In early 2025, AIIMS Nagpur, in collaboration with PATH, introduced a digital newborn care model in Melghat, a tribal region in Maharashtra that has long struggled with high neonatal mortality.
Through a Tele-Special Newborn Care Unit (Tele-SNCU), the initiative connected rural nurses with pediatric specialists remotely using 360° cameras, IoT-enabled monitors, and a real-time clinical dashboard. These tools enabled critical clinical decisions to be guided from afar without requiring a specialist to be physically present.
The outcomes were significant:
All of this was achieved using low-cost, off-the-shelf technology integrated into existing public health infrastructure.
What Made It Work?
At Acuitas Health Analytics, we see this not just as a successful pilot, but a real-world example of how digital tools, when thoughtfully applied, can address long-standing gaps in care delivery.
Key factors behind the success:
This was not about adding more infrastructure, it was about making the existing system smarter, faster, and more connected.
Can This Be Replicated?
Melghat’s success raises important questions for health systems and policymakers:
The answers lie not in copy-pasting a model, but in adapting the principles behind it: collaborative design, resource optimization, and outcome-driven implementation.
What’s Needed Next?
Rather than treat Melghat as a one-off success, we should use it to guide strategic replication. A few practical steps could include:
These aren’t large-scale interventions. They’re enablers that help systems prepare for change-thoughtfully and sustainably.
Our Take
Melghat’s story isn’t about technology alone. It’s about what happens when the right support reaches the right people at the right time.
The model didn’t require massive funding or new infrastructure. It required intent, collaboration, and a willingness to let local teams lead with the right tools in hand.
As consultants, our role is to help identify stories like Melghat’s and connect them with systems that are ready to grow.
Not by asking “Can we scale this?” but by asking “What will it take to scale it well?”