The American healthcare system faces a triple threat - rising administrative costs, physician burnout and a global nursing shortage. A 2022 report by the Council for Affordable Quality Healthcare found a 30% increase in healthcare administrative costs, reaching $60 billion annually. This burden coincides with physician burnout reaching 53% in 2022, according to Medscape. Additionally, the World Health Organization (WHO) reported a global nursing shortage exceeding 13 million in 2020.
These challenges present a significant opportunity for innovation. Healthcare providers, insurance companies, electronic health record developers and life science companies can leverage AI, particularly generative AI, to create solutions that benefit healthcare workers.
This is what pushed Google Cloud to launch new solutions – Vertex AI Search for Healthcare, Healthcare Data Engine (HDE) and MedLM – to help healthcare and life sciences organizations enable interoperability, build a better data foundation for their businesses and deploy GenAI tools to improve patient outcomes.
Vertex AI Search for Healthcare allows developers to build better assistive technology for clinicians and healthcare workers, alleviating their administrative burden. It offers medically tuned GenAI search capabilities across a broad range of healthcare data, including Fast Healthcare Interoperability Resources data and clinical notes.
This search and question-answering functionality now integrates with MedlinePlus, Healthcare Data Engine and Cloud Healthcare FHIR APIs. This streamlined approach simplifies building data analytics and AI solutions for next-generation healthcare systems.
“Vertex AI Search for Healthcare is making a difference for healthcare organizations by helping ensure clinicians have the right information and insights at the right time to inform decisions and improve the overall quality of patient care,” said Aashima Gupta, Global Director for Healthcare Strategy and Solutions, Google Cloud.
Google Cloud is also making its Healthcare Data Engine more accessible to healthcare organizations worldwide. HDE now operates as a consumption-based, pay-as-you-go managed service. This broader availability allows a wider range of healthcare organizations to deploy, build and manage near real-time healthcare data platforms in the cloud.
HDE expanded its reach beyond North America, with a planned rollout for most cloud regions in Europe and Asia Pacific. This increased global reach allows for wider adoption of the platform.
A new low-code graphical integrated development environment called HDE Data Mapper is also introduced. Built by Google Research specifically for healthcare, this tool simplifies data transformation and facilitates the creation of high-quality longitudinal patient records in FHIR format, a crucial element for powering gen AI applications.
Plus, the integration with Vertex AI Search for Healthcare allows clinicians to search across various systems and formats in a single search. This saves valuable time that can be redirected toward patient engagement and improving the overall patient experience. (Not to mention, the integration with MedLM allows users to answer complex questions directly informed by patient data.)
Futhermore, Google Cloud expanded MedLM capabilities for healthcare customers. MedLM, a suite of foundation models tailored for healthcare applications, offers two new features for exploration and testing:
- Chest X-ray Classification: This domain-specific model, launched as an API, converts chest x-ray images into data usable by machine learning models. Developers can leverage these embeddings with labeled data to train custom classification models within Vertex AI for various use cases, including operational efficiency, screening and diagnostics.
- Condition Summary API: This task-specific API provides a chronological list of patient conditions alongside AI-generated summaries for each condition, complete with citations from source documents.
Google Cloud plans to introduce further functionalities to the MedLM suite in the coming months.
"Not all generative AI is created equal, and in healthcare, the stakes are particularly high," said Gupta. "Healthcare organizations require enterprise-grade gen AI solutions, grounded in real data.
Google Cloud always emphasizes its commitment to customer data control. In healthcare, the company ensures patient data privacy through secure infrastructure, compliant data storage practices that adhere to HIPAA regulations and adherence to individual customer security and privacy controls.
