![\"esanjeevani\"](\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2025\/10\/esanjeevani.png\")
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I have lost count of how many digital health pilot projects<\/a> promised to revolutionize healthcare access in LMICs. Most delivered a few thousand consultations before quietly disappearing. Then there\u2019s eSanjeevani, India\u2019s national telemedicine platform, which just delivered 163 million consultations across 28 states in under four years.<\/p>\n The scale alone demands attention. However, what fascinates me about the new research published in Oxford\u2019s Digital Health journal<\/a> is what it reveals about which digital health models actually survive contact with reality. The findings challenge nearly every assumption we hold about digital health adoption in resource-constrained settings.<\/p>\n The Data Nobody Expected<\/p>\n The Indian Ministry of Health and Family Welfare launched eSanjeevani<\/a> to improve access to primary healthcare and advance digital health equity towards Universal Health Coverage. eSanjeevani has two models of usage:<\/p>\n In an era where we obsess over smartphone adoption, the winning strategy turned out to be low-tech intermediation through community health workers at rural health centers.<\/p>\n The study\u2019s most provocative finding: while acute conditions like fever dominated early consultations, by 2023 chronic disease management surged, with over 327,000 diabetes follow-ups recorded. This challenges the criticism that digital health solutions only work for minor ailments.<\/p>\n 7 Lessons Learned for Digital Health Practitioners<\/p>\n eSanjeevani\u2019s trajectory confronts the prevailing orthodoxy that direct-to-patient, smartphone-based solutions<\/a> represent healthcare access in LMICs. The data suggests otherwise.<\/p>\n The future, at least for the next decade in most low-resource settings, looks like community health workers with basic devices connecting patients to remote physicians through government-managed platforms integrated into public health systems.<\/p>\n Kinda like the Intelehealth approach<\/a>, eh?<\/p>\n This contradicts the market-driven, app-centric models that dominates global discussions. It also challenges assumptions that women\u2019s limited smartphone access will prevent telemedicine adoption. What actually prevents adoption is inadequate state capacity, fragmented systems, and platforms designed for urban, digitally literate users.<\/p>\n Here are the seven lessons learned in deploying eSanjeevani according to the research:<\/p>\n 1. Assisted models are best for LMIC contexts.<\/p>\n The 93% utilization through hub-and-spoke demonstrates that intermediated telemedicine, where a health worker facilitates the consultation, overcomes digital literacy barriers, trust deficits, and connectivity challenges simultaneously. This is not sexy, but it works.<\/p>\n We need to prioritize assisted telemedicine models with CHW facilitation over standalone patient apps in contexts with low digital literacy and connectivity challenges.<\/p>\n 2. Infrastructure expansion is a must.<\/p>\n eSanjeevani scaled from 6,868 spokes to 108,610 by 2023. The platform succeeded because it embedded within existing Health and Wellness Centers aligned with the WHO\u2019s Global Strategy on Digital Health<\/a>. Too many pilots fail because they operate in isolation.<\/p>\n We must embed platforms within existing health infrastructure rather than creating parallel systems. Integration with national digital health architecture is non-negotiable for sustainability, as detailed in recent locally-owned health data systems<\/a> analysis.<\/p>\n 3. Geographic concentration reflects state capacity.<\/p>\n The top five states generated over 70% of consultations. Rather than inequity, I see evidence that political commitment and implementation capacity matter more than technology design. This suggests governance capacity building should receive equal investment to platform development.<\/p>\n\n
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