Understanding Providers' Attitude Toward AI in India's Informal Health Care Sector: Survey Study

Area of Science:

• Medical Diagnostics
• Artificial Intelligence in Healthcare
• Global Health

Background:

• Tuberculosis (TB) remains a significant global health challenge, with millions of deaths annually.
• Current TB diagnostic methods often face limitations in accuracy, cost, and accessibility.
• AI-augmented chest x-rays present a promising alternative for improved TB diagnosis.

Purpose of the Study:

• To assess the adoption attitudes of Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homoeopathy (AYUSH) and informal healthcare providers (AIPs) towards AI for TB diagnosis in India.
• To understand the factors influencing AIPs' willingness to integrate AI into their TB diagnostic practices.

Main Methods:

• A cross-sectional survey was conducted with 406 AIPs in Jharkhand and Gujarat, India.
• The survey assessed provider confidence, trust in radiologists, beliefs about AI capabilities, and willingness to adopt AI for TB diagnosis.

Main Results:

• A high percentage of AIPs (93.7%) believed AI could enhance TB diagnostic accuracy.
• Overall willingness to try AI was 69.4%, but varied significantly between Gujarat (73.4%) and Jharkhand (58.4%).
• Trust in local radiologists showed contrasting effects on AI adoption willingness between the two states.

Conclusions:

• Despite recognizing AI's potential, a gap exists between perceived benefits and actual adoption intent among AIPs.
• Targeted interventions focusing on improving provider confidence and addressing regional infrastructural disparities are crucial for successful AI implementation.
• Enhancing beliefs among providers with limited access to radiology services can maximize AI's impact on TB diagnosis.