How can you know if the fake data is sufficiently similar to real data? I wonder what Google's use case for this is.
More broadly, all big 3 cloud providers (Azure, AWS, and Google) have offerings for FHIR data storage and API access, as well as common NLP based healthcare data analysis workflows. Many of these seem relatively new, or as if they have had a lot of recent attention focused on them. I'm definitely interested in how/why these companies (as well as some other VC funded ones, like Medplum), are entering this space with products that are not directly sellable, but are rather things that other tools would have to build upon. It seems like AWS works directly with end-customers to use their APIs to build products, but I'm not sure what Azure and Google are doing.
This one's probably too complex for my use case, but I thought the concept looked very neat and wanted to share.
Fairly sure they built this to test their HL7v2 store[2]. Also presuming it hasn't been very active given that Google surprisingly shut down their Healthcare division (and probably restarted it somewhere)[3].
[1] https://github.com/google/simhospital/blob/master/docs/dashb... [2] https://cloud.google.com/healthcare-api/docs/concepts/hl7v2#... [3] https://www.businessinsider.com/google-health-shutting-down-...
While I don't think it's a bad career move, and that may have been part of their consideration, I find the trivialization of the work put in by someone here to open source something they thought would be a positive contribution hurtful.