Google Cloud Launches General Availability of Vertex AI Search for Healthcare and Healthcare Data Engine

Google Cloud’s solutions help healthcare organizations improve medical systems and provide better care

SUNNYVALE, Calif., Oct. 17, 2024 /PRNewswire/ — Google Cloud today announced Vertex AI Search for Healthcare and several new features for Healthcare Data Engine are now generally available to global allowlist customers. Vertex AI Search for Healthcare helps developers build better assistive technology for healthcare workers to alleviate administrative burdens, and Healthcare Data Engine helps organizations build an interoperable data platform, the foundation of generative AI (gen AI). When used together, these products can accelerate digital transformation in healthcare, improving systems and enhancing patient care.

A new report from Google Cloud and The Harris Poll today showed that healthcare professionals are drowning in administrative work, with clinicians spending nearly 28 hours per week and medical office staff spending 34 hours per week on tasks like documentation, scheduling, billing and coding, and inventory management. Claims staff face a similar burden, dedicating 36 hours per week to administrative duties. This overload leads to burnout, with 82% of clinicians, 81% of medical staff, and 77% of claims staff reporting feeling burnt out. Ultimately, this reduces valuable time spent with patients, impacting the quality of care, as 80% of providers acknowledge that administrative tasks take away from patient interaction.

“The administrative burden on healthcare workers is immense, taking precious time away from what matters most: patient care,” said Lisa O’Malley, senior director, Cloud AI Applications, Google Cloud. “With the general availability of Vertex AI Search for Healthcare and new features in Healthcare Data Engine, we’re providing powerful tools for our customers to build a strong data foundation and harness the power of generative AI to create more efficient and effective healthcare systems.”

Healthcare-specific data platform goes global

Also announced today, Healthcare Data Engine (HDE) is now available in countries around the world, including all of the regions where Google Cloud’s Healthcare API is available. HDE enables an interoperable, longitudinal record of patient data, and provides clinical insights in FHIR format, the healthcare industry standard. Because AI is only as good as the data it is using, this is a critical tool that companies globally can now use. Additional HDE updates include:

• Simplified, pay-as-you-go pricing model to better align with the value customers get from the platform.
• New managed service version of the product, making it easier to deploy, upgrade, and manage.
• New data mapping tool, called Data Mapper, that brings a graphical mapping interface into the product.

“We’re committed to leveraging data to drive innovation and improve patient care,” said Sameer Sethi, SVP and chief data and analytics officer, Hackensack Meridian Health. “Google Cloud’s Healthcare Data Engine provides the robust and scalable foundation we need to unlock the full potential of our data and it’s accelerating our journey towards more efficient, personalized, and proactive healthcare.”

“Embracing Google’s Vertex AI advances CHS further along our digital journey, enabling us to integrate cutting-edge technologies and gain valuable data insights that ultimately enhance the delivery of safety and healthcare to our patients,” said Patrice Bordron, SVP and Chief Digital Information Officer for Community Health Systems.

Healthcare search gets smarter, and saves time

Vertex AI Search for Healthcare can improve how healthcare professionals and other employees find critical information within health records and medical documents. Medical information is traditionally hard to search, given complex vocabulary and abbreviations. With this tool, those nuances are understood in one intelligent search. And, thanks to integration with Gemini 1.5 Flash and MedLM – Google’s medical large language model – Vertex AI Search for Healthcare can generate answers to questions about the patient record, making the information easier to find and digest. In addition, Vertex AI Search uses the organization’s data to search, grounding gen AI outputs in this data to reduce the risks of hallucinations or inaccurate responses. It can cite and link to original, internal sources of the information, giving the user confidence in where information is coming from.

“MEDITECH is committed to empowering clinicians with cutting-edge tools that streamline their workflows and enhance patient care,” said Helen Waters, Executive Vice President and COO, MEDITECH. “By integrating Google Cloud’s Vertex AI Search for Healthcare into our Expanse EHR, we’re providing clinicians with an intuitive and efficient way to access the precise information they need, when they need it. This translates to reduced administrative burden, improved decision-making, and ultimately, better outcomes for patients.”

For more information on these technology advancements for healthcare and life sciences, stop by the Google booth #3013 at HLTH, and please contact your Google Cloud sales team to learn more.

Google Cloud’s LLM medically-tuned and multimodal capabilities

Google Cloud’s AI models offer advantages to healthcare organizations. MedLM offers a family of large language models (LLMs) specifically trained on medical data, and Gemini offers a vast context window that can analyze extensive patient records and research data. An organization can select the LLM that works best for the solution its building, to provide clinicians with comprehensive insights for informed decision-making and assist in tasks like answering complex medical questions, summarizing research findings, and streamlining administrative processes, such as claims processing and appointment scheduling.

“One of the best things about Google is how we share what we learn across the company, and our Google Cloud customers benefit from this,” said O’Malley. “The latest example of this is how we have applied what we’ve learned with MedLM to Gemini to work well when used to build healthcare solutions. This is particularly powerful when combined with Gemini’s multimodal capabilities, which allow it to process and analyze information from diverse sources like medical images, clinical notes, and genomic data, alongside text. Imagine Gemini analyzing a patient’s X-ray, EKG reading, and blood test results in conjunction with their medical history to provide a doctor with a more comprehensive and accurate view. Or, picture it helping researchers identify potential drug candidates by sifting through millions of research papers and clinical trial reports, ultimately accelerating the development of life-saving treatments. These are just a few examples of Gemini’s multimodal capabilities that will improve healthcare.”

Google Cloud’s customers retain control over their data. In healthcare settings, access and use of patient data is protected through the implementation of Google Cloud’s reliable infrastructure and secure data storage that support HIPAA compliance, along with each customer’s security, privacy controls, and processes.

About Google Cloud
Google Cloud is the new way to the cloud, providing AI, infrastructure, developer, data, security, and collaboration tools built for today and tomorrow. Google Cloud offers a powerful, fully integrated and optimized AI stack with its own planet-scale infrastructure, custom-built chips, generative AI models and development platform, as well as AI-powered applications, to help organizations transform. Customers in more than 200 countries and territories turn to Google Cloud as their trusted technology partner.

Survey methodology
This survey was conducted online within the United States by The Harris Poll on behalf of Google from Aug. 26 – Sept. 9, 2024, among 821 healthcare providers and 209 payors in the U.S. The sampling precision of Harris online polls is measured by using a Bayesian credible interval. For this study, the data for the healthcare sample is accurate to within + /- 3.4 percentage points and the data for the payor sample is accurate to within +/- 6.7 percentage points using a 95% confidence level. For complete survey methodology, including subgroup sample sizes, please contact [email protected]. 

SOURCE Google Cloud

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