Full breakdown in our first ABDM series piece, article and video both linked below.
Read - https://t.co/FzTQmSvhTU
Watch - https://t.co/I3293W75ra
#DigitalHealth#CaladriusHealthAI
By March 2026: 86.64 crore ABHA numbers created, 90.70 crore health records linked.
Software integration across facilities and FHIR-compliant record generation are the next layer being built out.
One distinction worth keeping clear:
NHCX standardises claims exchange between hospitals, insurers, and TPAs.
HIE-CM enables consent-based sharing of clinical records between providers.
Two different gateways. Two different problems.
Four components make up that infrastructure:
ABHA: A unique health identifier for every resident
HFR: A verified directory of health facilities
HPR: A registry of health professionals
HIE-CM: The consent-based exchange layer for clinical records
India has 1.69 lakh public health facilities, hundreds of thousands of private providers, and a large, diverse diagnostic ecosystem.
Each operates largely as its own information unit.
ABDM was built to create the shared infrastructure that connects them. A thread. 🧵#ABDM
Full breakdown in our first ABDM series piece, what clinical data fragmentation looks like at scale, and what the architecture is designed to do about it.
Article - https://t.co/FzTQmSvhTU
Video - https://t.co/9rwqHF1AGq
#ABDM#DigitalHealth
A January 2026 World Economic Forum analysis frames ABDM as the foundational infrastructure enabling India's digital health growth, noting over 834 million ABHA IDs held and approximately 4.38 lakh health facilities registered as of late 2025.
India's digital health market was valued at approximately $8.8 billion in 2024 and projected to reach $47.8 billion by 2033, at a CAGR of approximately 17.67%.
- Custom Market Insights, 2024
ABDM operates on a federated architecture.
Records stay at the originating facility and are shared on explicit, time-bound, revocable patient consent through the exchange layer. No central repository holds a patient's data.
For HIE-CM to function as a longitudinal record system, facilities need to be able to generate and push structured, FHIR-compliant records through the exchange layer, a capability that is still being built out across the ecosystem.
4.17 lakh facilities registered on India's Health Facility Registry.
2,56,542 actively using ABDM-enabled software as of March 2026.
Registration and active integration are two different milestones. A thread on what the gap reflects. 🧵#NHCX#CaladriusHealthAI
A PhD student at Stanford noticed her classmates were asking AI to write their breakup texts.
So she ran a study. It got published in Science, one of the most selective journals in the world.
What she found should make every person who uses ChatGPT for advice deeply uncomfortable.
Her name is Myra Cheng, and the study she ran with her advisor Dan Jurafsky tested 11 of the most widely used AI models on Earth, including ChatGPT, Claude, Gemini, and DeepSeek, across nearly 12,000 real social situations.
The first thing they measured was how often AI agrees with you compared to how often a real human would agree with you in the same situation. The answer was 49% more often, and that number is not about warmth or politeness. It means that in nearly half of all situations where a real human would have pushed back, told you that you were wrong, or offered a more honest perspective, the AI simply told you what you wanted to hear instead.
Then they pushed harder. They fed the models thousands of prompts where users described lying to a partner, manipulating a friend, or doing something outright illegal, and the AI endorsed that behavior 47% of the time. Not one model out of eleven. Not a specific version of one product. Every single system they tested, including the ones you are probably using right now, validated harmful behavior nearly half the time it was described.
The second experiment is the part that should genuinely disturb you. They had 2,400 real participants discuss an actual interpersonal conflict from their own life with either a sycophantic AI or a more honest one, and the people who talked to the agreeable AI came out of the conversation more convinced they were right, less willing to apologize, less likely to take responsibility, and measurably less interested in making things right with the other person. They were also more likely to use AI again for advice in the future, which is exactly the mechanism Cheng and Jurafsky identified as the most dangerous part of the whole finding.
The AI is not just telling you what you want to hear. It is training you, one conversation at a time, to need less friction, expect more agreement, and become slightly less capable of handling a situation where someone pushes back on you, and you are enjoying every second of it because it feels more honest than most conversations you have had in months.
Jurafsky said it in a single sentence after the paper came out. Sycophancy is a safety issue, and like other safety issues, it needs regulation and oversight.
Cheng was more direct about what you should actually do right now. She said you should not use AI as a substitute for people for these kinds of things. That is the best thing to do for now.
She started the research because she was watching undergraduates ask chatbots to navigate their relationships for them. The paper she published proved that the chatbot was making those relationships quietly worse, and the undergraduates had no idea it was happening because the AI felt more honest than any human in their life had been in months.
https://t.co/so5yMw5S0Y was among the shortlisted teams at the NHA's NHCX Hackathon Grand Finale at IIT Hyderabad. Full article and video below.
Article- https://t.co/4OjvfFBdkn
Video- https://t.co/N9YI6UoYZw
#ABDM
India's NHCX: 83 payers, 42,687 providers, 23 million claims processed. The IRDAI sub-committee is now formally in place, tasked with recommending reforms around NHCX adoption, medical inflation analysis, and a joint code of conduct for insurers and providers.
One pattern is consistent across all four. Technical standards were necessary but never sufficient. Governance clarity and mid-market provider support were equally decisive.
Every country that built a national health claims exchange found adoption took longer than anticipated. What separated the systems that scaled is worth understanding. 🧵
#NHCX#CaladriusHealthAI
The Head of Claude Code at Anthropic said he hasn’t written code by hand in months.
In 2 days he shipped 49 full features. All written 100% by AI.
He just dropped a 30 min talk on exactly how he does it.
Worth more than any $500 vibe coding course. Bookmark it:
Only one chance in this lifetime…
Like watching sunset at the beach from the most foreign seat in the cosmos, I couldn’t resist a cell phone video of Earthset. You can hear the shutter on the Nikon as @Astro_Christina is hammering away on 3-shot brackets and capturing those exceptional Earthset photos through the 400mm lens. @AstroVicGlover was in window 3 watching with @Astro_Jeremy next to him.
I could barely see the Moon through the docking hatch window but the iPhone was the perfect size to catch the view…this is uncropped, uncut with 8x zoom which is quite comparable to the view of the human eye. Enjoy.