I’m thrilled to sit down with Faisal Zain, a renowned healthcare expert in medical technology with deep expertise in the development and scaling of diagnostic and treatment devices. Today, we’re diving into the remarkable story of eSanjeevani, India’s national telemedicine platform, which has transformed healthcare access in resource-constrained settings. Our conversation explores how this initiative has achieved unprecedented scale, the innovative models behind its success, and the critical lessons it offers for digital health practitioners in low- and middle-income countries.
Can you start by giving us an overview of what eSanjeevani is and how it has reshaped healthcare access in India?
Absolutely. eSanjeevani is India’s national telemedicine platform, launched by the Ministry of Health and Family Welfare to enhance primary healthcare access and promote digital health equity. Its goal is to bridge the gap between patients and medical professionals, especially in underserved areas, as part of the broader vision for Universal Health Coverage. Since its inception, it has facilitated over 163 million consultations across 28 states in less than four years—an incredible feat that highlights its impact on expanding healthcare reach in a country as vast and diverse as India.
How do the two models of eSanjeevani differ, and what makes one more dominant in terms of usage?
eSanjeevani operates through two distinct models. The first, eSanjeevaniOPD, allows patients to connect directly with doctors and specialists using a mobile app on their smartphones. It’s designed for individual access and convenience. The second, eSanjeevani AB-HWC, operates through a hub-and-spoke model at over 208,000 rural health centers called Ayushman Arogya Mandirs, where community health workers facilitate teleconsultations with specialists at district hospitals. What’s striking is that 93% of consultations happen through this provider-assisted AB-HWC model. I believe this dominance comes down to the trust and support health workers provide, especially in areas where digital literacy and smartphone access are limited.
I understand women make up a large share of eSanjeevani’s users. What do you think enabled this, despite the gender digital divide in India?
Yes, it’s remarkable—between 57 to 70% of consultations on the platform were with women, which is unexpected given the well-documented gender gap in digital access in India. The assisted model at local health centers played a huge role here. It removed barriers like needing personal smartphones or navigating technology independently, and it also addressed cultural constraints around mobility and permission to seek care. Women could access services through trusted community health workers in a familiar setting. This shows other digital health programs that prioritizing intermediated access can significantly boost inclusion for marginalized groups like women in low-resource environments.
The platform’s focus seems to have evolved over time. Can you walk us through how the type of care provided has shifted?
Certainly. In the early days, eSanjeevani was primarily used for acute conditions—think fevers, colds, or minor ailments that needed quick consultations. But by 2023, there was a notable shift toward chronic disease management. For instance, over 327,000 follow-up consultations for diabetes were recorded that year. This evolution reflects both the platform’s growing technological maturity—like better audio-video stability and prescription tools—and the increasing trust among users to manage long-term conditions like hypertension or diabetes through telemedicine. It’s a powerful rebuttal to the notion that digital health is only for minor issues.
Why do you think assisted models, like the one used in eSanjeevani, are so effective in low- and middle-income countries?
Assisted models work exceptionally well in LMICs because they address multiple barriers at once. Community health workers act as intermediaries, helping patients who may lack digital literacy or trust in remote systems to navigate telemedicine. They’re often from the same community, so there’s a built-in layer of familiarity and cultural understanding. In contrast, standalone patient apps often struggle in these settings because they assume a level of tech-savviness and connectivity that just isn’t there for many people. My view is that digital health programs in LMICs should lean heavily on assisted models, at least in the near term, to ensure access and build confidence in these technologies.
Infrastructure played a big role in eSanjeevani’s success. How critical is embedding such platforms into existing health systems for scalability?
It’s absolutely essential. eSanjeevani didn’t just scale because of good technology; it grew from 6,868 to over 108,000 spokes by 2023 by integrating into existing Health and Wellness Centers and aligning with national digital health strategies. Many digital health pilots fail because they operate in silos, disconnected from public health infrastructure. Embedding platforms within these systems ensures sustainability, leverages existing resources, and builds on government commitment. Without this integration, you’re just creating parallel systems that can’t withstand the test of time or scale.
What’s your forecast for the future of digital health in low- and middle-income countries based on eSanjeevani’s experience?
I’m optimistic, but I think the future will look less like flashy, app-centric solutions and more like grounded, intermediated systems for at least the next decade. eSanjeevani shows that scaling digital health in LMICs hinges on government-led platforms integrated into public health systems, with community health workers playing a central role. We’ll see more focus on chronic disease management as technologies mature, and I expect a continued emphasis on equity—ensuring women, rural populations, and other underserved groups are reached through assisted models. The challenge will be building state capacity and infrastructure to support these initiatives, but if done right, digital health can truly transform access in resource-constrained settings.
