They will be in the Nuance AI Marketplace for Diagnostic Imaging, which is designed to provide a one-stop shop for radiologists to review and purchase AI models to improve their workflow.
At HIMSS20 next month, Nuance Communications, an AI-based clinician information systems vendor, will introduce new systems to the Nuance AI Marketplace for Diagnostic Imaging designed to provide a one-stop shop for radiologists to review and purchase AI models to improve their workflow.
The AI Marketplace is similar to the idea of an app store – a digital marketplace that enables subscribers to purchase applications, or, in the case of Nuance, AI models. The goal is to connect developers to radiologists, creating a direct line of communication to help build and improve AI models to meet their evolving needs and improve functionality of algorithms from development to practice.
Integrate AI models, collaborate on development
The AI Marketplace provides radiologists with tools for reading and reporting efficiencies, giving radiologists a unique opportunity to integrate AI models from various developers, collaborate on AI development and improvement, and ease administrative burdens of physicians overall, said Karen Holzberger, senior vice president and general manager, diagnostics, at Nuance Communications.
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“The solutions available in our AI Marketplace automate routine reporting and image analysis, aid in diagnosis, and help uncover incidental findings,” Holzberger explained. ”The ability to automate these tasks helps radiologists spend more time on higher priority cases. For example, one FDA-cleared application analyzes CT exams indicating a suspected intracranial hemorrhage, then prioritizes them based on the workflow for a radiologist’s immediate attention in cases when time-to-treatment is critical.”
AI tech amplifies intelligence
Nuance’s vision for AI is a world where technology amplifies intelligence to unburden caregivers and care teams from the distractions and complexities that get in the way of helping patients.
“AI, for us, has everything to do with making things simpler across the care continuum,” she explained. “It’s about deconstructing the workflow of physicians, nurses, care teams, radiologists and clinical documentation support teams to automate the mundane and deliver insights. That way, the path to their best care emerges as fast as possible. Amplifying, simplifying and surfacing the knowledge that your care teams rely on every minute of every day is how we multiply the collective power of providers to improve patient health on a global scale.”
AI is vital to the future of healthcare as current systems are outdated and in need of transformation, she contended.
“Physicians increasingly are burned out and bogged down with administrative burdens and increasing demands on their time,” she said. “Physicians spend much of their day capturing information instead of interacting with and taking care of patients. For each hour a physician spends with a patient, physicians spend two hours on administrative tasks.”
The healthcare industry cannot afford to ignore this problem, and AI is the optimal solution for repetitive, routine clinical tasks that can be automated, freeing the physician from burdensome documentation, she said.
AI technology adoption challenges
One challenge with artificial intelligence is giving providers the tools needed to put AI in action in everyday clinical practice by integrating them in physicians’ workflows in ways appropriate to each medical specialty or department, Holzberger contended.
“Integration also must enhance workflows in natural and intuitive ways with clear improvements in quality and efficiency, and in patient and financial outcomes,” she said. “Provider satisfaction feedback is as important as what the performance metrics say.”
With so many options available on the market today, it can be hard to identify what AI systems to choose, she added.
“As CIOs look to implement AI in their practice, they should first start by evaluating pain points in hospital operations and workflows, and identifying where technology can make the most impactful improvements,” she advised. “With this vantage point, finding a technology partner with the expertise, scale and tools to solve their specific challenges becomes much easier.”
Another challenge: Trust
Another challenge is, simply, trust, she continued.
“As AI becomes more widely implemented in real-world clinical practice, we will see more academic reports on the clinical benefits that have arisen from the real-world use of AI,” she said. “With more clinical evidence, we’ll see AI become more mainstream in various clinical settings, creating a positive feedback loop of evidence-based research and use in the field.”
However, this positive feedback loop between clinicians, AI developers, patients and academics takes time. Earning trust and demonstrating value of AI through evidence-based research will continue to be a challenge but a major point of growth, she said.
“Seemingly incremental change will add up to a completely integrated experience for the patient and caregiver alike,” she said. “AI will become more pervasive as the experience becomes more passive and integrated in smaller, more nuanced ways.
“Looking forward,” she concluded, “the goal is to incorporate AI as another tool to help physicians make the best care decisions possible.”
Source: Healthcare IT News