- Why Application Programming Interfaces Are Key for Healthcare
For applications that function by pulling a constant stream of data from one or more sources, an API is especially important to decrease development time, save storage space on endpoint devices, and overcome any differences in the standards or programming languages used to create the data that lives at either end of the bridge.
Google’s API platform can help streamline digital transformations because the data is managed from one tool that is interoperable with other IT infrastructure tools.
Google added Google App Engine and Cloud Machine Learning Engine to its HIPAA-compliant solutions.
The Google API collects and manages critical healthcare data types including HL7, FHIR, and DICOM so organizations can use that data for analytics and machine learning in the cloud.
A large part of what makes APIs successful and progressive is having them be open source. This ensures that many different organizations and developers can work on improving the API specifically for the healthcare space.
“Through an API-first approach, we can help healthcare enterprises simplify data interoperability by providing a strong foundation with cloud infrastructure and services,” said Google in its official blog post.
Several healthcare organizations worked with the tool before its official launch, including Stanford School of Medicine, to develop the API.
"Open standards are critical to healthcare interoperability as well as for enabling biomedical research,” Stanford School of Medicine Director of Research IT Somalee Datta, PhD, said in a statement. “We have been using the Google Cloud Genomics API for a long time and are very excited to see Google Cloud expanding its offerings to include the new Cloud Healthcare API.”
“The ability to combine interoperability with Google Cloud’s scalable analytics will have a transformative impact on our research community."
Google believes that machine learning the next significant step in the healthcare digital transformation as the industry moves to the cloud. The move to the cloud gives entities the space and scalability to take on data intensive projects that involve machine learning.
Larger, well-known tech companies like Google are increasingly extending into the healthcare sector even though the healthcare vertical is slow to adopt new technology that could greatly benefit the way it operates.
Google Cloud, Microsoft Azure, and Amazon Web Services (AWS) are competing for the most prominent place in healthcare cloud by focusing on interoperability, which has been one of the biggest challenges in healthcare over the past several years.
“Google Cloud’s goal for healthcare is very much a reflection of Google’s overall mission: to organize the world’s information and make it universally accessible and useful,” said Google. “Applying this mission to healthcare means using open standards to help enable data sharing and interactive collaboration, while also providing a secure platform.”
Using APIs to simplify how data is used can significantly increase the usability of data collected by clinicians and medical devices. A platform that allows organizations to embrace their data for analytics can help entities make future plans to include more data intensive initiatives.