The engine for interoperability
The Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-driven data formats and protocols of existing healthcare technologies, the Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including data processing with Cloud Dataproc, scalable analytics with BigQuery, and machine learning with Cloud ML Engine, while also simplifying application development and device integration. The Cloud Healthcare API accelerates digital transformation for organizations with existing clinical systems and enables new entrants to easily integrate with care networks.
FHIR (Fast Healthcare Interoperability Resources) is the emerging standard for healthcare interoperability. FHIR specifies a robust, extensible data model using REST semantics for interacting with resources. FHIR benefits from technical advances in web development to deliver significant industry traction, including major electronic health record systems, and support among notable government projects. Google Cloud's FHIR API provides full support for STU3 resources. In addition, Google Cloud is developing tools and utilities to transform data from other formats into and out of FHIR resources to simplify data ingestion for use with analytics and machine learning tools.
DICOM is the established standard for storing and exchanging medical images across a wide range of modalities including radiology, cardiology, ophthalmology, and dermatology. DICOMweb is a REST API for organizing and querying medical images. The DICOMweb API allows existing imaging devices, PACS solutions, and viewers to interact with Cloud Healthcare API, either directly or via open source adapters designed to support existing DICOM DIMSE protocols. The DICOMweb API enables the curation and export of imaging datasets for research, machine learning model training, and archival storage for disaster recovery. It can also be used to integrate machine learning and other processing modules into a clinical workflow by presenting output in the existing viewers.
HL7v2 is an essential communication modality for any application seeking to integrate with legacy clinical systems. The HL7v2 API implements a REST interface for ingesting, sending, searching, and retrieving HL7v2 messages. In addition, Google Cloud provides an open source adapter to send and receive messages over Minimal Lower Layer Protocol (MLLP). The adapter runs within Google Kubernetes Engine to provide rapid provisioning, communicates over Cloud Pub/Sub to deliver horizontal scalability, and connects with Cloud VPN to enable transport security.
Analytics and machine learning
Once data is brought to Google Cloud Platform, you can leverage Google Cloud machine learning and analytic tools such as BigQuery, which offers highly scalable, managed analytics to produce meaningful insights. Visualization and machine learning tools such as Cloud Datalab, as well as third-party tools such as Tableau, can make these analytics easy to consume. ETL (extraction, transformation, and load) tools will help manage field and vocabulary mappings on data from multiple sources and ease the conversion between schemas, whether you're creating a clinical data warehouse or a less formal data lake. Machine learning is made simpler by leveraging the FHIR and DICOM standards. DICOM analytics enable you to bring image data into BigQuery for analysis.
Data sent to Google Cloud via the Cloud Healthcare API is controlled by your organization. See Google Cloud Platform's data processing terms for details.
Committed to compliance
The Cloud Healthcare API supports HIPAA compliance. Google Cloud is HITRUST CSF certified. In addition, the Cloud Healthcare API is in scope for Google Cloud Platform's ISO 27001, ISO 27017, and ISO 27018 certifications. See Google Cloud Platform's compliance page for more information.
Guided by leading security experts, Google Cloud provides cutting-edge security capabilities, including data loss prevention tools and precise policy controls.
Direct support for open healthcare standards enables organizations to send, receive, and process data in formats expected by existing healthcare applications and care systems. Support for Cloud Pub/Sub allows you to trigger custom processing when new data has been received, and to securely integrate the Cloud Healthcare API with your applications.
Healthcare API services are integrated with Google Cloud Platform's auditing service. By default, administrative modifications to datasets, data stores, and IAM policies are logged. In addition, you can enable audit logging of item creation, modification, and reads within each data store.
The Cloud Healthcare API treats data locality as a core component of the API. You have the option to select the storage location for each dataset from currently available locations. The available locations correspond to distinct geographic areas. Future locations will allow for the distribution of storage across wider geographic areas.
The Cloud Healthcare API is built on top of Google's industry-leading cluster management and networking infrastructure. Whether you are storing one or 100 million records, your datasets automatically benefit from multiple layers of redundancy and fault tolerance.
The Cloud Healthcare API provides web-native, serverless scaling optimized by Google's infrastructure. Simply activate the API and start sending requests — no initial capacity configuration required. Although some limits exist (e.g., Cloud Pub/Sub quotas), capacity can expand to match usage patterns.
The Cloud Healthcare API integrates with Apigee, recognized by Gartner as a leader in full life cycle API management, to deliver app and service ecosystems around your data.
The Cloud Healthcare API organizes your healthcare information into datasets with one or more modality-specific stores per set. Each store exposes both a REST and RPC interface. You can use Google Cloud IAM to set fine-grained access policies.
The Cloud Healthcare API is currently in alpha and available through our Trusted Tester Program. Pricing will be announced during beta, following alpha and prior to general availability. In the meantime, the Cloud Healthcare API is free to use. However, fees may be incurred while using other Google Cloud services such as BigQuery and Cloud ML Engine.
This product is in alpha trusted tester program. For more information on our product launch stages, see here.