Hi everyone,

I'm a research scientist at King's College London and I'm relatively new to working with MIMIC data. I've been trying to get started with MIMIC-III and IV by downloading the CSV files and working with them in Python/pandas. So far, my experience has been... challenging.

For example, when I try to download sepsis patients with 1Hz vital sign data, I need to:

• Download several large compressed CSV files (multiple GB each)
• Spend a lot of time figuring out which tables have what data
• Write scripts to join different tables together (PATIENTS, ADMISSIONS, CHARTEVENTS, LABEVENTS, etc.)
• Understand the data structure and relationships
• Start over each time when I need a different cohort (e.g., COPD vs sepsis)

I'm about 2 weeks in and still haven't gotten to my actual analysis yet.

From reading online, I see people mention:

• Setting up local PostgreSQL databases
• Using BigQuery on GCP
• Tools like MIMIC-Extract (but it seems outdated?)
• PyHealth (just learned about this)

I'm genuinely curious:

1. Is this normal? Does it get easier once you learn the system?
2. What workflow do experienced MIMIC users actually use?
3. Are there tools or resources I should know about that would help?

I don't want to reinvent the wheel if there's a better approach. Any guidance from folks who've been through this learning curve would be really helpful.

Thank you!