Google Cloud Healthcare API and Healthcare Data Engine

Unleashing the Power of Data for Better Care

TABLE OF CONTENTS

Standardizing apps and solutions in the cloud

Enabling large-scale analytics and machine learning

Bringing a myriad set of features to enter the future of healthcare

Empowering healthcare organizations to improve care and research

Google’s Healthcare Data Engine to harmonize data

How can BTC help?

Healthcare and life sciences organizations are increasingly moving to the cloud to store data and extract insights. While a unified view of data from multiple sources can help organizations improve efficiency and care, the proliferation of data and lack of interoperability often make it difficult. 

Google Cloud Healthcare API is at the forefront of enabling healthcare organizations to meet these challenges and unlock transformation. Through Cloud Healthcare API, organizations can ingest and manage data from a range of systems, including electronic health records (EHRs), patient registries, clinician notes, medical images, and clinical data, and analyze data using AI/ML technologies while safeguarding data privacy. 

Standardizing apps and solutions in the cloud

Google Cloud Healthcare API is a fully managed, serverless, scalable service that helps organizations access and store data in Google Cloud Platform (GCP). It allows users to standardize the data exchange between healthcare applications and care systems developed on Google Cloud, bridging the gap between them. Further, the Google Cloud Healthcare API is compliant with international privacy requirements and standards-based data protocols.

Google Cloud Healthcare API streams data to advanced Google Cloud services such as Cloud Dataproc and BigQuery, providing a path for analytics and machine learning functionalities. This is carried out while simplifying the process of application development and integration of devices. 

The Cloud Healthcare API can accelerate digital transformation for healthcare organizations and help new entrants to integrate with networks easily. Beyond this, the API allows to unlock the potential of advanced technologies and drive the next generation of healthcare solutions.

Data Model

Google Cloud Healthcare API implements fully managed REST API in JSON format, one of the most widely used API paradigms, which contains a set of operations based on the HTTP protocol and is identifiable by a URL. The API ingests and manages data of the following data types for applications across various healthcare operations:

  • FHIR (Fast Healthcare Interoperability Resources): Considered the standard for the interoperability of healthcare data today, FHIR can transform data from other formats into its resources. This is helpful in getting data ready for functions, including AI/ML applications and data analytics.
  • HL7v2 (Health Level 7 v2): Widely used interface for the integration of healthcare systems, it can function as a communication channel between healthcare applications and existing systems.
  • DICOM (Digital Imaging and Communications in Medicine): This is a popular standard for storing and accessing medical imaging data, including x-ray, MRI, and CT scans, and has applications across multiple healthcare disciplines, including radiology. DICOM helps users of Google Cloud Healthcare API to connect medical imaging data to ML and analytics tools.

Enabling large-scale analytics and machine learning

In Cloud Healthcare API, the health information is stored in datasets and stores. Each of these stores is associated with any of the three data types (FHIR, HL7v2, and DICOM), and data can be streamed into the stores using API calls. 

The data types are then linked to a pub/sub topic such that every time new data enters, a message to a given topic is triggered. The message contains the path of the resource which changed and, using ML function or data analytics, we can perform the required action. 

The Cloud Healthcare API allows exporting data from a store directly to other analytics tools such as BigQuery and Dataflow or ML tools such as Looker. With these state-of-the-art tools, organizations can simplify custom ML model training and rapidly develop, test, and deploy production-grade ML models. 

It is also easy to export outputs of these ML models directly to cloud storage and integrate them into existing clinical workflows. 

Bringing a myriad set of features to enter the future of healthcare

Google Cloud Healthcare API has numerous features that are integral for next-generation healthcare systems and applications.

Compliance with data privacy requirements:

Cloud Healthcare API has built-in multi-layered security systems that leverage encryption and utilize robust authentication tools to ensure data privacy.  The API also offers a centralized solution to manage privacy and consent, adaptable to regulations and consent models. It complies with global regulations such as HIPAA, 21 CFR Part 11, PIPEDA, and various other standards, along with Google Cloud’s security, privacy, compliance assessments for industry standards. 

Data Security:

With data security a core component, Cloud Healthcare API has its own highly secure Identity and Access Management (IAM) system that gives stakeholders control over their access to data. Besides, Google uses its Apigee API Management System that provides traffic management and threat detection capabilities, allowing authorized access to PHI with patient and provider applications.

Bulk Import and export:

Google Cloud Healthcare API supports bulk export and import of data which is available on FHIR and DICOM modalities. This allows easy transfer of data sets via the Cloud transfer system, speeding up time-to-delivery for healthcare applications.

De-identification:

This process of breaking the link between data and users with whom data is initially associated is made possible for DICOM by Google Cloud Healthcare API. This is especially effective in the case of research purposes.

Developer-friendly:

The healthcare information is organized into datasets with multiple modality-specific stores per set making it easy for developers to work with. 

Empowering healthcare organizations to improve care and research

Google Cloud Healthcare API brings multi-fold benefits for healthcare organizations. Here are few use cases:

Hospitals: Empower physicians with a holistic view of data and deliver better outcomes. For example, providers can bring data together as patients move from one hospital to another of the same hospital chain and care for patients remotely even after leaving the hospital.

Health Plans: The API enables payers to analyze patient information and also helps patients to securely access data via smartphones and make informed health decisions. Another instance is where payer organizations can input patient data into the system and easily determine the patient’s coverage for specific procedures or medications.

Application Developers: It supports vendors to make digital health solutions, such as for medical and imaging records, more seamless and provides secure access between healthcare providers and patients. Cloud Healthcare API is developer-friendly and allows them to work faster and efficiently.

Research organizations: CROs and non-profit research organizations can leverage clinical data to make models predicting diseases such as Diabetes. It also has applications in clinical trial management and other related areas.

Google’s Healthcare Data Engine to harmonize data

Data harmonization is an initial and crucial step to achieving true interoperability since information is mostly collected using different coding schemas and gathered in disparate buckets. By harmonizing data, we can bring together information of varying file formats and standards and transform the data into a cohesive, standardized dataset for analysis.

Building on the core capabilities of Google Cloud Healthcare API, Google Cloud has introduced a new tool named ‘Healthcare Data Engine’ to harmonize data from multiple sources such as clinical trials, research data, and medical records. Google Cloud’s Healthcare Data Engine integrates and standardizes data to provide a holistic view of patient longitudinal records in real-time. Currently, in private preview, the end-to-end solution enables advanced analytics and AI in a secure, compliant, and scalable cloud environment.

The platform can convert healthcare data in any form, whether it’s HL7 or CSV, to FHIR format. Further, Healthcare Data Engine can map more than 90 percent of HL7v2 messages in clinical messaging format to FHIR across leading EHR systems. This becomes the foundation for enabling interoperability across the organization.

Google Cloud’s Healthcare Data Engine brings the analytics and AI power through BigQuery, Google’s fully-managed, self-scaling warehousing and analytics engine. This facilitates healthcare organizations to process and visualize petabytes of patient information.

Benefits of Google Cloud’s Healthcare Data Engine

  • It enables healthcare organizations to get up and running quickly and avoids the need to create custom tooling or services to translate between data schemas
  • With Healthcare Data Engine, healthcare and life sciences organizations can make better real-time decisions—whether it is around resource utilization, optimizing clinical trials, accelerating research, identifying high-risk patients, reducing physician burnout.
  • Optimize care pathways and streamline operations by better understanding your healthcare data.
  • Empowers organizations with rapid scaling abilities as they produce voluminous amounts of data.
  • All this can be done while ensuring the highest security levels, compliance, and user privacy.

How can BTC help?

As a Google Cloud Partner, we can help you significantly reduce the time and effort needed to integrate and harmonize data from disparate healthcare applications to the cloud. By harnessing the power of Cloud Healthcare API, you can standardize healthcare data and get the foundation for reporting advanced analytics and machine learning. To see how BTC can help you achieve this, contact us.

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