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HL7 and FHIR have been around for decades. Exchanging data is actually the easy part.
The problem is typically more on the business logic side of things. Good example is the fact that matching a patient to a particular record between facilities is a much harder problem than people realize because there are so many ways to implement patient identifiers differently and for whoever inputs a record to screw up entry. Another is the fact that sex/gender codes can be implemented wildly differently between facilities. Matching data between systems is the really hard part.
(I used to do HL7 integration, but have since moved more to the systems side of things).
I work in a particularly niche area (home infusion/home medical equipment) and while HL7 and FHIR are indeed things, practically no software that was built for those lines of business had any sort of module for that. We have a FHIR interface now and...no one uses it. They prefer faxes.
That's likely a peculiarity of the niche you're in. HL7/FIHR are the norm for enterprise-level systems. Hospitals couldn't function without it and at any given time we typically have multiple HL7 integration projects rolling just as a mid-size regional.
Definitely less defined in the small-practice and patient-side space. Though, like I said, the big problem there ends up being data normalization anyway.
I feel this - I'm often on the other end working with data from clinicians in the field for massive studies. The forms that come in can have an infinite number of possibilities just for noting sex. Enough so that our semantic layer needs a human reviewer because we keep finding new ways field clinicians have of noting this. Now imagine that over the whole gamut of identifiers.
tl:dr - Humans are almost always the problem in data harmonization.
EDI as well