I'm skeptical. I concede it's probably a hard problem but there is an entire field dedicated to hard statistical problems called data science. What is the point of having detailed patient histories and data if it can't be used to inform decisions?
There is certainly noise in healthcare data especially when patient-reported, but is it noise to say that a patient having X procedure later does or doesn’t have serious complications? Analyzes of medical care and their consequences can be evaluated and it’s not noise
And big healthcare data has lagged, partially because privacy concerns trump sharing. There are companies selling anonymized medical records for basically every American now though. Big data is coming
Big _bad_ data... Let's see how we fare in 5y, then. My prediction as a clinician with a special interest in stats: close to zero medical progress. But insurance priced by a ML algorithm, and much greater efficiency in coverage and claim denials.
https://www.healthcare.gov/how-plans-set-your-premiums/
The more likely use case for ML is detecting insurance fraud patterns.
I think that's covered under "much greater efficiency in coverage and claim denials."
The codes we do have are mostly CPT4 and ICD-10 for billing purposes. Those are generally pretty accurate, but not detailed enough to reliably assess whether one surgeon is better than another at a particular procedure.