They're required to publish their prices, which results in giant PDF documents with thousands of different charge codes and prices. Its almost incomprehensible to analyze unless you're in healthcare billing. Plus, you'd need to know what services/medications/equipment you'll need before you even get to the hospital, which is pretty dang tricky unless you're a doctor yourself.
I was recently in the hospital for abdominal issues. How would I know what drugs they would give me? How would I know if they were going to give me some kind of scan? If they were going to give me a scan, are they going to use a portable machine or use a stationary machine? Are they going to need to use some kind of endoscopic scope? Will I need other things to assist with those scans (sedatives, contrast materials, etc)? Which blood work tests is the doctor going to order? Which urine tests is the doctor going to order? Are they going to order stool samples? How many samples are they going to need, how many times are they going to need to re-run tests? What if I get there and determine I need surgery? How should I have known I needed that ahead of time? What kind of surgery is it going to be? What drugs are involved in that?
Its not like you can walk up and see a board that says "INTESTIONAL DISTRESS -- $175"
I briefly tried using the results of that, they're totally unnormalized, so even lining up identical line item charges is difficult. We have a deep learning language model that normalizes the language and lines up potential matches. But even if that works, it still doesn't get you the bill, because a single encounter includes a big batch of billing codes, depending on what the doctor tries to give you. And to get normal baskets, you probably want claims data. And the claims data providers we spoke to wanted 6-7 figures for a small dataset.
It's an incredibly parasitic industry, I've never seen anything quite like it. It's a pretty stark contrast to the largely altruistic motives of many of the healthcare professionals themselves.
