Two Data Groupers Healthcare Analysts Shouldn’t Be Without

Health Data Guru #024

Have you ever had to work with diagnoses and procedure codes — two hallmarks at the core of healthcare analytics? Healthcare analysts will often get an oddball request like “how many diabetics [diagnosis] living in this county and had a hernia repair [procedure] this year?”

We might dive right in and start combing through lists for diagnoses that we’ll need to pull, plucking out the ones that look or sound like they’re related to the things in question, searching for diagnosis descriptions that contain “diabetes, diabet, diab” etc.

If we’re lucky, we’ll already have a vetted codeset available to us that identifies the codes in this grouped fashion, have a medical biller around to consult, or perhaps a clinician champion available to validate our assumptions.

But in my career, having a reliable crosswalk laying around has only been the case about 50% of the time, so I’ve had to be industrious.

I’ve found 2 datasets to be extremely helpful over the last decade as a healthcare analyst, which I’m sharing here.

Diagnosis Crosswalk: