There’s plenty of coverage on what machine learning may do for healthcare and when. Painfully little has been written for non-technical healthcare leaders whose job it is to successfully execute in the real world with real returns. It’s time to address that gap for two reasons.
First, if you are responsible for improving care, operations, and/or the bottom line in a value-based environment, you will soon be forced to make decisions related to machine learning. Second, the way this stuff actually works is incredibly inconsistent with the way it’s being sold and the way we’re used to using data/information technology in healthcare.
I’ve been fortunate to have spent the past dozen years designing machine learning-powered solutions for healthcare across hundreds of academic medical centers, international public health projects, and health plans as a researcher, consultant, director, and CEO. Here’s a list of what I wish I had known years ago.
