Real-World Data Riddles

Real-World Data Riddles

What to Fix First When Your Morphium Cohort Suddenly Doubles: The Hidden Risk of Data Merging

Your cohort just doubled. Overnight. The metric board glows green, the PI smiles, and somewhere a slide deck is already being updated. But stop. Befor...

Real-World Data Riddles

When Temporal Drift Sank My Morphium Analysis: A Real-World Data Riddle

I remember the sinking feeling. My Morphium dashboard showed a gleaming 97% accuracy on the historical test set. Then I fed it fresh data from last mo...

Real-World Data Riddles

How to Spot a Hidden Selection Bias in Your Real-World Data Before It Skews Results

You run a Cox model on insurance claim. The hazard ratio looks clean — 0.85, tight confidence interval. But here is the thing: you only have data on p...

Real-World Data Riddles

Why Your Morphium Prediction Model Fails in Practice: Missing Data vs. Missing Context

You built a model. It predicts Morphium pull with 95% accuracy on holdout data. Then output hits—and the model misses a stockout by 40%. Sound familia...

Real-World Data Riddles

Choosing a Real-World Data Source Without Confounding by Indication: Five Mistakes to Fix First

You have a ques: does this treatment more actual effort in the patient you see every day? The randomized trial says yes, but your populaing is older, ...

Real-World Data Riddles

When Your Real-World Data Looks Too Perfect: The Overfitting Trap in Morphium Studies

You run a regression on 2,000 morphium patient records. R-squared: 0.94. P-values: tiny. Residuals: barely a wiggle. Primary thought? I nailed it. Sec...