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Evidence-based medicine treats the "average patient" — but that patient doesn't exist.
Knowing a patient's history, family, stress, and habits predicts outcomes more powerfully than any checklist.
The therapeutic alliance is more important than the medication itself in determining treatment success.
15-minute appointments force algorithmic care, leaving patients unseen, unheard, and frustrated.
Imagine two people walk into their psychiatrist’s office on the same day. Both are struggling with low mood, poor sleep, and fatigue. Both leave with the same prescription, the same dose, and the same follow-up appointment scheduled in six weeks. One gets better. The other doesn't. Why?
This story is repeated millions of times each year, and raises the question: Should doctors treat diseases, or should they treat people?
Evidence Based Medicine
For most of the 20th century, medicine operated on a simple premise: find the best treatment for a given condition, test it on large populations, and apply that knowledge universally. This approach —called evidence-based medicine (EBM)— was formalized in the 1990s, largely by Canadian physician David Sackett.
Sackett described the goal of EBM is to replace hunches and habits with data and clinical trials. Clinical guidelines were developed involving protocols that tell doctors which drug to prescribe first, what dose to use, when to escalate treatment, and when to refer a patient to a specialist. Today, these guidelines are often incorporated into electronic health records, where they guide physicians toward the statistically optimal choice for the average patient.
But there’s a problem with........
