Two-thirds of patients have little confidence that their health system will use artificial intelligence responsibly, according to a report in MedCity News. The findings, based on research by Yuliia Apanasenko, CEO of Phenomenon Studio, point to a design problem - not a technology problem - as the root cause of widespread AI mistrust in healthcare.
Sixty-six percent of patients said they have little confidence their health system will use AI responsibly. Another 58 percent doubt health systems will protect them from AI-related harm. A separate Accenture study found that patients in the United States are twice as likely to leave a provider over poor digital service experiences than over substandard medical care.
Poor portal design drives the trust gap
"One in four patients refresh online portals while waiting for test results," Apanasenko said. "Frequent refreshers are more likely to message their doctor afterward, even for routine tests." The author argued this is a system design failure, not a sign of patient impatience.
Portal results presented without context create confusion. Visual scales that compare patient values to normal ranges reduce unnecessary follow-up messages. Apanasenko identified four specific Design patterns that erode patient trust: ignoring the patient's anxious state, delivering results without clear next steps, using inappropriate language, and mismatching tone with patient needs.
The divide between patients and health systems adopting AI is fundamentally a design problem, according to Apanasenko. Poorly designed portals that deliver lab results without context - whether data is raw, system-interpreted, or doctor-confirmed - drive the gap. The same principles apply whether the patient-facing layer is built in-house or through an outsourced engagement team.
Four design patterns that erode trust
Portals need to distinguish between raw data, system interpretations, and doctor-confirmed findings. Patients should see visual scales that show values relative to normal ranges, not just numbers. Apanasenko's recommendations include creating guided pathways rather than distributing data, maintaining an honest tone, and explaining how AI conclusions were reached.
"Design choices determine whether patients engage with or disengage from digital health tools," Apanasenko said. For health systems managing this trust gap, investing in the patterns - guided pathways, transparent AI reasoning, and clear data labeling - is the path forward. Offshore teams trained in US healthcare workflows that are training in digital empathy can help, but the design layer itself must earn trust first.
Why this matters for healthcare professionals
Healthcare professionals who manage patient communication systems need to audit their portal's design for the four trust-eroding patterns identified in the report. Digital empathy practices - tone matching, clear next steps, and visual comparators - directly impact whether patients message their doctors and whether they stay with their providers. The financial stakes are concrete: get outsourced service teams or build better portals using AI for Healthcare design courses to address the root cause, or risk patients leaving for providers with better experiences.
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