Signal Evaluating Ambient Clinical Scribes in India: The Need for Multilingual Real-World Clinical Conversation Data

Summary

Ambient clinical scribes are being rapidly deployed at scale across Global South healthcare settings, aiming to reduce clinician documentation time in overburdened environments such as India. However, these tools are primarily developed or distilled from models built and validated on Global North speech, languages and consultation styles. Indian clinical encounters tend to be brief and triadic, involving patient, caregiver and doctor, and are conducted in multilingual, code-mixed low-resource-language settings under noisy, resource-constrained conditions. These characteristics increase the likelihood of automatic speech recognition and note-generation errors when Global North-trained tools are applied. The authors posit an urgent need for real-world, multilingual clinical conversation datasets collected in Indian settings to properly evaluate and improve these tools.