Why underpowered studies are more dangerous than you think
In epidemiology, statistical power determines whether a study can accurately detect an effect of a...
A better way to measure healthcare costs in closed claims data This is the second post in our four-part taXonomy X blog series (part 1 here), and here we’ll discuss one of the most common pain points in closed claims analytics: costs. Specifically,...
In epidemiology, statistical power determines whether a study can accurately detect an effect of a...
A better way to measure healthcare costs in closed claims data This is the second post in our...
How clinical data linkage closes evidence gaps in real-world data Clinical data linkage helps...
Real World Data (RWD) is increasingly being incorporated into healthcare and life science research...
Artificial intelligence is moving quickly into healthcare research, but one question still comes...
One in nine Americans age 65 and older has Alzheimer’s disease (AD), a devastating illness that...
Healthcare claims data are one of the most powerful sources of data in generating real-world...
Why healthcare marketers need more transparency in audience targeting Healthcare marketers are...
In Season 2 of The Pitt, Dr. Santos accepts an AI-drafted clinical note and moves on. It’s one of...
When our client, a global pharmaceutical company, set out to better understand long COVID pathways,...
In epidemiology, statistical power determines whether a study can accurately detect an effect of a given size with a specified probability, typically 80% or higher. When studies fall below that threshold, the consequences extend well beyond inconclus...