👀 3 Things That Surprised Me in Healthcare Analytics
The deeper I get into healthcare analytics, the more I realize how differently things operate in this space. A few lessons have really stuck — and they’ve reshaped how I think about data in clinical environments.
1️⃣ More data ≠ more insight
EHRs, claims, labs — there’s no shortage of data. But without a clear question or clinical context, it’s easy to get lost.
Sometimes, one thoughtful question is worth more than an entire machine learning pipeline.
2️⃣ Small changes can have big impact
A slight drop in no-show rates, a better scheduling flow — these aren’t flashy, but they save real time and reduce stress.
It often starts with one clean, actionable visualization.
3️⃣ Without clinical context, data is just numbers
Metrics are useful, but only when grounded in reality.
Understanding what drives the data — diagnoses, care decisions, workflows — is where the meaning really lives.
🛠 Right now I’m building in Power BI and SQL, and slowly getting into HL7 and FHIR.
The more I learn, the more I see how analytics can actually support care — not just report on it.
If you’re in this space — or curious about it — feel free to follow, connect, or share resources.
Always open to learning together.
