This is Part 3 of our series on creating an FHIR API using Google Cloud’s offering. In the last installment, we began implementing an FHIR using GCP. We covered creating both the BigQuery resources and your FHIR repository resources. if you missed Part 1 and Part 2, be sure you go back to read those – they’re critical to understanding!
This time, we’re continuing the implementation. I’ll explain the authentication methods, and we’ll also tackle populating data in our FHIR repository.
Welcome back to our series, Creating an FHIR API. This is Part 2 in our 4-part series on standing up an FHIR using GCP. In Part 1, we talked through two of the offerings out there, Google and Azure, and based on the pros and cons, I decided to use GCP FHIR Cloud Healthcare API.
In this part, we’ll start in on our implementation. A forewarning: we won’t be able to finish it during this installment, so stay tuned for parts 3 and 4! Let’s dive in.
Data interoperability is one of the hardest problems in Healthcare IT. The most popular approach is to exchange HL7v2 messages between systems. These pipe-delimited messages are difficult to read by a human and often need additional customizations between implementations.
The next major paradigm shift is towards FHIR (Fast Healthcare Interoperability Resources), a JSON-based standard that is evolving ahead of the needs of the industry. Cloud vendors like Microsoft, Amazon, and Google are trying to lay their claim to be the one-stop shop for healthcare on the cloud.
This blog is part of a 4 part series diving into an actual use case I recently encountered while working with a client. I had to stand up an FHIR repository/API for 2+ million patients that could be used by hundreds of users every day, as well as countless background processes.
