66% of patients don’t trust AI in healthcare: report
NEW YORK, UNITED STATES — Two-thirds of patients have little confidence that their health system will use artificial intelligence (AI) responsibly.
AI mistrust threatens digital health adoption
Sixty-six percent of patients have little confidence their health system will use AI responsibly, while 58 percent doubt health systems will protect them from AI-related harm.
Separate Accenture research 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.
According to Yuliia Apanasenko, Chief Executive Officer of Phenomenon Studio, writing in MedCity News, One in four patients refresh online portals while waiting for test results, and frequent refreshers are more likely to message their doctor afterward, even for routine tests. Apanasenko argues this behavior reflects a system design failure, not patient impatience.
According to Apanasenko, poor portal design that delivers results without context drives the trust gap between patients and health systems adopting AI. The divide is, they argue, fundamentally a design problem.
Patients in the United States are twice as likely to leave a provider over poor digital service experiences than over substandard medical care, according to Accenture research.
Transparent design rebuilds healthcare AI trust
Apanasenko identifies four 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.
Portal results presented without context create confusion, while visual scales showing values relative to normal ranges reduce unnecessary follow-up messages.
To close the trust gap, Apanasenko recommends creating guided pathways rather than distributing raw data, maintaining an honest tone, and explaining how AI conclusions were reached. Systems should also distinguish between raw data, system interpretations, and doctor-confirmed findings.
Writing in MedCity News, Apanasenko concludes that design choices determine whether patients engage with or disengage from digital health tools. The same principles apply, they argue, whether the patient-facing layer is built in-house or through an outsourced engagement team.
Apanasenko identifies guided pathways, transparent AI reasoning, and a clear distinction between data, system interpretations, and doctor-confirmed findings as the design features most likely to earn patient trust.
For health systems managing the trust gap, outsourcing revenue cycle management (RCM) and communication workflows to business process outsourcing (BPO) partners offers a path to cost-efficient patient engagement. Offshore teams trained in U.S. healthcare workflows manage portal communications, appointment follow-up, and test result outreach with the human context digital tools lack.
As health systems invest in AI-powered outsourcing solutions, the principles Apanasenko identifies are increasingly embedded in how vendors structure patient support. Firms among the top healthcare outsourcing companies in the United States are training offshore teams in digital empathy practices that the technology layer alone cannot deliver.
Related news
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- Healthcare digital experience makes or breaks member trust: mPulse · 31 Jul
- 92% of health leaders want AI vendors with deep expertise · 30 Jul
Disclosure: Outsource Accelerator uses AI tools in the backend of its editorial workflow. Every article is reviewed and verified by a human editor before publication.
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