though healthcare is quite complex and highly regulated, when it comes to leading and operating a software development organization regardless of industry, you often find that similar playbooks apply. At Relatient, our mission is to create a simpler experience for people accessing the healthcare system. While certainly aligned to that foundational goal as CTO, I tend to focus much of my time on creating organizational and procedural efficiency to ensure our product development engine is working optimally.
How do you identify and address inefficiencies?
Every company has some degree of friction and waste buried in structures and processes, so the challenge is finding the root causes. An effective innovation engine relies on recognizing and removing those inefficiencies. At my prior company, Vendavo, I led an agile transformation initiative that compressed release cycles from four months to three weeks. The transformation took about six months, but not only did we streamline the development process, we simultaneously improved the software quality and delivery predictability. A similar kind of transformation is currently underway at Relatient, and we have already begun to see those efforts yield benefit.
How will you measure success in 2026 and beyond?
I am fascinated with eliminating waste and friction. My primary measure of success is always looking at the long-term impact of key decisions. Something like a process transformation may require many months of effort and lots of obstacles along the way, but if the outcome is a materially improved organization, then I find that to be deeply rewarding.
For more information, visit relatient.com. Relatient engages with over 50 million unique patients on behalf of provider groups and health systems nationwide each year.
