This is a genuinely solid clinical reasoning framework. Here's how I see it:

Your professor is describing hypothesis-driven differential diagnosis - essentially forcing you to reason from first principles rather than pattern-matching a symptom cluster too early. It's a structured way to avoid premature closure (one of the most common diagnostic errors).

1. It fights anchoring bias When you see two complaints together, the brain naturally tries to find one elegant unifying diagnosis. Sometimes that's right, but it can blind you to a simpler or more dangerous alternative. Splitting them forces independent reasoning on each thread.

2. It builds a proper differential for each symptom Each complaint has its own pathophysiological basis. If a patient has, say, secondary amenorrhea + galactorrhea, you might jump straight to prolactinoma. But if you work them up separately first, you'd list:

Now when you combine them, prolactinoma earns its place at the top rather than just feeling obvious.

3. It catches coincidental co-morbidities Not every cluster of complaints has a single cause. Two pathologies can coexist - and the "combine and intersect" step lets you recognize when no single diagnosis explains both, prompting you to look for two separate conditions.

4. It trains pattern recognition properly By repeatedly doing this exercise, you learn which diseases characteristically cluster certain symptoms. Over time, the combination step becomes fast and intuitive - that's expert clinical pattern recognition, but now grounded in mechanistic understanding rather than rote memory.

The approach assumes the complaints are independent at the reasoning stage. In practice, some symptoms are directly causally linked (e.g., pain causing reflex tachycardia), and splitting them artificially can occasionally lead you astray. The skill is knowing when to split vs. when one complaint is clearly secondary to another.

Also, in a busy clinical setting, this full exercise takes time - but the habit of mind it builds is what matters. You don't always run the full formal process, but your instinct becomes more reliable because of the training.

This is particularly apt in gynecology because symptoms like pain, bleeding, amenorrhea, and discharge each have long, overlapping differentials across very different pathologies (hormonal, structural, infectious, neoplastic). The "intersect at the end" step is essentially what diagnostic algorithms like the one for pelvic pain are doing formally - just made explicit and teachable.

It's a smart, evidence-aligned teaching tool. The underlying principle maps directly onto what cognitive psychology research on diagnostic error recommends: slow down system-1 thinking, reason analytically on each data point, then synthesize. Your professor packaged that into a very practical bedside method.