Clinical guidelines and insurance reimbursement often reflect population averages, which quietly shapes the options available to you as an individual patient. Health research also tends to isolate single variables, which is clean and easy to study but doesn’t reflect how people actually experience health: you aren’t just an A1C of 6.2, or just PCOS, but you’ll often be treated as if you were. We have far more powerful tools now — pattern-finding methods like principal component analysis, person-centered approaches, and machine learning — that can reveal the complex, individual profiles averages hide. I don’t know anyone who’s actually “average.” It’s time our analysis caught up to that.
End of field note 11