Harsh Shah, Sandeep Rai, Jay Patel, Abhishek Sen, Rajesh Sharma
Frontline healthcare workers (HCWs) in India must navigate rapidly evolving National Tuberculosis Elimination Program (NTEP) guidelines, yet existing digital tools largely function as static repositories that are decoupled from point‑of‑care decision‑making. There is a critical need for cadre‑specific, real‑time decision support to bridge the "know-do" gap in tuberculosis (TB) care. We developed Ni‑kshay Support to End Tuberculosis (SETU), a national‑scale digital ecosystem conceptualized as a "ready reckoner" for TB care, using a human‑centered design framework and a collaborative requirements development methodology. The platform integrates an artificial intelligence (AI)‑based chatbot, cadre‑specific multilingual clinical decision support systems (CDSS), and a knowledge hub into a single web and mobile interface. We evaluated the ecosystem using the reach, effectiveness, adoption, implementation, and maintenance framework, drawing on platform analytics, in‑app assessments, and user feedback from HCWs across India. As of the current assessment, Ni‑kshay SETU has 46,379 active subscribers and over 1.63 million total visits, with active users in 35 of 36 states and union territories and more than 450 districts. Over 70% of users are frontline HCWs, including senior treatment supervisors, health visitors, and laboratory technicians, indicating deep penetration at the operational level. Knowledge assessments (approximately 18,900 completed) showed a statistically significant increase in mean scores from 14.49 (±6.67) at baseline to 20.46 (±7.84) at post‑intervention (p<0.001). Users reported high perceived utility for the CDSS (mean: 4.32/5) and AI chatbot (4.15/5), and 96.4% indicated they would recommend the platform to peers. Ni‑kshay SETU operationalizes national TB guidelines into a living, digital "ready reckoner" that delivers cadre‑specific, point‑of‑care decision support at national scale. By combining human‑centered design with dynamic, cloud‑based content updates, the platform reduces cognitive load on HCWs, standardizes protocol‑compliant care, and provides a scalable blueprint for extending similar digital ecosystems to other disease programs in low‑ and middle‑income settings.