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Exploring Emerging Health Care Tech in the U.S.

To gather information on emerging health care technologies, the U.S. Department of Veterans Affairs (VA) is looking for capability, delivery and market information on a wide spectrum of clinical and administrative areas. The Accelerating VA Innovation and Learning program aims to gather enough information to inform possible procurements and identify interested parties for technologies ranging from advanced manufacturing and digital twins to Artificial Intelligence (AI), immersive-reality simulations and blockchain solutions.

According to the recent request for information, the VA wants insights into the design, development, manufacturing and testing of customised medical devices, such as anatomical models for pre-surgical planning, personalised prosthetics, surgical instruments, personalised dental equipment, assistive technologies and bio-fabrication.

When it comes to data transformation, VA is looking at decision-support and AI tools for chronic disease management in high-risk patient populations, vulnerable or underserved patient populations and those with acute conditions like sepsis. Application programming interfaces will be considered for data-driven care and administrative tasks. Synthetic data solutions are also of interest. The VA expects these data solutions to integrate with the existing VA workflows, clinical information systems and product lines.

About digital twins, VA wants contractors to evaluate the feasibility of virtual models as architectural blueprints for planned or future clinical spaces and facilities like an exam or operating rooms and also to speed adoption of emerging technologies, like 3D printing, into clinical care.

Digital twin solutions should consider virtual and augmented reality and be able to model ​​future clinician and operational workflows for resource forecasting, the RFI said.

Additionally, VA requests contractor insights into 5G-enabled or augmented technology solutions that could improve real-time remote and virtual care delivery and bring greater connectivity with edge devices. Examples include AR-guided surgical navigation and patient wearables.

For patients, VA is interested in immersive and simulation technologies that it can use for alternative therapies for mental health disorders, clinical training, virtual individual and/or group clinical visits and virtual rehabilitation. For clinical use, it wants to hear about simulation solutions that would help it integrate emerging technology and workflow optimisation tools.

On the business side, the VA is looking for information on innovative clinical and business models that would enhance or streamline existing VHA processes, improve veteran health outcomes and save money. Strategic planning, program and project scheduling support services are also of interest.

Contractors are expected to provide programmatic and implementation support for solutions as well as assistance with replication and scaling, measurement and analytic support. All deliverables are expected to take the form of monthly progress reports, which will serve as a barometer for both progress in implementation and for insights gained during the process.

As reported by OpenGov Asia, the U.S. has been using technologies, specifically AI in the healthcare industry. AI has the potential to help doctors accurately diagnose patients and predict the risk for complex diseases. Using AI, one can generate models that health care providers can use to predict patients’ risk for heart disease, cancer and various other conditions. However, AI must be trained using data from multiple providers to make the models accurate.

While health care generates vast amounts of data year after year, most of it isn’t available because of the need to protect identifiable patient information. With limited data access, AI models often aren’t as reliable in the real world, limiting how they can be used within healthcare.

To expand AI applications while still protecting patient data, the U.S. Department of Energy (DOE) has committed $1 million toward a one-year collaborative research project. The goal of the project is to create a secure AI framework that enables health care organisations to improve AI models used in biomedicine while keeping sensitive data secure.

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