AI

Rhapsody introduces AI for Identity with Rhapsody Autopilot

AI-powered Functionality Automates Data Stewardship and Lowers Costs by Reducing the Need for Manual Intervention

Rhapsodya global leader in digital health enablement, announced Rhapsody Autopilot, a first-of-its-kind technology that uses machine learning (ML) to automatically link person records, in line with customer preferences, for a comprehensive view. The technology includes a companion feature, Rhapsody Copilot, which uses AI to guide the data steward in their decision-making. The initial release of this technology is planned for late summer as part of Rhapsody EMPI v12.1.

Healthcare information is created at an increasingly rapid and accelerating rate, making identity data governance a resource-intensive process. Rhapsody Autopilot mirrors human decision-making to resolve data linking and data quality issues. It automates preferred actions, improving downstream credibility and reducing the workload on data stewards and data consumers like clinicians. Ultimately, lower duplicate rates lead to higher patient safety and quality.

“Healthcare organizations seek ways to drive higher-quality data while reducing cost. Using AI to automate data stewardship is the perfect use case for technological advancements to achieve those goals,” said Sagnik Bhattacharya, CEO of Rhapsody. “With Rhapsody Autopilot, we’re helping improve the effectiveness of teams and products otherwise hampered by poor data quality and incomplete views.”

This ML technology makes the same decisions an organization would make, in an always consistent way. Without this technology, a team of 10 people would only solve the same problem in the same way roughly 72% – 85% of the time. Healthcare organizations leveraging Rhapsody Autopilot have seen decisions aligning to organizational matching guidelines 98% of the time, improving accuracy and saving significant hours and money. By automating data stewardship, teams potentially save $150,000 for every 100,000 data quality tasks and 50,000 hours of data steward time by evaluating over 2M records in less than 80 minutes.

Rhapsody Autopilot is trained to look inward at the customer’s data, using the organization’s data quality preferences and guidelines to resolve data quality issues. Customers continue to receive full transparency to how decisions are made, the data used to make those decisions, and ongoing data lineage.

“Rhapsody Autopilot uses a neural network-based model trained with data steward tasks to mirror and automate the decisions a human would make,” said Lynn Stoltz, product manager for Rhapsody EMPI. “By enabling customers to bring their data together in alignment with their preferences, we set a new standard for this age-old problem. We believe this will fundamentally change the approach that healthcare organizations take towards patient matching.”

Looking ahead, Rhapsody is focused on making its products smarter through targeted use of AI and ML, while creating infrastructure to enable other AI companies to accelerate innovation. Rhapsody connects the healthcare ecosystem seamlessly with composable solutions for integration, identity, and semantic interoperability. Rhapsody health solutions are built to scale, accelerate innovation, and reduce the time it takes to move from idea to adoption, all with the intent of reducing clinician burden and removing limits to more-informed patient care. Plus, Rhapsody meets customers where they are with the industry’s most flexible deployment options, including cloud deployments or integration platform as a service.

More than 1,700 provider groups, health systems, digital health companies, and public health agencies across 22 countries rely on Rhapsody to accelerate digital health innovation and adoption through interoperability.

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