General discussion
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Topic
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Edge-to-cloud data fabric really fixing real time healthcare analytics?
The healthcare IT community is running into the same challenge over and over. Hospitals are collecting mountains of data from monitors, imaging, EHRs, and smart devices at every bedside. The problem is that most of this data gets stuck exactly where it’s created. Bringing it all together for real-time analytics or AI seems nearly impossible. Reports from McKinsey show most healthcare organizations see this “data gravity” as the top thing holding them back from scaling up AI.
Now, there’s a lot of talk about edge-to-cloud data fabrics. The pitch is simple: set up a unified system that moves and manages data across the edge, on-prem, and cloud, and does it all in real time. This system should automate the heavy lifting for ETL and security, giving instant insights. MIT Sloan claims these setups can make analytics ten times faster and cut manual work by more than half. All of this sounds promising, but many are asking if it really delivers on those promises when put to the test in live healthcare settings.
There are a few hospitals using these data fabrics for rapid sepsis alerts or to predict readmissions, and some are getting research data to the cloud more quickly. But the real difference seems to come from more than just picking the right tools. It’s about having the right governance, building with open APIs, and getting buy-in from every team. Many still face real headaches with data quality at the edge, connecting older systems, and finding enough skilled people.
With this in mind, here are a few questions for anyone who’s been in the thick of it:
– How do teams actually move data between bedside devices and the cloud while keeping everything secure and compliant?
– Who has managed to get real-time ETL working smoothly, and what issues came up along the way?
– Are there clinical or business wins being seen, or is edge-to-cloud still more talk than results?
– How are organizations making sure they don’t get locked into a vendor or a system that’s hard to change later?
– What helps bring IT, analytics, and clinical teams together to make these projects work without constant roadblocks?
– Anyone with experience, stories, or lessons learned is encouraged to share. The community is looking for real-world advice, things to watch out for, and practical tips for making edge-to-cloud data fabrics actually work in healthcare.
