Patients Want AI, So Long As There’s No Copay

Key Takeaways

• 80% chose AI when copay waived, vs 43% with $50 copay
• No difference whether insurer or developer waived the copay
• AI users three times more likely to seek doctor confirmation after abnormal
• Even with normal AI results, patients 50% more likely to request follow‑up
• Trust in AI remains lower than in human specialists

Pulse Analysis

The diabetic retinopathy market has become a proving ground for artificial intelligence, with several algorithms already cleared by the FDA and integrated into ophthalmology clinics. These tools can analyze retinal photographs in seconds, offering a scalable alternative to specialist examinations that are often limited by geographic access and appointment backlogs. However, the cost structure surrounding AI services—whether billed as a separate procedure or bundled into insurance plans—has received less scrutiny, despite its potential to dictate patient adoption rates.

The Johns Hopkins experiment reveals a classic case of price elasticity applied to health technology. When the $50 copay was eliminated, more than four‑fifths of participants opted for the AI screening, underscoring that even modest out‑of‑pocket expenses can deter usage. Yet the study also uncovers a paradox: patients who embraced the AI still pursued physician verification, especially after abnormal findings, and even after normal results they were 50% more likely to request a follow‑up. This behavior signals that cost savings alone will not replace the perceived need for human oversight, and that trust remains a critical barrier to full autonomous deployment.

For insurers and AI developers, the implications are twofold. First, eliminating or subsidizing copays could dramatically increase AI utilization, reducing overall screening costs and expanding reach to underserved populations. Second, building trust will require integrated care pathways that embed AI outputs within clinician workflows, perhaps through shared decision‑making tools or guaranteed physician review. Policies that align financial incentives with transparent validation studies and clear communication about AI accuracy may accelerate acceptance while preserving patient confidence, ultimately shaping the future landscape of digital diagnostics.