I knew healthcare would be different — just didn’t expect this different.
Here’s what’s stood out the most so far:
⚠️ You don’t get a second chance
In e-commerce, a bad dashboard might mean missed sales.
In healthcare, it could delay a diagnosis.
The stakes are higher — and so is the pressure to get it right.
🧹 Data isn’t just messy — it’s fragmented
Different EHRs, manual entry, free-text notes, ICD/CPT soup.
Cleaning isn’t a one-time task — it’s part of the daily workflow.
đź“ś You work inside a regulatory box
HIPAA, internal policies, audit trails — compliance isn’t optional, and it shapes every decision.
đźš« No real A/B testing
You can’t split patients into “treatment” vs “no treatment” groups just to test a hypothesis.
So you learn to get creative with observational data, historical comparisons, and domain input.
🧠Clinicians don’t want dashboards — they want clarity
No one has time to “explore trends.” The best analytics fit into the clinical workflow, not sit beside it.
Which leads to the real job:
đź’¬ Analytics = Translation
Between data teams, IT, and clinicians — each with their own language.
The role is less about charts, more about context.
Less about tools, more about trust.
🖥️ (see illustration):
📤 From: Healthcare Data (EHR, CPT, HL7…)
đź“Ą To: Real-World Care Decisions
Still learning every day — but that framing has helped a lot.
If you’re in the space — or curious about it — feel free to connect, follow, or share.
