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Implementing artificial intelligence (AI)-supported communication tools in healthcare: System-level perspectives.
Carmen M Diaz1, Kelly L Reed1, Laura E Barnes2
1University of Virginia School of Nursing, Charlottesville, VA, US.
Digital Health
|June 29, 2026
Summary
Artificial intelligence (AI) can improve patient-clinician communication by analyzing conversations and providing feedback. Successful implementation requires integrating AI tools into healthcare systems and involving diverse experts.
Area of Science:
- Healthcare technology
- Artificial intelligence in medicine
- Communication science
Background:
- Quality patient-clinician communication is essential for optimal health outcomes.
- Advancements in artificial intelligence (AI) offer new possibilities for evaluating and supporting communication.
- CommSense is an AI tool designed to analyze clinical conversations and provide feedback to clinicians.
Purpose of the Study:
- To explore system-level considerations for implementing communication technologies in healthcare.
- To use the CommSense AI tool as a case study for implementation.
Main Methods:
- A descriptive qualitative study was conducted.
- Purposive sampling recruited 13 participants with communication expertise (administrators, industry, policymakers, scientists).
- Semi-structured interviews explored communication barriers and technology implementation factors, analyzed via inductive and deductive coding.
Main Results:
- Barriers identified include inadequate training, generalized patient communication, and hesitancy with sensitive topics.
- Implementation requires integrating AI tools into existing infrastructure, workflows, and policies.
- Engaging champions and intentional feedback design are crucial; AI tools benefit trainee learning.
Conclusions:
- AI-supported communication technologies can overcome persistent healthcare communication barriers.
- Involving decision-makers and external experts across domains is vital for successful AI tool implementation in complex healthcare systems.
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