Everything You Want To Know About Google's New Cloud Healthcare API
Now Google is more focused on providing the healthcare organizations with the innovative technology needed to improve the overall healthcare system. It is working with the many organizations which include the discovery, development, and provide the best healthcare system to the patients.
On 5 April 2019, Google announced the Beta version of Cloud Healthcare API. The primary goal with Cloud Healthcare API is to build the database that helps healthcare industry. This API allows organizations to use the data, manage the crucial data, and better understand the data through the application of analytics and Machine Learning (ML).
This API allows to manage the solutions for storing and accessing healthcare data in Google Cloud Platform (GCP). It provides the critical bridge between the existing care system and the application hosted on Google Cloud, by using the API customer can unlock the significant new capabilities for data analysis, machine learning, and application development. These type of capabilities can enable the next generation of healthcare solutions.
By supporting the standard based data formats and the protocols of the existing healthcare technologies, this API helps to connect the data with the advance Google cloud capabilities such as streaming data processing with cloud dataflow, scalable analytics with the BigQuery, and Machine Learning with the cloud machine learning engines. This API simplifies application development and device integration to accelerate digital transformation and enables real-time integration with care network.
Let's discuss the important components of this API.
Fast Healthcare Interoperability Resources (FHIR)
FHIR is the emerging standard for the healthcare interoperability, it is the robust extensible data model for interacting with clinical resources. Google cloud can transform data from other formats into and FHIR resources use to simplify the data ingestion and ensure the data available for the analytics and Machine Learning tools.
HL7v2
HL7v2 is an important communication modality for any application seeking to connect the existing clinical systems. The HL7v2 API implements a REST interface for the ingesting, sending, searching, and retrieving HL7v2 messages. It has to be integrated with an open source adapter to send and receive messages over Minimal Lower Layer Protocol (MLLP) and several common HL7v2 interface engines.
DICOM
It is the well-known standard for storing and exchanging the medical images, it is used to access the metadata across the wide range of modalities, radiology, cardiology, ophthalmology, and dermatology. It allows customers to store their medical imaging data and connect their data to powerful tools for analytics and machine learning.
De-identification
It is the process of removing the information from the database so that data cannot be linked back to a specific individual. It is a very crucial process for the healthcare industry because the data can be used for analysis, training, and evaluation of the Machine Learning models.
Data locality
It is the core component of Cloud Healthcare API, it allows you to choose the storage location for each dataset. You can also control where the data is stored in the Google Cloud with the help of this API. It allows organizations to track the actions that are affecting the data by logging the administrative modifications of the datasets, data stores, and IAM policies.
Analytics and Machine Learning
Once data is brought to the Google Cloud Platform then the healthcare API enables customers to integrate their data with powerful analytic tools such as BigQuery, Machine Learning, and the third party tools such as Tableau.
Now, let's discuss the features of the Cloud Healthcare API and the primary purpose of each feature.
Compliance with privacy regulation
The Cloud Healthcare API is covered by GCP's security, privacy, and compliance assessments for industry standards such as ISO 27001, ISO 27017, ISO 27018, and PCI DSS.
Security
The security model of this API is based on Google's Identity and Access Management (IAM) system. IAM's guidelines give you the complete control over healthcare data and it's also implemented on the open source proxies for the Apigee API management system, which provides comprehensive threat detection and traffic management capabilities that allow you to surely exposes the sensitive ePHI with the patient and provider applications.
Bulk Import and Export
The Cloud Healthcare API DICOM and FHIR modalities support bulk import and export of the data, which makes easier to transfer the data from cloud storage. You can also export the DICOM store metadata and FHIR resources to BigQuery, this allows you to perform the advanced analytics on the large worksheets.
High performance
By using the GCP's high-performance technology, the Cloud Healthcare API has the capability to manage thousands of requests per second, even when processing a large amount of data.
Durability
This API is designed for 99.99% annual durability which is achieved by storing data across multiple disks located in different power and network failure domains.
Developer friendly
This API organize the information of the users into the database with one or more modality specific stores per set where each exposes both a REST and RPC interface.
This is all about the new Google Cloud Healthcare API. If you want to explore more about this new API, go and check out the documentation of this API.
After the implementation of this new API one thing is sure that the healthcare industry is going to change completely. Collecting and managing the data of the patients will be much easier with the help for this API and doctors can view the patient's information from anywhere and whenever they want. You can easily find out the best Android application development company which develop the app which consist this APIs.