365Telugu.com online news,National, February 20, 2025: A study conducted by the Max Institute of Healthcare Management (MIHM) at the Indian School of Business (ISB) has shed light on the attitudes of healthcare providers toward artificial intelligence (AI) in tuberculosis (TB) diagnosis.
The findings highlight both the potential of AI-driven solutions and the challenges in their adoption within India’s informal healthcare sector.
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Published in JMIR Formative Research, a peer-reviewed journal, the study-titled “Understanding Providers’ Attitude Toward AI in India’s Informal Health Care Sector: Survey Study”-surveyed 406 practitioners from Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy (AYUSH), along with informal healthcare providers (AIPs) across Gujarat and Jharkhand.
The results revealed a contrast between belief and adoption: while 93.7% of respondents acknowledged AI’s potential to improve TB diagnosis accuracy, only 69.4% expressed willingness to integrate the technology into their practice.
Key Insights & Regional Disparities
Lead author Professor Sumeet Kumar, Assistant Professor of Information Systems at ISB, noted that while AI’s technological advantage is recognized, successful implementation depends on multiple factors, including infrastructure and regional differences.
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The study found that adoption readiness was higher in Gujarat (73.4%) compared to Jharkhand (58.4%), reflecting the role of healthcare infrastructure development in AI acceptance. Additionally, providers with greater confidence in diagnosing TB were more inclined to adopt AI tools, while trust in local radiologists influenced AI adoption differently across regions.
TB Burden and AI’s Role in Diagnosis
Tuberculosis remains a significant global health challenge, with 1.5 million deaths reported in 2020, and India accounting for a substantial portion of cases. While molecular diagnostic tests offer high accuracy, they are costly and difficult to access in many regions.
AI-powered chest X-ray (CXR) scans provide a promising alternative, particularly in underserved areas where informal healthcare providers serve as the first point of contact for TB patients.
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The Path to Effective AI Implementation
The research emphasizes that AI integration in healthcare requires customized approaches, including:
Addressing regional healthcare infrastructure disparities
Providing additional support and training for healthcare providers
Targeting providers with limited access to diagnostic tools
Evaluating cost implications to ensure affordability and sustainability
A Behavioral Approach to AI Adoption
Co-author Professor Sarang Deo, Deputy Dean, Faculty and Research at ISB and Executive Director of MIHM, highlighted the importance of behavioral and implementation science in AI evaluation.
“Our study underscores the need to move beyond technical assessments and consider behavioral factors that impact AI adoption.
The finding that providers with weaker diagnostic skills are less likely to use AI suggests that its real-world impact on health outcomes may not align with purely technical expectations.”
The study’s findings offer valuable insights for policymakers, healthcare stakeholders, and technology developers working to enhance AI-driven TB diagnosis in India’s informal healthcare sector.