ArticleBMJ public health2025
Challenges and strategies for early diagnosis and management of type 2 diabetes mellitus at the primary healthcare level in rural Western Vidarbha, India: a qualitative study.
Article in BMJ public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Machine learning-based risk prediction models for type 2 diabetes in primary care: a scoping review.Frontiers in public health · 2026Article
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6 authors.
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Abstract
Background: Type 2 diabetes mellitus presents a major public health challenge globally, with India bearing a disproportionate burden. Early detection and management at the primary healthcare (PHC) level are critical but remain underexplored in rural contexts. Methods: We conducted a phenomenological qualitative study in Akola district from western Vidarbha region of India. Data were collected through 15 key informant interviews with healthcare providers, 11 interviews with patients and 13 focus group discussions with community health workers. Thematic analysis was performed following Braun and Clarke's framework, and intercoder reliability was established (Cohen's Kappa=0.85). Results: Barriers included limited provider knowledge, patient health literacy gaps, fragmented referral systems and resource shortages. Facilitators encompassed training initiatives, home-based screening innovations, community awareness programmes and integration of specialist support. A conceptual framework was developed mapping systemic, provider and community-level determinants influencing diabetes outcomes. Conclusion: Strengthening early diabetes screening and management at the PHC level requires multifaceted interventions encompassing workforce capacity development, supply chain improvements and community engagement. The findings offer a scalable model for integrating diabetes care into primary health systems in resource-constrained settings, contributing to global efforts to address the rising non-communicable disease burden.
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