Bridging Digital Health and Nursing Informatics: A Look Ahead
Digital health and artificial intelligence (AI) are poised to reshape healthcare, but their success hinges on workforce preparedness, seamless interoperability, and ethical considerations. At HIMSS25, leaders like Whende M. Carroll, Clinical Informatics Advisor and HIMSS Fellow, addressed the critical factors shaping the future of digital health. The discussion, moderated by Morgan Searles, Senior Manager of Strategic Communications at HIMSS, highlighted the need for a human-centered approach to digital transformation that empowers clinicians.

Three Pillars of Digital Health Transformation
Carroll identified three key areas of focus for informatics professionals:
- Long-Term Vision: Resist fragmentation, focus on a holistic approach to digital transformation that connects data, AI, and patient-centered care.
- Patient and Provider Focus: Digital health should amplify care, not just introduce technology. AI should refine clinical workflows without replacing human interaction.
- Ethical Intelligent Automation: Align governance, workflows, and ethics as AI gains momentum. AI should augment, not dictate.
Breaking Down Silos
A significant challenge is the gap between clinical expertise and technology development. Many initiatives lack frontline provider input, leading to inefficiency and poor adoption rates.
”Nursing informatics isn’t just about working with EHRs,” Carroll stated. “We are technically savvy professionals who bridge clinical practice, technology, and policy. It’s time for non-clinicians to understand the full scope of what informaticists do.”
Carroll advocated for collaboration among policymakers, data scientists, engineers, and clinicians.
The Next 3-5 Years
Over the next five years, AI will play a role in:
- Data Connectivity & Interoperability: AI-powered automation will help standardize and map healthcare data, connecting different systems.
- Patient and Provider AI Literacy: Clinicians and patients must become well-versed in using AI-driven insights.
- AI-Driven Risk Detection: Real-time AI analysis can identify risk factors, care gaps, etc.
Interoperability Challenges
Interoperability remains a persistent barrier.
“Interoperability remains the biggest frustration for everyone—clinicians, patients, administrators, and policymakers alike,” Carroll said. “Without breaking down data silos, we cannot fully realize the benefits of AI and digital health.”
Carroll pointed out that market-driven solutions could drive the most meaningful changes.

AI and the Workforce
Addressing workforce concerns, Carroll emphasized that AI should assist, not replace.
“We need more nurse-led, clinician-driven AI solutions,” she stated. “AI should empower nurses and providers at the bedside, not create additional layers of administrative burden.”
Ethical Concerns with AI Terminology
The discussion also raised concerns about AI-driven healthcare chatbots being marketed as ‘nurses’.
“We should never deceive the consumer,” Carroll asserted. “Calling an AI-powered tool a ‘nurse’ misleads patients. Nursing is a licensed profession requiring education, exams, and certification—AI is not a substitute for human expertise.”
Looking Ahead
Carroll concluded by emphasizing governance, education, and standardization.
“We need a common digital health language, better workforce preparedness, and stronger interoperability standards,” she said. “AI isn’t just about efficiency—it’s about keeping the human touch in healthcare while leveraging technology to enhance care quality.”
In summary, the future of digital health depends on people, workflows, and the ethical application of AI. As healthcare evolves, collaboration among industry leaders is critical to ensure that AI and digital health transformations benefit all stakeholders.